| user_dict |
{'id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'name': 'andrewzm', 'fullname': 'Andrew Zammit Mangion', 'created': '2014-11-25T10:23:45.276071', 'about': '', 'last_active': '2025-04-07T07:07:56.775376', 'activity_streams_email_notifications': False, 'sysadmin': True, 'state': 'active', 'image_url': None, 'display_name': 'Andrew Zammit Mangion', 'email_hash': '99c737296496dab77aaad22ec5ce56b7', 'number_created_packages': 31, 'image_display_url': None, 'datasets': [{'author': 'Australian Bureau of Statistics', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '700d2403-2181-41b9-a1d0-05d407d937c5', 'isopen': True, 'license_id': 'cc-by', 'license_title': 'Creative Commons Attribution', 'license_url': 'http://www.opendefinition.org/licenses/cc-by', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm@uow.edu.au', 'metadata_created': '2017-07-17T13:20:37.434903', 'metadata_modified': '2019-08-08T02:38:30.275744', 'name': 'mfi_abs_2011', 'notes': '## Description\r\n\r\nThis dataset\'s primary purpose is to reproduce the results in Section 4.4 in *A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields* by Zammit-Mangion and Rougier, which can be found [here](https://arxiv.org/abs/1707.00892). All data here was produced by the **Australian Bureau of Statistics** and is freely available under the Creative Commons Attribution 2.5 Australia License.\r\n\r\nThe ZIP file contains two folders, census_data and shapefiles. These are discussed in turn.\r\n\r\n**census_data**\r\n\r\nThis folder contains 9 CSV files. \r\n* The filenames containing "SA1" contain data at the SA1 level, while the filenames containing "SA2" contain data at the SA2 level.\r\n* The filenames containing "B02" contain selected median and averages of income (not used in the study).\r\n* The filenames containing "B16" contain data on education. Note that "B16A" and "B16B" refer to "Book A" and "Book B" of the same dataset.\r\n* The filenames containing "B26" contain family income data.\r\n\r\nThe folders "About DataPacks" and "MetaData" contain more information about the datasets. To access entire DataPacks, please visit the [DataPack webste](https://datapacks.censusdata.abs.gov.au/datapacks/).\r\n\r\nThe other file in this folder is censuscounts_mb_2011_aust.csv. This contains the Census counts at the Mesh Block level and this data can be downloaded from [here](http://www.abs.gov.au/websitedbs/censushome.nsf/home/meshblockcounts).\r\n\r\n**shapefiles**\r\n\r\nThis folder contains shapefiles of the Mesh Blocks (MB) in New South Wales (NSW), those for the SA1 regions and those for the SA2 regions for all of Australia. These shapefiles are freely available from (here)[http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1270.0.55.001July%202011].\r\n\r\n## Instructions\r\n\r\nTo reproduce the results in the manuscript, please place the two folders in the source directory containing the script files and run `Example3_SAs.R`.\r\n\r\n## References\r\n\r\nAustralian Bureau of Statistics, 2013. Mesh Block counts.\r\nURL http://www.abs.gov.au/websitedbs/censushome.nsf/home/meshblockcounts\r\n\r\nAustralian Bureau of Statistics, 2016.1270.0.55.001 - Australian Statistical Geography Standard (ASGS): Volume 1 - Main Structure and Greater Capital City Statistical Areas, July 2011.\r\nURL http://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/1270.0.55.001July%202011\r\n\r\nAustralian Bureau of Statistics, 2017. Census Datapacks.\r\nURL https://datapacks.censusdata.abs.gov.au/datapacks/', 'num_resources': 4, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'ABS 2011 Census data on Mean Family Income', 'type': 'dataset', 'url': 'www.abs.gov.au', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2017-07-17T23:38:50.925525', 'datastore_active': False, 'description': 'Please download all parts of the ZIP archive and extract using 7z (http://www.7-zip.org/download.html).', 'format': 'ZIP', 'hash': '', 'id': 'fdc8021e-035b-4105-befb-1fba19dc9f8c', 'last_modified': '2017-07-18T08:05:16.135231', 'metadata_modified': '2017-07-17T23:38:50.925525', 'mimetype': None, 'mimetype_inner': None, 'name': 'Datasets and Shapefiles for MFI Study: Part 1', 'package_id': '700d2403-2181-41b9-a1d0-05d407d937c5', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/700d2403-2181-41b9-a1d0-05d407d937c5/resource/fdc8021e-035b-4105-befb-1fba19dc9f8c/download/mfistudy.zip.001', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2017-07-18T18:12:12.942810', 'datastore_active': False, 'description': 'Please download all parts of the ZIP archive and extract using [7z](http://www.7-zip.org/download.html)', 'format': 'ZIP', 'hash': '', 'id': 'e2c22c7d-68e8-4f67-a7b5-248c61a9411a', 'last_modified': '2017-07-18T08:51:50.718956', 'metadata_modified': '2017-07-18T18:12:12.942810', 'mimetype': None, 'mimetype_inner': 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'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/700d2403-2181-41b9-a1d0-05d407d937c5/resource/959b73cb-975a-4370-99ff-2d2b94b5bcab/download/mfistudy.zip.003', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2017-07-18T18:21:07.017707', 'datastore_active': False, 'description': 'Please download all parts of the ZIP archive and extract using [7z](http://www.7-zip.org/download.html)', 'format': 'ZIP', 'hash': '', 'id': 'fbc2803f-5303-4129-991e-b5b403c9ec74', 'last_modified': '2017-07-18T09:00:11.216824', 'metadata_modified': '2017-07-18T18:21:07.017707', 'mimetype': None, 'mimetype_inner': None, 'name': 'Datasets and Shapefiles for MFI Study: Part 4', 'package_id': '700d2403-2181-41b9-a1d0-05d407d937c5', 'position': 3, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/700d2403-2181-41b9-a1d0-05d407d937c5/resource/fbc2803f-5303-4129-991e-b5b403c9ec74/download/mfistudy.zip.004', 'url_type': 'upload'}], 'tags': [{'display_name': 'economy', 'id': 'd80b6b31-ef50-46e5-b65b-2dd89abcbef3', 'name': 'economy', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'mean family income', 'id': '9d764a06-41d4-473e-bcbc-b1decaf6e7f5', 'name': 'mean family income', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial datasets', 'id': 'd9775515-e12f-4573-beec-cc41f0acab25', 'name': 'spatial datasets', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '4929bad8-5057-41a1-be2e-e676ef1d6680', 'isopen': True, 'license_id': 'cc-by', 'license_title': 'Creative Commons Attribution', 'license_url': 'http://www.opendefinition.org/licenses/cc-by', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm@uow.edu.au', 'metadata_created': '2017-01-11T22:33:59.817447', 'metadata_modified': '2017-02-06T05:51:42.102187', 'name': 'soil-data', 'notes': '## Description:\r\n\r\nSoil is a key factor affecting agricultural production. Soil maps at high spatial resolution are beneficial for both sound land management and profitable crop production.\r\n\r\nThe NSW Soils Data consists of the _total count_ for the full gamma ray spectrometer spectrum from three fields (F-Brigalow, 12-Brigalow, and Coda) covering about 2.66 km² of Nowley Farm (30.23°S, 150.24°E) in New South Wales, Australia.\r\n\r\nA ground-based gamma ray spectrometer (GRS), or gamma radiometer, measures broad radioactive emissions from elements such as potassium, uranium, and throium in the top 40-60 cm of the soil. In this particular soil survey, the GRS was run on a single vehicle, which was driven along (approximately) evenly spaced swaths, 30-40 m apart, in the direction of tillage. Location data was received from a single GPS mounted on the vehicle. Total count (TC) in counts per second (cps) from the GRS is the variable of interest, it integrates the entire spectrum and often shows strong spatial patterns.\r\n\r\nThe original TC dataset is made up of 34,266 data. Exploratory analysis indicated that measurement-error variance on the original scale depended on the measured value, and hence Cressie and Kang (2010) made a _shifted logarithmic transformation_.\r\n\r\nDefine the adjusted count (AC) as AC ≡ TC + 160; a spatial analysis was carried out on the transformed variable, Z ≡ log(AC) = log(TC + 160). The measurement-error variance on the transformed scale was identified from an independent study to be σ² = 0.0016.\r\n\r\n## Format:\r\n\r\nThe file Soil_X.mat contains the X-coordinates, Soil_Y.mat the Y-coordinates, and Soil_TC.mat the total counts. The file basis_fns.m contains a script for generating the basis functions for Fixed Rank Kriging of the total counts.\r\n\r\n## Reference:\r\n\r\nCressie, N. and Kang, L. (2010). High-resolution digital soil mapping: Kriging for very large datasets, in Proximal Soil Sensing, eds R.A. Viscarra Rossel, A. B. McBratney, and B. Minasny. Springer, Dordrecht, NL, 49-63. ', 'num_resources': 4, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'New South Wales (NSW) Soils Data', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2017-01-12T09:34:41.062462', 'datastore_active': False, 'description': '', 'format': 'MAT', 'hash': '', 'id': '07b3db78-57c0-4716-bc8a-5b88fa7891ff', 'last_modified': '2017-01-11T22:34:41.030848', 'metadata_modified': '2017-01-12T09:34:41.062462', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data X-coordinates', 'package_id': '4929bad8-5057-41a1-be2e-e676ef1d6680', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/4929bad8-5057-41a1-be2e-e676ef1d6680/resource/07b3db78-57c0-4716-bc8a-5b88fa7891ff/download/soilx.mat', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2017-01-12T09:34:49.063865', 'datastore_active': False, 'description': '', 'format': 'MAT', 'hash': '', 'id': '23bf30da-159e-4764-86db-9f5b8946f47d', 'last_modified': '2017-01-11T22:34:49.022564', 'metadata_modified': '2017-01-12T09:34:49.063865', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data Y-coordinates', 'package_id': '4929bad8-5057-41a1-be2e-e676ef1d6680', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/4929bad8-5057-41a1-be2e-e676ef1d6680/resource/23bf30da-159e-4764-86db-9f5b8946f47d/download/soily.mat', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2017-01-12T09:35:00.127028', 'datastore_active': False, 'description': '', 'format': 'MAT', 'hash': '', 'id': '26fd57c3-615c-4f15-a891-92dd8aa7537e', 'last_modified': '2017-01-11T22:35:00.085923', 'metadata_modified': '2017-01-12T09:35:00.127028', 'mimetype': None, 'mimetype_inner': None, 'name': 'Data Total Counts', 'package_id': '4929bad8-5057-41a1-be2e-e676ef1d6680', 'position': 2, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/4929bad8-5057-41a1-be2e-e676ef1d6680/resource/26fd57c3-615c-4f15-a891-92dd8aa7537e/download/soiltc.mat', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2017-01-12T09:35:25.747901', 'datastore_active': False, 'description': '', 'format': 'm', 'hash': '', 'id': '7c01be53-17c9-47d4-aab2-0ff88962d2a2', 'last_modified': '2017-01-11T22:35:25.701458', 'metadata_modified': '2017-01-12T09:35:25.747901', 'mimetype': None, 'mimetype_inner': None, 'name': 'Basis functions generation script for FRK', 'package_id': '4929bad8-5057-41a1-be2e-e676ef1d6680', 'position': 3, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/4929bad8-5057-41a1-be2e-e676ef1d6680/resource/7c01be53-17c9-47d4-aab2-0ff88962d2a2/download/basisfns.m', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '5ea8872b-fcd3-486c-9e89-027f23627d54', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T23:04:00.980529', 'metadata_modified': '2017-02-06T02:36:57.310482', 'name': 'tropical-pacific-sea-surface-temperature-sst-anomalies', 'notes': 'This data is hosted on the web page of Chris Wikle http://www.stat.missouri.edu/~wikle/datasets.html. The text below is copied from that website. \r\n\r\nDescription:\r\n----------------\r\n\r\nThese data represent gridded monthly SST anomalies for 399 consecutive months from January 1970 through March 2003. The data were obtained from the IRI/LDEO Climate Data Library at Columbia University (http://iridl.ldeo.columbia.edu/). The data are gridded at a 2 degree by 2 degree resolution and represent anomalies from a January 1970 - December 1985 monthly (average) climatology. A more complete description can be found at http://iridl.ldeo.columbia.edu/SOURCES/.CAC/\r\n\r\nReferences:\r\n----------------\r\n\r\nIn addition to Chapter 5 and 9 of Cressie and Wikle (2011), these data have been described and modeled in the following:\r\n\r\nBerliner, L.M., Wikle, C.K. and N. Cressie, (2000). Long-lead prediction of Pacific SSTs via Bayesian Dynamic Modeling. Journal of Climate, 13 , 3953-3968.\r\n\r\nWikle, C.K. and M.B. Hooten, 2010: A general science-based framework for spatio-temporal dynamical models. Invited discussion paper for Test. 19, 417-451.\r\n\r\nWikle, C.K. and S.H. Holan, 2011: Polynomial nonlinear spatio-temporal integro-difference equation models Journal of Time Series Analysis. DOI: 10.1111/j.1467-9892.2011.00729.x', 'num_resources': 3, 'num_tags': 4, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Tropical Pacific Sea Surface Temperature (SST) anomalies between 1970-1985', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T10:05:09.095630', 'datastore_active': False, 'description': '2520 x 2 matrix; longitude in first column and latitude in the second, corresponding to the spatial grid locations in SST011970_032003.dat; note: the longitudes are given from 124 to 290 by 2, corresponding to 124E to 290E (where 290E corresponds to 70W).', 'format': 'dat', 'hash': '', 'id': 'bc5f6017-d880-49eb-a730-260c6b855bd3', 'last_modified': None, 'metadata_modified': '2014-12-04T10:05:09.095630', 'mimetype': None, 'mimetype_inner': None, 'name': 'SSTlonlat', 'package_id': '5ea8872b-fcd3-486c-9e89-027f23627d54', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'http://www.stat.missouri.edu/~wikle/SSTlonlat.dat', 'url_type': ''}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T10:05:48.398737', 'datastore_active': False, 'description': '2520 x 399 matrix; 2520 spatial locations corresponding to an 84 (longitude) by 30 (latitude) grid with 2 deg x 2 deg spacing. The longitudes correspond to 124 E to 70W and the latitudes to 29S to 29N. There are 399 time periods representing sequentially the months from January 1970 through March 2003.', 'format': 'dat', 'hash': '', 'id': 'c5bcef95-1317-4679-a1c1-bef69d6d80c1', 'last_modified': None, 'metadata_modified': '2014-12-04T10:05:48.398737', 'mimetype': None, 'mimetype_inner': None, 'name': 'SST011970_032003', 'package_id': '5ea8872b-fcd3-486c-9e89-027f23627d54', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'http://www.stat.missouri.edu/~wikle/SST011970_032003.dat', 'url_type': None}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T10:06:11.444315', 'datastore_active': False, 'description': '2520 x 1 vector; land/sea mask corresponding to the grid locations in SSTlonlat.dat, with a value of 1 corresponding to a "land" location and a 0 corresponding to a water location.', 'format': 'dat', 'hash': '', 'id': '2a619e18-9c67-47cc-bd79-605c8ea7fc56', 'last_modified': None, 'metadata_modified': '2014-12-04T10:06:11.444315', 'mimetype': None, 'mimetype_inner': None, 'name': 'SSTlandmask', 'package_id': '5ea8872b-fcd3-486c-9e89-027f23627d54', 'position': 2, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'http://www.stat.missouri.edu/~wikle/SSTlandmask.dat', 'url_type': None}], 'tags': [{'display_name': 'El Nino', 'id': '9607bffd-2c5c-4c3a-ac1d-3fa9f6123cab', 'name': 'El Nino', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'SST', 'id': '4cc4b9d9-4b13-4c44-8894-d14800f9e64c', 'name': 'SST', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sea-surface temperatures', 'id': 'd4d00e65-3e2d-42f2-832c-3d2c5956c47f', 'name': 'sea-surface temperatures', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatiotemporal data', 'id': '4168f287-dac2-4ccf-b421-f502745b8669', 'name': 'spatiotemporal data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '84cc232b-908b-4075-83fb-bd517b80423c', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:41:10.928257', 'metadata_modified': '2017-02-06T02:36:39.336091', 'name': 'tco', 'notes': 'Description:\r\n---------------\r\n\r\nThe CSV file contains 173405 rows of level 2 TCO data obtained using the Nimbus-7 polar orbiting satellite on October 1st, 1988. \r\n\r\nFormat:\r\n----------\r\n\r\nThe file contains 6 columns.\r\n\r\n- scan: scan number\r\n- lon: longitude\r\n- lat: latitude\r\n- size: (please ignore)\r\n- angle: (please ignore)\r\n- ozone: TCO level 2 data.\r\n\r\nReferences:\r\n---------------\r\n\r\nCressie, Noel, and Gardar Johannesson. "Fixed rank kriging for very large spatial data sets." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 70.1 (2008): 209-226.', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Total Column Ozone data from the Nimbus-7 polar orbiting satellite', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:41:39.132006', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '907fd34e-ccf7-402c-9ce2-37d19c439b75', 'last_modified': None, 'metadata_modified': '2014-12-04T09:41:39.132006', 'mimetype': None, 'mimetype_inner': None, 'name': 'Ozone data used in Cressie and Johannesson (2008)', 'package_id': '84cc232b-908b-4075-83fb-bd517b80423c', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/84cc232b-908b-4075-83fb-bd517b80423c/resource/907fd34e-ccf7-402c-9ce2-37d19c439b75/download/toms881001.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'environment', 'id': 'e11a3571-4c5d-4a12-94f2-2de78265bccf', 'name': 'environment', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'ozone', 'id': '9b318b1d-0e67-453e-ae99-783e3fc5f681', 'name': 'ozone', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial data', 'id': '495c6bf0-9e18-48d5-9dfb-350c91aee049', 'name': 'spatial data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '8ce9b855-d1a3-4454-80e1-70598718a98a', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-21T22:38:49.797208', 'metadata_modified': '2017-02-06T02:36:21.881255', 'name': 'global-temperature-data', 'notes': 'Permission for dissemination of these data was given to us by the CESM Chief Scientist Jean-Francois-Lamarque 16/02/2015 by e-mail correspondence. These data can only be used for publication purposes. \r\n\r\nDescription:\r\n---------------\r\n\r\nThere are 21 files in the directory. The file “TREFHT_1980-1999.nc” (in netcdf format) contains the 2-meter air temperature (128 lon x 64 lat x 240 months) from 1980-1999. This file has also been transferred into 20 ASCII files, x1-x20 for years 1980-1999, respectively. There are 128x64x12 elements in each ASCII file, which can be input as an array in R by `array(“x1”,dim=c(128,64,12))`.\r\n\r\nThe data were generated from the NCAR Climate System Model. A part of this data set was used in Shen et al. (2002). \r\n\r\nReference:\r\n-------\r\n\r\nShen, X., Huang, H. C., & Cressie, N. (2002). Nonparametric hypothesis testing for a spatial signal. Journal of the American Statistical Association, 97(460), 1122-1140.\r\n', 'num_resources': 3, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Global temperature data from NCAR CSM', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-22T09:40:46.655047', 'datastore_active': False, 'description': '', 'format': '', 'hash': '', 'id': 'aac3afb3-0f3a-4525-8f0f-fb45234f212c', 'last_modified': None, 'metadata_modified': '2014-12-22T09:40:46.655047', 'mimetype': None, 'mimetype_inner': None, 'name': 'Global temperature data in NetCDF format 1980--1999', 'package_id': '8ce9b855-d1a3-4454-80e1-70598718a98a', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/8ce9b855-d1a3-4454-80e1-70598718a98a/resource/aac3afb3-0f3a-4525-8f0f-fb45234f212c/download/trefht19801999.nc', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-22T09:53:14.682127', 'datastore_active': False, 'description': '', 'format': 'ZIP', 'hash': '', 'id': '3f64dad9-9296-49e6-9e33-c32bdb445db3', 'last_modified': None, 'metadata_modified': '2014-12-22T09:53:14.682127', 'mimetype': None, 'mimetype_inner': None, 'name': 'Global temperature data in txt format (zipped) 1980 -- 1989', 'package_id': '8ce9b855-d1a3-4454-80e1-70598718a98a', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/8ce9b855-d1a3-4454-80e1-70598718a98a/resource/3f64dad9-9296-49e6-9e33-c32bdb445db3/download/trefht19801989.zip', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-22T09:54:13.092791', 'datastore_active': False, 'description': '', 'format': 'ZIP', 'hash': '', 'id': '1ba24f02-77e3-4a30-8ab0-d9d18c3c726e', 'last_modified': None, 'metadata_modified': '2014-12-22T09:54:13.092791', 'mimetype': None, 'mimetype_inner': None, 'name': 'Global temperature data in txt format (zipped) 1990 -- 1999', 'package_id': '8ce9b855-d1a3-4454-80e1-70598718a98a', 'position': 2, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/8ce9b855-d1a3-4454-80e1-70598718a98a/resource/1ba24f02-77e3-4a30-8ab0-d9d18c3c726e/download/trefht19901999.zip', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Sayre, R., J. Dangermond, C. Frye, R. Vaughan, P. Aniello, S. Breyer, D. Cribbs, D. Hopkins, R. Nauman, W. Derrenbacher, D.Wright, C. Brown, C. Convis, J. Smith, L. Benson, D. Paco VanSistine, H. Warner, J. Cress, J. Danielson, S. Hamann, T. Cecere, A. Reddy, D. Burton, A. Grosse, D. True, M. Metzger, J. Hartmann, N. Moosdorf, H. Dürr, M. Paganini, P. DeFourny, O. Arino, S. Maynard, M. Anderson, and P. Comer. ', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '03a2ff61-3021-405b-bf0b-614f3fa2ce20', 'isopen': False, 'license_id': 'cc-nc', 'license_title': 'Creative Commons Non-Commercial (Any)', 'license_url': 'http://creativecommons.org/licenses/by-nc/2.0/', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-01-25T02:11:46.436349', 'metadata_modified': '2017-02-06T02:35:59.602201', 'name': 'global-elus', 'notes': 'Description:\r\n-------\r\n\r\nIn response to the need and an intergovernmental commission for a high resolution and data-derived global ecosystem map, land surface elements of global ecological pattern were characterised in an ecophysiographic stratification of the planet. The stratification produced 3,923 terrestrial ecological land units (ELUs) at a base resolution of 250 meters. The ELUs were derived from data on land surface features in a three step approach. The first step involved acquiring or developing four global raster datalayers representing the primary components of ecosystem structure: bioclimate, landform, lithology, and land cover. These datasets generally represent the most accurate, current, globally comprehensive, and finest spatial and thematic resolution data available for each of the four inputs. The second step involved a spatial combination of the four inputs into a single, new integrated raster dataset where every cell represents a combination of values from the bioclimate, landforms, lithology, and land cover datalayers. This foundational global raster datalayer, called ecological facets (EFs), contains 47,650 unique combinations of the four inputs. The third step involved an aggregation of the EFs into the 3,923 ELUs.\r\n\r\n\r\n\r\nUse constraint:\r\n-------\r\n\r\nAlthough these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein. We make every effort to provide and maintain accurate, complete, usable, and timely information on our Web sites. These data and information are provided with the understanding that they are not guaranteed to be correct or complete. Users are cautioned to consider carefully the provisional nature of these data and information before using them for decisions that concern personal or public safety or the conduct of business that involves substantial monetary or operational consequences. Conclusions drawn from, or actions undertaken on the basis of, such data and information are the sole responsibility of the user. Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U. S. Government.\r\n\r\nData quality:\r\n-----\r\n\r\nThe primary accuracy assessment approach was to compare EFs at randomly generated points to their corresponding locations on high resolution imagery. This match of EFs to imagery was generally very high, with the following level of confirmation observed: Africa, 91%; California, 98%; Australia, 98%; and elsewhere in North America, 97%. The secondary accuracy assessment approaches included comparing ELUs to their corresponding ecosystem labels on the three GEO continental-scale ecosystem maps for South America, the conterminous United States, and Africa. The results for those comparisons were 88%, 87%, and 94%, for South America, the conterminous United States, and Africa, respectively. The comparison of EFs to other sources of thematic information yielded the following probable matches: Africa (81%), California (88%), Australia (96%) and elsewhere in North America (93%). Finally, for the Degree Confluence project points, a 100% match between the EFs and the VGI (photos and descriptions) was observed for Australia, and a 98% match was observed for elsewhere in North America.\r\n\r\nThe quality of the data used in the global stratification will obviously influence the quality of the derived ecosystem products, and anomalous values were found in each of the input layers. While some of these data quality issues are discussed below, it is important to first note that both the input layers and the output products should be considered as collaborative best efforts and works in progress, rather than definitive, current, and complete representations of their themes. The production of any high resolution, globally comprehensive datalayer that characterises a particular feature of the environment is an ambitious and sometimes very difficult undertaking. These efforts to develop and disseminate best available datasets are appreciated by the scientific community, and making the information broadly available is the best way to ensure it can be improved over time. Identification of anomalous values and other data quality issues in underlying data is important for both the understanding of unexpected results, and for the improvement of the input datasets. The bioclimates layer, as mentioned, represents an interpolated data surface from point observations obtained at meteorological stations. Some areas of the planet are not well-covered by weather stations, and the modeled climate regions in those areas (e.g. western Sahara Desert region) were developed from very little data. Moreover, we felt the original bioclimate regions were underrepresentative of aridity, and we modified the data accordingly. The landforms layer was built from a 250 m global DEM, and 250 m was the base resolution of the effort, given the big data nature of the effort and the difficulty of working at finer spatial resolutions. Nevertheless, 90 m and 30 m global DEMs do exist, and a finer spatial resolution global landforms layer could be developed. The global lithology layer, built as a compendium of a variety of best available regional and national scale lithology datasets, lacks complete attribution at all levels of the hierarchy, and does not attempt to reconcile or harmonise classes across maps from adjacent geographies produced by different organizations. The above-mentioned limitations in the data really represent opportunities for collective improvements in the characterization of ecologically important Earth surface features, and we anticipate working with these data providers and others in future collaborations to advance the quality, currency, resolution, and accessibility of Earth science data.\r\n\r\nProcedure:\r\n-----\r\n\r\nThe fundamental approach undertaken was to stratify the Earth into physically distinct areas with their associated land cover. The stratification was executed as a geospatial combination of the four input layers (bioclimate, landform, lithology, and land cover) to produce a single raster datalayer where every cell represented a unique combination of the four inputs. Following the production of the foundational raster datalayer, a data reduction step was undertaken to reduce the large number of combinations produced from the union of the input datalayers. The approach was undertaken in three steps. Step One involved acquiring or developing the four input raster base layers (bioclimates, landforms, lithology, and land cover), and reconciling them to a standard, 250 meter global raster framework. The choice of 250 m as the base resolution for the project was based on the availability of a global 250 m digital elevation model (Danielson and Gesch, 2011) whose raster framework could be used as the geospatial reference standard, as well as the desire to improve over the typical square kilometer resolution associated with many global data products (e.g. Gesch et al., 1999; Hijmans et al., 2005). Step Two involved combining all four raster inputs into a single master 250 m global raster datalayer where each cell was the resulting combination of the values from the four input rasters. This foundational raster dataset was called the ecological facets (EFs) layer. Finally, Step Three involved reducing the many classes of EFs resulting from the spatial combination into a more manageable and cartographically approachable number of ecological land units (ELUs). The aggregation was achieved by generalising the input layer attribute classes. This approach to developing global ELUs can be considered as classification neutral in the sense that no a priori ecosystem classification was used to label the mapped entities.\r\n\r\nOther:\r\n----------\r\n\r\nFor more user-friendly information on this dataset visit http://blogs.esri.com/esri/esri-insider/2014/12/09/the-first-detailed-ecological-land-unitsmap-in-the-world/. An interactive application for viewing the data is available at http://ecoexplorer.arcgis.com/eco/\r\n\r\nReferences:\r\n---------\r\n\r\nSayre, R., J. Dangermond, C. Frye, R. Vaughan, P. Aniello, S. Breyer, D. Cribbs, D. Hopkins, R. Nauman, W. Derrenbacher, D.Wright, C. Brown, C. Convis, J. Smith, L. Benson, D. Paco VanSistine, H. Warner, J. Cress, J. Danielson, S. Hamann, T. Cecere, A. Reddy, D. Burton, A. Grosse, D. True, M. Metzger, J. Hartmann, N. Moosdorf, H. Dürr, M. Paganini, P. DeFourny, O. Arino, S. Maynard, M. Anderson, and P. Comer. 2014. A New Map of Global Ecological Land Units — An Ecophysiographic Stratification Approach. Washington, DC: Association of American Geographers. 46 pages.', 'num_resources': 1, 'num_tags': 5, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Global Ecological Land Units (ELUs)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-01-25T13:12:29.526458', 'datastore_active': False, 'description': '', 'format': 'TIF', 'hash': '', 'id': 'a9361969-8413-4e3b-9423-32262592924c', 'last_modified': None, 'metadata_modified': '2015-01-25T13:12:29.526458', 'mimetype': None, 'mimetype_inner': None, 'name': 'USGS Geosciences and Environmental Change Science Center (GECSC) Outgoing Datasets', 'package_id': '03a2ff61-3021-405b-bf0b-614f3fa2ce20', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'http://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/', 'url_type': None}], 'tags': [{'display_name': 'bioclimate', 'id': '5b7ad1ae-9d20-4659-b774-c7302c969f4f', 'name': 'bioclimate', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'ecosystems', 'id': '3d088806-ca29-4558-b0a0-6f9b9d685e8e', 'name': 'ecosystems', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'land cover', 'id': 'f8aeb8b0-4202-47ea-a7a6-471bea6a47c0', 'name': 'land cover', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'landforms', 'id': '52c5e391-69d2-48f0-9f3b-cf33c56b4a20', 'name': 'landforms', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'lithology', 'id': '84bd1f5a-8b14-42aa-bc45-73b25c1ff5f4', 'name': 'lithology', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '8dcd387d-49be-4134-aea9-96a3d581f513', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-03-10T00:17:56.099475', 'metadata_modified': '2017-02-06T02:28:31.162942', 'name': 'locations-of-nyssa-tupelo-trees-in-south-carolina', 'notes': 'These data were made available in the data webpage of the [book by Gaetan and Guyon](http://www.dst.unive.it/~gaetan/ModStatSpat/datasets.html), courtesy of Philip Dixon.\r\n\r\nDescription:\r\n-----\r\nLocation of male, female, and juvenile tupelo trees in 3 plots in the Savannah River, Barnwell County, South Carolina. \r\n\r\nFormat:\r\n----\r\n\r\n- `plot`: number of the plot\r\n- `sex`: sex of the tree \r\n- `x`, `y`: coordinates.\r\n\r\nUsage:\r\n-----\r\n\r\n library(ggplot2)\r\n X <- read.table("~/Desktop/tupelo.txt",header=T)\r\n ggplot(X) + geom_point(aes(x,y,colour=sex)) + geom_facet(~plot())\r\n\r\n\r\n\r\nReferences:\r\n------\r\n\r\nShea, M.M., Dixon, P.M. and Sharitz R.R. (1993), Size differences, sex ratio, and spatial distribution of male and female water tupelo, Nyssa aquatica (Nyssaceae), American Journal of Botany, 80, 26--30.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Locations of Nyssa (tupelo) trees in South Carolina', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-03-10T11:18:11.949532', 'datastore_active': False, 'description': '', 'format': 'TXT', 'hash': '', 'id': '1778af58-4b74-4070-a0b6-7d9564f6f170', 'last_modified': None, 'metadata_modified': '2015-03-10T11:18:11.949532', 'mimetype': None, 'mimetype_inner': None, 'name': 'Tupelo dataset', 'package_id': '8dcd387d-49be-4134-aea9-96a3d581f513', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/8dcd387d-49be-4134-aea9-96a3d581f513/resource/1778af58-4b74-4070-a0b6-7d9564f6f170/download/tupelo.txt', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '76450eb9-53ea-418c-8d07-0fef59ebd1a2', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-03-10T00:59:23.624337', 'metadata_modified': '2017-02-06T02:28:07.660373', 'name': 'distribution-of-castanea-pumila-in-florida-with-covariates', 'notes': 'These data were made available in the data webpage of the [book by Gaetan and Guyon](http://www.dst.unive.it/~gaetan/ModStatSpat/datasets.html).\r\n\r\nDescription:\r\n-----\r\n\r\nDistribution of about 180 plants of Castanea pumila (species 38) in the state of Florida, and data on the values of four climate variables which are expected to be important factors in determining the distribution of the plant species.\r\n\r\nFormat:\r\n-----\r\n\r\n- `row`: row number\r\n- `col`: column number\r\n- `sp38`: incidence of Cuastanea pumila\r\n- `FZF`: median freeze-free period in days\r\n- `TAV`: mean annual temperature in degrees Celsius\r\n- `PRCP`: mean total annual precipitation in millimetres\r\n- `MI`: moisture index = (PRCP)/(TAV x 58.93), where TAV x 58.93 = estimate of mean annual potential evapotranspiration by the Holdridge method.\r\n\r\nUsage:\r\n----\r\n\r\n library(ggplot2)\r\n X <- read.table("~/Desktop/sp38data.txt",header=T)\r\n ggplot(X) + geom_tile(aes(col,row,fill=sp38))\r\n\r\n\r\n\r\n ggplot(X) + geom_tile(aes(col,row,fill=mi))\r\n\r\n\r\n\r\nReferences:\r\n----\r\nWu, H. and Huffer, F.W. (1997), Modelling the Distribution of Plant Species Using Autologistic Regression Model, Environmental and Ecological Statistics, 4, 49-64. \r\n\r\n[Fred Huffer\'s web page](http://stat.fsu.edu/~huffer/software/autologistic.shar)', 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Distribution of Castanea pumila in Florida with covariates', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-03-10T11:59:42.163989', 'datastore_active': False, 'description': '', 'format': 'TXT', 'hash': '', 'id': '42402d6f-71aa-4a42-8cfa-6f380511239f', 'last_modified': None, 'metadata_modified': '2015-03-10T11:59:42.163989', 'mimetype': None, 'mimetype_inner': None, 'name': 'Castanea data', 'package_id': '76450eb9-53ea-418c-8d07-0fef59ebd1a2', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/76450eb9-53ea-418c-8d07-0fef59ebd1a2/resource/42402d6f-71aa-4a42-8cfa-6f380511239f/download/sp38data.txt', 'url_type': 'upload'}], 'tags': [{'display_name': 'ecology', 'id': '6027bf7a-8465-4670-aa0a-ea3886383341', 'name': 'ecology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'plant', 'id': 'af7ef24c-fafe-4124-ad38-375db628a74d', 'name': 'plant', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'f9c24c5b-ec50-4cd7-b2c6-9a157e4d0513', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-03-10T00:51:51.186066', 'metadata_modified': '2017-02-06T02:27:26.139239', 'name': 'lung-cancer', 'notes': 'These data were made available in the data webpage of the [book by Gaetan and Guyon](http://www.dst.unive.it/~gaetan/ModStatSpat/datasets.html). The data are courtesy of Chantal Guihenneuc-Jouyaux.\r\n\r\nDescription:\r\n----\r\n\r\nMale lung cancer mortality rate standardised over the age range 35--74 and over 2 year period, 1968--1969 at the scale of the French départments. \r\n\r\nFormat:\r\n---\r\n\r\n- `poumon`: Male lung cancer mortality rate\r\n- `metallurgie`: Male percentage employed in metal industry\r\n- `mecanique`: Male percentage employed in mechanical industry\r\n- `textile`: Male percentage employed in textile industry\r\n- `vente tabac`: Cigarette sales\r\n- `numero departement`: Department number\r\n- `latitude`: Latitude of department (centroid?)\r\n- `longitude`: Longitude of department (centroid?).\r\n\r\nReferences:\r\n-----\r\n\r\nRicharson, S., Guihenneuc, C. and Lasserre, V. (1992), Spatial linear models with autocorrelated error structure, The Statistician, 41, 539-557. ', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Lung cancer mortality in French departments (1968--1969)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-03-10T11:52:36.173788', 'datastore_active': False, 'description': '', 'format': 'TXT', 'hash': '', 'id': '389eb6e0-1a9d-4228-9ca4-b6077046c096', 'last_modified': None, 'metadata_modified': '2015-03-10T11:52:36.173788', 'mimetype': None, 'mimetype_inner': None, 'name': 'Male lung cancer incidence', 'package_id': 'f9c24c5b-ec50-4cd7-b2c6-9a157e4d0513', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/f9c24c5b-ec50-4cd7-b2c6-9a157e4d0513/resource/389eb6e0-1a9d-4228-9ca4-b6077046c096/download/cancer.txt', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'c9990660-31a6-48af-a1fa-6f36b674b532', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-03-09T23:11:31.940478', 'metadata_modified': '2017-02-06T02:27:07.178378', 'name': 'ozone', 'notes': 'Description:\r\n-----\r\n\r\nThese data and much of the description below was obtained from the [UCAR website](http://www.image.ucar.edu/GSP/Data/O3.shtml). The data describe 8 hour average daily ozone in parts per billion (ppb) for 513 sites in the US over the ozone "season" which runs from April through October (184 days) for five years (1995--1999). \r\n\r\nFormat:\r\n-------\r\n\r\nDownload the file, `ozmax8.dat`, which has the actual ozone measurements (max 8-hr daily average). Units are concentrations in parts per billion (PPB). Also, download the file, `ozmax8.info.q`, This is a list with information about the data set: `station.no`: station number\r\n\r\n`lat`: latitude coordinate of station\r\n\r\n`lon`: longitude coordinate of station\r\n\r\n`dates`: observation timestamp. The times are in julian days where day 1 = JAN-01-1960. The actual times start on April 1, 1995. The ozone "season" runs from April through October ( 184 days) over five years (1995 - 1999). \r\n\r\nData import:\r\n-----\r\n\r\nPlease see the following example for importing and plotting the data. More details can be found [here](http://www.image.ucar.edu/GSP/Data/O3.shtml).\r\n\r\n ozmax8 <- matrix( scan("ozmax8.dat"), 920,513) \r\n source("ozmax8.info.q") \r\n # names( ozmax8.info) \r\n # are "stat.no" "lat" "lon" "dates" "loc" \r\n #\r\n # to plot station locations\r\n plot( ozmax8.info$lat, ozmax8.info$lon)\r\n\r\n\r\n\r\n # time series plot of first station\r\n plot( ozmax8.info$date, ozmax8[,1])\r\n\r\n', 'num_resources': 2, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Ozone data in ppb from 513 stations in the US (1995--1999)', 'type': 'dataset', 'url': 'http://www.image.ucar.edu/GSP/Data/O3.shtml', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-03-10T10:11:51.158098', 'datastore_active': False, 'description': '', 'format': 'dat', 'hash': '', 'id': '179f4920-bb54-426d-9c89-2fa7ba0625ad', 'last_modified': None, 'metadata_modified': '2015-03-10T10:11:51.158098', 'mimetype': None, 'mimetype_inner': None, 'name': 'Ozone data file', 'package_id': 'c9990660-31a6-48af-a1fa-6f36b674b532', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/c9990660-31a6-48af-a1fa-6f36b674b532/resource/179f4920-bb54-426d-9c89-2fa7ba0625ad/download/ozmax8.dat', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2015-03-10T10:12:41.824560', 'datastore_active': False, 'description': '', 'format': '', 'hash': '', 'id': '1db2d01c-f9e1-4efd-96a3-edc9e7f07b09', 'last_modified': None, 'metadata_modified': '2015-03-10T10:12:41.824560', 'mimetype': None, 'mimetype_inner': None, 'name': 'Ozone information file', 'package_id': 'c9990660-31a6-48af-a1fa-6f36b674b532', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/c9990660-31a6-48af-a1fa-6f36b674b532/resource/1db2d01c-f9e1-4efd-96a3-edc9e7f07b09/download/ozmax8.info.q', 'url_type': 'upload'}], 'tags': [{'display_name': 'ozone', 'id': '9b318b1d-0e67-453e-ae99-783e3fc5f681', 'name': 'ozone', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatio-temporal', 'id': 'f06bfac9-bff8-4613-8da7-921880f75326', 'name': 'spatio-temporal', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Grace Chiu', 'author_email': 'Grace.Chiu@csiro.au', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '754f03a2-79f8-464b-9499-ec4260ba0ed8', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:44:20.710660', 'metadata_modified': '2017-02-06T02:26:35.590940', 'name': 'murray-darling-basin-stream-gauge-daily-data-from-1990-to-2011-netcdf-format', 'notes': 'Description:\r\n---------------\r\nThis dataset was produced and is hosted by CSIRO Australia. The following description is taken directly from the CSIRO data portal website:\r\n\r\nThese four NetCDF databases constitute the bulk of the spatial and spatio-temporal environmental covariates used in a latent health factor index (LHFI) model for assessment and prediction of ecosystem health across the MDB. The data formatting and hierarchical statistical modelling were conducted under a CSIRO appropriation project funded by the Water for a Healthy Country Flagship from July 2012 to June 2014. Each database was created by collating and aligning raw data downloaded from the respective state government websites (QLD, NSW, VIC, and SA). (ACT data were unavailable.) There are two primary components in each state-specific database: (1) a temporally static data matrix with axes "Site ID" and "Variable," and (2) a 3D data cube with axes "Site ID", "Variable," and "Date." Temporally static variables in (1) include geospatial metadata (all states), drainage area (VIC and SA only), and stream distance (SA only). Temporal variables in (2) include discharge, water temperature, etc. Missing data (empty cells) are highly abundant in the data cubes. The attached state-specific README.pdf files contain additional details on the contents of these databases, and any computer code that was used for semi-automation of raw data downloads.\r\n\r\nReferences:\r\n------\r\n\r\nChiu, G.S., Wu, M.A., Lu, L. (2013). “Model-based assessment of estuary ecosystem health using the latent health factor index, with application to the Richibucto estuary,” PLoS One, 8, Issue 6, e65697.', 'num_resources': 1, 'num_tags': 5, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Murray-Darling Basin stream gauge daily data between 1990-2011', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:44:48.121557', 'datastore_active': False, 'description': 'CSIRO Data Access Portal redirection', 'format': 'NetCDF', 'hash': '', 'id': 'b0448130-2ca3-442f-ad0d-3eff298acab7', 'last_modified': None, 'metadata_modified': '2014-12-04T09:44:48.121557', 'mimetype': None, 'mimetype_inner': None, 'name': 'Stream gauge data', 'package_id': '754f03a2-79f8-464b-9499-ec4260ba0ed8', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://data.csiro.au/dap/landingpage?pid=csiro:9610&v=3&d=true', 'url_type': None}], 'tags': [{'display_name': 'Australia', 'id': 'e95878ac-50e4-4577-9bb6-fcb6a09d74a9', 'name': 'Australia', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'Murray-Darling Basins', 'id': 'bb2a4999-a8b2-4e3f-8667-1c6477ce9cf8', 'name': 'Murray-Darling Basins', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial data', 'id': '495c6bf0-9e18-48d5-9dfb-350c91aee049', 'name': 'spatial data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatio-temporal data', 'id': '2d18ca6f-c679-4294-892e-78c75e6c545e', 'name': 'spatio-temporal data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'stream gauges', 'id': '3bd881c0-5655-4ec3-ab46-0a82373681a7', 'name': 'stream gauges', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'ee911c5d-5f94-4ae8-a0dd-a50afffef819', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-23T23:53:28.988381', 'metadata_modified': '2017-02-06T02:26:19.060512', 'name': 'finnish-forest-data', 'notes': 'Description:\r\n--------\r\n\r\nThese data record pine saplings in a bounded region `A`, where `A` is a 10 m x 10 m square region of a Finnish forest. The data were supplied by Antti Penttinen and Dietrich Stoyan, are mapped in Stoyan and Stoyan (1994, p. 287) and analysed in Cressie and Collins (2001).\r\n\r\nFormat:\r\n------\r\n\r\n`x`: x location\r\n\r\n`y`: y location\r\n\r\n`height`: sapling height in m\r\n\r\n`diam`: sapling diameter in cm.\r\n\r\nUsage:\r\n----\r\n\r\n X <- read.table("forest.csv",sep=",",header=T)\r\n ggplot() + geom_point(data=X,aes(x,y,size=diam,colour=height))\r\n\r\n\r\nReferences:\r\n--------\r\n\r\nStoyan, D. (1987), "Statistical Analysis of Spatial Point Processes: A Soft-Core Model and Cross-Correlations of Marks," Biometrical Journal, 29, 971-980. \r\n\r\nCressie, N., & Collins, L. B. (2001). Analysis of spatial point patterns using bundles of product density LISA functions. Journal of agricultural, biological, and environmental statistics, 6(1), 118-135.', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Pine saplings in a 10m x 10m region of a Finnish forest', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-24T10:53:45.536686', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'f1c82392-3588-4a6e-92b5-76f1d4b968ab', 'last_modified': None, 'metadata_modified': '2014-12-24T10:53:45.536686', 'mimetype': None, 'mimetype_inner': None, 'name': 'Forest data', 'package_id': 'ee911c5d-5f94-4ae8-a0dd-a50afffef819', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/ee911c5d-5f94-4ae8-a0dd-a50afffef819/resource/f1c82392-3588-4a6e-92b5-76f1d4b968ab/download/forest.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'ecology', 'id': '6027bf7a-8465-4670-aa0a-ea3886383341', 'name': 'ecology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'forest', 'id': '14664b81-9301-485a-a0db-aead618dd2cb', 'name': 'forest', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'point process', 'id': '0f755bc9-a8e9-4cde-84de-608989f9276d', 'name': 'point process', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': 'Platt, Evans and Rathbun ', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'c7ce7c39-37f8-48bb-ac15-b4dfe000c6d2', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:28:19.423123', 'metadata_modified': '2017-02-06T02:25:35.512162', 'name': 'long-leaf-pine-forest-data', 'notes': 'Description:\r\n---------------\r\n\r\nThe longleaf data as used in Rathburn and Cressie (1994) is now also part of the "spatstat" package in R. The description below is taken from the package.\r\n\r\nThe data record the locations and diameters of 584 Longleaf pine (Pinus palustris) trees in a 200 x 200 metre region in southern Georgia (USA). They were collected and analysed by Platt, Evans and Rathbun (1988). This is a marked point pattern; the mark associated with a tree is its diameter at breast height (dbh), a convenient measure of its size. Several analyses have considered only the “adult” trees which are conventionally defined as those trees with dbh greater than or equal to 30 cm. The pattern is regarded as spatially inhomogeneous.\r\n\r\nFormat:\r\n----------\r\nThe csv file contains three columns:\r\n\r\n- `x`: x-coordinate in metres\r\n- `y`: y-coordinate in metres\r\n- `marks`: tree diameter at breast height.\r\n\r\nReferences:\r\n---------------\r\nRathbun, Stephen L., and Noel Cressie. "A space-time survival point process for a longleaf pine forest in southern Georgia." Journal of the American Statistical Association 89.428 (1994): 1164-1174.', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Long-leaf pine locations and diameters in a 200 m x 200 m region', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:29:00.619245', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '173d3dfc-5ee1-4a48-bb04-17ce6e711355', 'last_modified': None, 'metadata_modified': '2014-12-04T09:29:00.619245', 'mimetype': None, 'mimetype_inner': None, 'name': 'Long-leaf pine forest data', 'package_id': 'c7ce7c39-37f8-48bb-ac15-b4dfe000c6d2', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/c7ce7c39-37f8-48bb-ac15-b4dfe000c6d2/resource/173d3dfc-5ee1-4a48-bb04-17ce6e711355/download/longleaf.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'forest', 'id': '14664b81-9301-485a-a0db-aead618dd2cb', 'name': 'forest', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'point process data', 'id': '0b54d3ca-6c57-42f4-bc4f-d822812cba43', 'name': 'point process data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'space-time data', 'id': '850595ed-b972-49ed-bc9d-4de7252c6fc7', 'name': 'space-time data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'a4332c1d-2bdb-4539-8bbf-e2b2044a56cc', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-01-21T22:10:10.261987', 'metadata_modified': '2017-02-06T02:24:54.104381', 'name': 'archaeological', 'notes': 'Description:\r\n-----------\r\n\r\nTaken from Cressie and Kapat (2008):\r\n\r\nBetween 1983 and 1989, a joint team from the British School in Athens, Greece, and the Universities of Amsterdam and Nottingham carried out an intensive survey of a 70 sq km area of Laconia across the Evrotas (ancient Eurotas) river, east from the ancient site of Sparta, Greece. These data consist of raw phosphate concentration readings (in mg P/100 g of soil) taken 10 m apart, from the site LS 165 of the Laconia Survey; the observations are distributed over a regular 16×16 grid (Buck et al. 1988). We denote these raw data by D(x, y), where (x, y) represents a location of a datum on the grid; x, y = 1, . . . , 16. \r\n\r\nFormat:\r\n---------\r\n\r\nA csv file containing a 16 x 16 matrix. The first row is at y = 16 and the final row at y = 1. The first column is at x = 1 and the last column at x = 16. Missing values are listed as -999.\r\n\r\nUsage:\r\n---------\r\n\r\nTo plot use the following\r\n\r\n library(tidyr)\r\n library(ggplot2)\r\n X <- read.csv("~/Desktop/archaeology.csv",header = F)\r\n names(X) <- 1:16\r\n\r\n X <- gather(X,key = x,value=ph)\r\n X <- mutate(X,y = rep(16:1,16))\r\n X <- subset(X, !(ph < 0))\r\n\r\n ggplot() + geom_tile(data=X,aes(x,y,fill=pmin(ph,150))) + \r\n scale_fill_gradient(low="light yellow",high="red") + \r\n coord_fixed()\r\n\r\n\r\n\r\nReferences:\r\n------------------\r\n\r\nBuck, C. E., Cavanagh, W. G., & Litton, C. D. (1988). The spatial analysis of site phosphate data. Computer and Quantitative Methods in Archaeology, 1, 151.\r\n\r\nCressie, N., & Kapat, P. (2008). Some diagnostics for Markov random fields. Journal of computational and graphical statistics, 17(3), 726-749.\r\n\r\n', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Archaeological dataset of phosphate concentrations at Evrotas river', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-01-22T09:10:49.456587', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'c815b264-6fdf-4cb9-a615-7da9355f98c4', 'last_modified': None, 'metadata_modified': '2015-01-22T09:10:49.456587', 'mimetype': None, 'mimetype_inner': None, 'name': 'Archaeological dataset of phosphate concentrations', 'package_id': 'a4332c1d-2bdb-4539-8bbf-e2b2044a56cc', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/a4332c1d-2bdb-4539-8bbf-e2b2044a56cc/resource/c815b264-6fdf-4cb9-a615-7da9355f98c4/download/archaeology.csv', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '360fcbb2-be6e-4bc2-a165-b06027c46a2f', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:30:09.301434', 'metadata_modified': '2017-02-06T02:24:02.796833', 'name': 'melanoma-skin-cancer-incidence', 'notes': "Description:\r\n---------------\r\n\r\nThis data was taken from the R `lattice' package. The data is described in the package as follows:\r\n\r\nThese data from the Connecticut Tumor Registry present age-adjusted numbers of melanoma skin-cancer incidences per 100,000 people in Connecticut for the years from 1936 to 1972. \r\n\r\nFormat:\r\n------------\r\n\r\nA csv file has 37 observations on the following 2 variables.\r\n\r\n- `year`: years 1936 to 1972.\r\n\r\n- `incidence`: rate of melanoma cancer per 100,000 population.\r\n\r\nReferences:\r\n--------------\r\nRamsay, James O., and Silverman, Bernard W. (2006), Functional Data Analysis, 2nd ed., Springer, New York.", 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Melanoma skin cancer incidence in Connecticut between 1936-1972', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:30:36.462980', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'd2bef476-607a-41a1-a496-1ff0edf7b352', 'last_modified': None, 'metadata_modified': '2014-12-04T09:30:36.462980', 'mimetype': None, 'mimetype_inner': None, 'name': 'Melanoma skin cancer incidence', 'package_id': '360fcbb2-be6e-4bc2-a165-b06027c46a2f', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/360fcbb2-be6e-4bc2-a165-b06027c46a2f/resource/d2bef476-607a-41a1-a496-1ff0edf7b352/download/melanoma.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'cancer', 'id': '48c39e64-7acb-4623-a1b3-07b40d08df98', 'name': 'cancer', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'health', 'id': '7c1d6d8b-de6d-4111-b1e2-3df6b8a90ce8', 'name': 'health', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'skin cancer', 'id': '46389d6a-3dd3-42c4-ba18-574891bc1f47', 'name': 'skin cancer', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'isopen': True, 'license_id': 'cc-zero', 'license_title': 'Creative Commons CCZero', 'license_url': 'http://www.opendefinition.org/licenses/cc-zero', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:35:11.665172', 'metadata_modified': '2017-02-06T02:23:41.606227', 'name': 'sudden-infant-death-syndrome-data', 'notes': "Description:\r\n---------------\r\n\r\nThe following description is taken from the R vignette by Roger Bivand (linked to as a resource in this dataset)\r\n\r\nThis dataset was presented first in Symons et al. (1983), analysed with reference to the spatial nature of the data in Cressie and Read (1985), expanded in Cressie and Chan (1989), and used in detail in Cressie (1991). It is for the 100 counties of North Carolina, and includes counts of numbers of live births (also non-white live births) and numbers of sudden infant deaths, for the July 1, 1974 to June 30, 1978 and July 1, 1979 to June 30, 1984 periods. \r\n\r\nSpatio-temporal addition:\r\n---------------\r\n\r\nIn this dataset we include the 'spatial-only' 1974--1978 period but also add a spatio-temporal version of the second period (1979 -- 1984). These latter data were studied in detail in a recent work by Zhuang and Cressie (2012). \r\n\r\n\r\nReferences:\r\n--------------\r\n\r\nCressie, N., 1991. Statistics for spatial data. New York: Wiley, pp. 900\r\n\r\nCressie, N., Chan N. H., 1989. Spatial modelling of regional variables. Journal of\r\nthe American Statistical Association, 84 (406), 393–401.\r\n\r\nCressie, N., Read, T. R. C., 1985. Do sudden infant deaths come in clusters?. Statistics and Decisions, Supplement Issue 2, 333–349\r\n\r\nSymons, M. J., Grimson, R. C., Yuan, Y. C., 1983. Clustering of rare events. Bio-\r\nmetrics, 39 (1), 193–205.\r\n\r\nZhuang, L. and Cressie, N., 2012. Spatio-temporal modeling of Sudden Infant Death Syndrome data. Statistical Methodology, 9, 117–143.", 'num_resources': 7, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Sudden Infant Death Syndrome (SIDS) incidence in North Carolina between 1974-1984', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:35:50.741211', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '3ac86f79-ab01-4bb4-ae90-63476ba1a0db', 'last_modified': None, 'metadata_modified': '2014-12-04T09:35:50.741211', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1974 -- 1978', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/3ac86f79-ab01-4bb4-ae90-63476ba1a0db/download/countydata7478.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:36:24.712693', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '5de12724-4f45-492c-9c04-1c47ed2a27a3', 'last_modified': None, 'metadata_modified': '2014-12-04T09:36:24.712693', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1979 -- 1980', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/5de12724-4f45-492c-9c04-1c47ed2a27a3/download/countydata7980.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:36:37.217333', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'bff51f28-7374-48ee-8588-aa8f218d9a32', 'last_modified': None, 'metadata_modified': '2014-12-04T09:36:37.217333', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1980 -- 1981', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 2, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/bff51f28-7374-48ee-8588-aa8f218d9a32/download/countydata8081.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:36:53.585803', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '591b3a27-a2b7-41f2-9ce3-398d7e74754f', 'last_modified': None, 'metadata_modified': '2014-12-04T09:36:53.585803', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1981 -- 1982', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 3, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/591b3a27-a2b7-41f2-9ce3-398d7e74754f/download/countydata8182.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:37:07.805692', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'd8ce279d-aa3e-4371-b869-cfcb98780140', 'last_modified': None, 'metadata_modified': '2014-12-04T09:37:07.805692', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1982 -- 1983', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 4, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/d8ce279d-aa3e-4371-b869-cfcb98780140/download/countydata8283.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:37:20.427256', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '7def9549-4e2d-412b-89c8-cdc7798c68f2', 'last_modified': None, 'metadata_modified': '2014-12-04T09:37:20.427256', 'mimetype': None, 'mimetype_inner': None, 'name': 'SIDS data 1983 -- 1984', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 5, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/7def9549-4e2d-412b-89c8-cdc7798c68f2/download/countydata8384.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:37:56.198804', 'datastore_active': False, 'description': 'This excellent vignette by Roger Bivand presents some spatial analysis of SIDS datasets.', 'format': 'PDF', 'hash': '', 'id': 'c52cad0c-d270-4dc1-a915-f0257afc8857', 'last_modified': None, 'metadata_modified': '2014-12-04T09:37:56.198804', 'mimetype': None, 'mimetype_inner': None, 'name': 'Spatial Analysis of SIDS data (R vignette)', 'package_id': '32199479-93dd-4a17-9bb6-788b5733b79b', 'position': 6, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/32199479-93dd-4a17-9bb6-788b5733b79b/resource/c52cad0c-d270-4dc1-a915-f0257afc8857/download/sids.pdf', 'url_type': 'upload'}], 'tags': [{'display_name': 'health', 'id': '7c1d6d8b-de6d-4111-b1e2-3df6b8a90ce8', 'name': 'health', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'sudden infant death syndrome', 'id': 'db68f86c-d31c-4aae-b73c-65bd408f7d24', 'name': 'sudden infant death syndrome', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'fd82b833-08d3-4435-818e-5eb126431b87', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:38:42.880699', 'metadata_modified': '2017-02-06T02:23:17.637701', 'name': 'scallops-data', 'notes': 'Description:\r\n------------\r\n\r\nThe scallops data set lists the catch of scallops from a 1990 National Marine Fisheries Service trawl survey in the Atlantic Ocean. The survey area runs from the Delmarva Peninsula off the coast of Virginia and Maryland up to the George Banks.\r\n\r\nFormat:\r\n--------\r\n\r\nThe data contains the following fields:\r\n\r\n- `strata`: a factor indicating the National Marine Fisheries Service (NMFS) 4-digit strata designator in which the sample was taken.\r\n- `sample`: sample number per year ranging from 1 to approximately 450. \r\n- `lat`: latitude location of each sample in the Atlantic Ocean.\r\n- `long`: longitude location of each sample in the Atlantic Ocean.\r\n- `tcatch`: total number of scallops caught at the i-th sample location. This is `prerec` + `recruits`.\r\n- `prerec`: number of scallops whose shell length is smaller than 70 millimeters.\r\n- `recruits`: number of scallops whose shell length is 70 millimeters or larger.\r\n\r\nReferences:\r\n-------------\r\n\r\nEcker, Mark D. and Heltshe, James F. (1994) Geostatistical estimates of scallop abundance. In Case Studes in Biometry. Nicholas Lange, Louis Ryan, Lynne Billard, David Brillinger, Loveday Conquest, and Joel Greenhouse, eds. New York: Wiley, pp. 107--124.', 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Scallops caught in the Atlantic Ocean in 1990', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:39:11.284763', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '4862f5b4-50e5-4354-8c43-a598e51be68f', 'last_modified': None, 'metadata_modified': '2014-12-04T09:39:11.284763', 'mimetype': None, 'mimetype_inner': None, 'name': 'Scallops data set', 'package_id': 'fd82b833-08d3-4435-818e-5eb126431b87', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/fd82b833-08d3-4435-818e-5eb126431b87/resource/4862f5b4-50e5-4354-8c43-a598e51be68f/download/scallops.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'ecology', 'id': '6027bf7a-8465-4670-aa0a-ea3886383341', 'name': 'ecology', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'scallops', 'id': '60ea6034-9f22-419b-b764-2998cbeb69aa', 'name': 'scallops', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '228cffc2-4c0e-460f-a91c-7750f22a4230', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:40:04.814906', 'metadata_modified': '2017-02-06T02:22:11.649009', 'name': 'scottish-lip-cancer-data-set', 'notes': 'Description:\r\n--------------\r\n\r\n This dataset is provided in the package "gcmr" in R and published in Waller and Gotway (2004). It contains data on male lip cancer incidence in Scotland counties between 1975-1980.\r\n\r\nFormat:\r\n----------\r\nThe csv file contains 5 columns:\r\n\r\n- `observed`: observed cases in each county.\r\n- `expected`: excpected cases in each county.\r\n- `AFF`: proportion of the population employed in agriculture, fishing, or forestry.\r\n- `latitude`: county latitude.\r\n- `longitude`: county longitude.\r\n\r\nReferences:\r\n---------------\r\n\r\nClayton D. and Kaldor J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics 43, 671–681.\r\n\r\nWaller, L.A. and Gotway, C.A. (2004) Applied Spatial Statistics for Public Health Data. New York: John Wiley and Sons.\r\n', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Lip cancer incidence in Scotland counties between 1975-1980', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:40:19.958409', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'a9968e3a-868f-4170-a04b-b2db942184d8', 'last_modified': None, 'metadata_modified': '2014-12-04T09:40:19.958409', 'mimetype': None, 'mimetype_inner': None, 'name': 'Scottish lip cancer data set', 'package_id': '228cffc2-4c0e-460f-a91c-7750f22a4230', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/228cffc2-4c0e-460f-a91c-7750f22a4230/resource/a9968e3a-868f-4170-a04b-b2db942184d8/download/scotland.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'cancer', 'id': '48c39e64-7acb-4623-a1b3-07b40d08df98', 'name': 'cancer', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'lip cancer', 'id': 'f77016ce-3b78-404b-ad2b-8f475ee7fe1c', 'name': 'lip cancer', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial data', 'id': '495c6bf0-9e18-48d5-9dfb-350c91aee049', 'name': 'spatial data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'a35a69ec-d7eb-4cc8-b103-9dc9ad9e5584', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-09T00:29:03.893798', 'metadata_modified': '2017-02-06T02:21:50.133655', 'name': 'coalash', 'notes': 'This data is available in Cressie (1993) and is also present in the R `gstat` and `fields` packages.\r\n\r\nDescription:\r\n---\r\n\r\nData obtained from Gomez and Hazen (1970, Tables 19 and 20) on coal ash for the Robena Mine Property in Greene County Pennsylvania.\r\n\r\nFormat:\r\n---\r\n\r\nThis data frame contains the following columns:\r\n\r\n- `x`: a numeric vector; x-coordinate; reference unknown\r\n- `y`: a numeric vector; x-coordinate; reference unknown\r\n- `coalash`: the target variable.\r\n\r\nReferences:\r\n---\r\n\r\nN.A.C. Cressie, 1993, Statistics for Spatial Data, Wiley.\r\n\r\nGomez, M. and Hazen, K. (1970). Evaluating sulfur and ash distribution in coal seems by statistical response surface regression analysis. U.S. Bureau of Mines Report RI 7377.\r\n\r\nsee also fields manual: http://www.image.ucar.edu/GSP/Software/Fields/fields.manual.coalashEX.Krig.shtml', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Coal ash data from a mine in Pennsylvania', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-09T11:29:37.453031', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '2cdcb7e4-c760-4ccd-b755-a2dff504ea72', 'last_modified': None, 'metadata_modified': '2014-12-09T11:29:37.453031', 'mimetype': None, 'mimetype_inner': None, 'name': 'Coal ash data', 'package_id': 'a35a69ec-d7eb-4cc8-b103-9dc9ad9e5584', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/a35a69ec-d7eb-4cc8-b103-9dc9ad9e5584/resource/2cdcb7e4-c760-4ccd-b755-a2dff504ea72/download/coalash.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'coal', 'id': '9c5428e2-3a87-405f-99d6-73174c81b27e', 'name': 'coal', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'pollution', 'id': '6afc65e4-78f6-4e96-bb27-f90063a08a9c', 'name': 'pollution', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial data', 'id': '495c6bf0-9e18-48d5-9dfb-350c91aee049', 'name': 'spatial data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '5d8398c1-d090-44f3-acda-cffacb38d80d', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:31:30.329834', 'metadata_modified': '2017-02-06T02:21:17.610429', 'name': 'mercer-and-hall-wheat-yield-data', 'notes': 'Description:\r\n----------------\r\n\r\nThese data were taken from the R package `spdep\'. The Mercer and Hall yield data consist of wheat yields on a 20 by 25 lattice of plots which total to around 1 acre in area. Each of the 20 rows runs in the E-W direction and each of the 25 columns in the N-S direction. Authors have analysed the wheat-yield data using both lattice models (through specification of the inverse covariance matrix) and geostatistical models (through specification of the covariance matrix). More details on these data can be found in Cressie (1993) pp. 248--259, 454--456.\r\n\r\nFormat:\r\n--------\r\n\r\nThis is a three column csv file, the data in which was made available by Hongfei Li. There are 500 observations on the following 6 variables.\r\n\r\n- `lat`: local coordinates northings ordered north to south\r\n\r\n- `lon`: local coordinates eastings\r\n\r\n- `yield`: Mercer and Hall wheat yield data.\r\n\r\nNote:\r\n--------\r\n\r\n- These are /local/ lat-lon coordinates.\r\n\r\n- The value of 4.03 was changed to 4.33 (wheat[71,]) 13 January 2014; thanks to Sandy Burden; cross-checked with http://www.itc.nl/personal/rossiter/teach/R/mhw.csv, which agrees.\r\n\r\nThe following image can be generated as follows:\r\n \r\n library(ggplot2)\r\n wheat <- read.table("wheat.csv",sep=",",header=T)\r\n g <- ggplot() + geom_tile(data=wheat,aes(lon,lat,fill=yield)) + coord_fixed() + scale_fill_gradient(low="light yellow",high="dark blue")\r\n ggsave("wheat.jpg")\r\n \r\n\r\n\r\nReferences:\r\n------------------\r\n\r\nCressie, N. A. C. (1993) Statistics for Spatial Data. Wiley, New York, p. 455.\r\nMercer, W. B. and Hall, A. D. (1911) The experimental error of field trials. Journal of Agricultural Science 4, 107-132.', 'num_resources': 1, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Wheat yields at Rothamsted in 1910 (Mercer and Hall Wheat Yield data)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:31:45.026398', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '9f0d148f-e7c2-4a04-a1e2-62c021966abb', 'last_modified': None, 'metadata_modified': '2014-12-04T09:31:45.026398', 'mimetype': None, 'mimetype_inner': None, 'name': 'Mercer and Hall wheat yield data', 'package_id': '5d8398c1-d090-44f3-acda-cffacb38d80d', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/5d8398c1-d090-44f3-acda-cffacb38d80d/resource/9f0d148f-e7c2-4a04-a1e2-62c021966abb/download/wheat.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'agriculture', 'id': 'e0624bc5-133a-44dd-ad2a-933fdf42c744', 'name': 'agriculture', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'wheat', 'id': 'f7695610-422a-4766-a525-882931b86a07', 'name': 'wheat', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'ab9fc512-9dc6-40b3-90a7-7f00a9a2fa60', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-20T06:38:31.134919', 'metadata_modified': '2017-02-06T02:20:34.023932', 'name': 'heather-data', 'notes': 'These data were taken from the website of [Peter Diggle](http://www.lancaster.ac.uk/staff/diggle/moredata/). He includes the following description with the data.\r\n\r\nDescription:\r\n-----------\r\n\r\n The file "heather" contains a binary representation of the presence/absence (1/0) of heather in a 10metre by 20metre rectangle, digitised to a 256 by 512 array. The file is arranged with 32 entries per line, corresponding to a row-wise scan of the ground-truth 256 by 512 array.\r\n \r\nThe data were collected in central Sweden by Goran Agren, Toby Fagerstrom and Peter Diggle, in September 1978. Their representation as a 256 by 512 binary array was constructed some years later by Adrian Baddelely.\r\n\r\nUsage:\r\n---------------\r\n\r\nThese data are also available in the package `spatstat`. To reproduce the data as shown in spatstat you can use the following commands in `R`:\r\n\r\n library(ggplot2)\r\n Z <- matrix(scan("heather.txt"),nrow=256,ncol=512,byrow=T)\r\n x <- seq(0,10,length = 256)\r\n y <- seq(0,20,length = 512)\r\n xy <- as.data.frame(expand.grid(x,y))\r\n names(xy) <- c("x","y")\r\n xy$z <- c(Z)\r\n ggplot() + geom_tile(data=xy,aes(-x,y,fill=z)) + coord_fixed()\r\n\r\n\r\n\r\nReferences:\r\n---------\r\nDiggle, P. J. "Binary mosaics and the spatial pattern of heather." Biometrics (1981): 531-539.\r\n\r\n', 'num_resources': 1, 'num_tags': 1, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Aerial view of heather in central Sweden', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-20T17:39:42.818446', 'datastore_active': False, 'description': '', 'format': 'TXT', 'hash': '', 'id': '34f8f83b-2224-4acf-932b-c770cb52641e', 'last_modified': None, 'metadata_modified': '2014-12-20T17:39:42.818446', 'mimetype': None, 'mimetype_inner': None, 'name': 'Heather data', 'package_id': 'ab9fc512-9dc6-40b3-90a7-7f00a9a2fa60', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/ab9fc512-9dc6-40b3-90a7-7f00a9a2fa60/resource/34f8f83b-2224-4acf-932b-c770cb52641e/download/heather.txt', 'url_type': 'upload'}], 'tags': [{'display_name': 'heather', 'id': '64624ece-c9b8-4ecf-b3dc-d8554e75c6ce', 'name': 'heather', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '01b79b68-401e-4694-b300-4475842339ad', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-01-05T23:27:13.687678', 'metadata_modified': '2017-02-06T02:19:00.084273', 'name': 'brousse-tigree-dataset', 'notes': 'Description:\r\n----------\r\n\r\nThis is an aerial view of Brousse Tigree in an arid landscape in Niger. This picture was taken from the book of Dale (1999) which itself was extracted from Thiery et al. (1995). The area shown is about 1km x 1.3km.\r\n\r\nFormat:\r\n---------\r\n\r\nThe file is a csv and contains 786 rows and 597 columns. \r\n\r\nUsage:\r\n-----\r\n\r\nThe data can be read into R using\r\n\r\n X <- as.matrix(read.table("brousse.csv",header=F,sep=","))\r\n\r\n\r\n\r\nReferences:\r\n-----------\r\n\r\nDale, M. R. (1999). Spatial pattern analysis in plant ecology. Cambridge, United Kingdom.\r\n\r\nThiery, J. M., d\'Herbes, J. M., & Valentin, C. (1995). A model simulating the genesis of banded vegetation patterns in Niger. Journal of Ecology, 497-507.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Aerial view of Brousse Tigree in Niger', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-01-06T10:27:53.597007', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'a1785c69-8110-439d-84e4-d182660e6d41', 'last_modified': None, 'metadata_modified': '2015-01-06T10:27:53.597007', 'mimetype': None, 'mimetype_inner': None, 'name': 'Brousse Tigree dataset', 'package_id': '01b79b68-401e-4694-b300-4475842339ad', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/01b79b68-401e-4694-b300-4475842339ad/resource/a1785c69-8110-439d-84e4-d182660e6d41/download/brousse.csv', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'a4c0401f-cf7a-4a66-9094-2369c8ffad07', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:32:43.371042', 'metadata_modified': '2017-02-06T02:18:11.863228', 'name': 'monthly-weather-station-temperature-data-across-the-northeastern-us', 'notes': "Description:\r\n--------------\r\n\r\nThis data was taken from the R package `spBayes'. The data description in the package is as follows:\r\n\r\nMonthly temperature data (Celsius) recorded across the Northeastern US starting in January 2000. Station UTM coordinates and elevation are also included.\r\n\r\nFormat:\r\n----------\r\n\r\nThe csv file contains the following fields\r\n\r\n- `elev`: station elevation in metres\r\n- `UTMX`: UTM x-coordinate of station\r\n- `UTMY`: UTM y-coordinate of station\r\n- `y.###`: (where ### is a number) denotes a monthly reading.", 'num_resources': 2, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Monthly weather station temperature data across the Northeastern US', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:33:09.658252', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '8a618ef7-6b71-41e3-b775-f831bae076ba', 'last_modified': None, 'metadata_modified': '2014-12-04T09:33:09.658252', 'mimetype': None, 'mimetype_inner': None, 'name': 'Monthly weather station temperature data across the Northeastern US', 'package_id': 'a4c0401f-cf7a-4a66-9094-2369c8ffad07', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/a4c0401f-cf7a-4a66-9094-2369c8ffad07/resource/8a618ef7-6b71-41e3-b775-f831bae076ba/download/netemp.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:34:02.934069', 'datastore_active': False, 'description': 'Vignette by Andrew O. Finley and Sudipto Banerjee using the data', 'format': 'PDF', 'hash': '', 'id': 'f70e8c68-fa71-499e-9be3-86cbd8acf451', 'last_modified': None, 'metadata_modified': '2014-12-04T09:34:02.934069', 'mimetype': None, 'mimetype_inner': None, 'name': 'Bayesian Dynamic Modeling for Space-time Data in R', 'package_id': 'a4c0401f-cf7a-4a66-9094-2369c8ffad07', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/a4c0401f-cf7a-4a66-9094-2369c8ffad07/resource/f70e8c68-fa71-499e-9be3-86cbd8acf451/download/initialexplorationspdynlm.pdf', 'url_type': 'upload'}], 'tags': [{'display_name': 'temperature', 'id': '29fb5f40-0feb-41ac-a31c-ebb287355fb5', 'name': 'temperature', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'weather', 'id': '7a948dae-d5dd-4de4-8de6-1b5e2009708b', 'name': 'weather', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '772ef0d6-9072-47cd-86d7-e766b76c5a32', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:25:35.673689', 'metadata_modified': '2017-02-06T02:16:58.580628', 'name': 'daily-8-hour-ozone-averages-for-sites-in-the-midwest', 'notes': "Description:\r\n--------------\r\n\r\nThis dataset was taken from the package 'fields' and put into table format. The description in the package is as follows:\r\n\r\nThe response is 8-hour average (surface) ozone ( from 9AM-4PM) measured in parts per billion (PPB) for 153 sites in the midwestern US over the period June 3,1987 through August 31, 1987, 89 days. This season of high ozone corresponds with a large modeling experiment using the EPA Regional Oxidant Model.\r\n\r\nFormat:\r\n--------------\r\n\r\nThe csv file has 153 rows (one per site) and 92 fields. \r\n\r\n- `lon`: longitude coordinate of site\r\n\r\n- `lat`: latitude coordinate of site\r\n\r\n- `station id`: unique identifier of station\r\n\r\n- the other 89 columns are the ozone readings on the different days (column names are in year/month/day format). \r\n\r\nReferences:\r\n--------------\r\n\r\nNychka, D., Cox, L., Piegorsch, W. (1998) Case Studies in Environmental Statistics Lecture Notes in Statistics, Springer Verlag, New York", 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Daily 8-hour ozone averages for sites in the Midwest', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:26:22.817537', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'd6735721-8862-4dfb-adea-d60027f876a0', 'last_modified': None, 'metadata_modified': '2014-12-04T09:26:22.817537', 'mimetype': None, 'mimetype_inner': None, 'name': 'Daily 8-hour ozone averages for sites in the Midwest', 'package_id': '772ef0d6-9072-47cd-86d7-e766b76c5a32', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/772ef0d6-9072-47cd-86d7-e766b76c5a32/resource/d6735721-8862-4dfb-adea-d60027f876a0/download/ozone2.csv', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '9e2e7f88-e597-41a4-927c-7d7e74e7994f', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:42:46.244896', 'metadata_modified': '2017-02-06T02:16:39.638311', 'name': 'simulated-co2-data', 'notes': "Description:\r\n---------------\r\nThis CO2 data is available in the R package `fields' except that the data here has been converted into a more user-friendly long-table format. In the package contains the following data description:\r\n\r\nThis is an example of moderately large spatial data set and consists of simulated CO2 concentrations that are irregularly sampled from a lon/lat grid. Also included is the complete CO2 field used to generate the synthetic observations. \r\n\r\nThis data was generously provided by Dorit Hammerling and Randy Kawa as a test example for the spatial analysis of remotely sensed (i.e. satellite) and irregular observations. The synthetic data is based on a true CO2 field simulated from a geophysical, numerical model.\r\n\r\nFormat:\r\n---------\r\n\r\n**co2sim.csv**\r\n\r\nThe CSV file has three columns:\r\n\r\n- `lon`: longitude coordinate.\r\n- `lat`: latitude coordinate.\r\n- `z`: CO2 concentration in parts per million. \r\n\r\n**co2true.csv**\r\n\r\nThe CSV file has three columns:\r\n\r\n- `lon`: longitude coordinate.\r\n- `lat`: latitude coordinate.\r\n- `z`: CO2 concentration in parts per million. \r\n- `mask`: logical vector that indicates with grid locations were selected for the synthetic CO2 dataset.\r\n", 'num_resources': 2, 'num_tags': 2, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Simulated CO2 data', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:43:18.512713', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': '13bc89e6-9340-490d-9ddf-03fb4d52bced', 'last_modified': None, 'metadata_modified': '2014-12-04T09:43:18.512713', 'mimetype': None, 'mimetype_inner': None, 'name': 'Simulated irregularly sampled CO2 data', 'package_id': '9e2e7f88-e597-41a4-927c-7d7e74e7994f', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/9e2e7f88-e597-41a4-927c-7d7e74e7994f/resource/13bc89e6-9340-490d-9ddf-03fb4d52bced/download/co2sim.csv', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:43:29.045236', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'ab049f50-971a-402e-995f-3d3a34e640d2', 'last_modified': None, 'metadata_modified': '2014-12-04T09:43:29.045236', 'mimetype': None, 'mimetype_inner': None, 'name': 'Complete simulated CO2 data', 'package_id': '9e2e7f88-e597-41a4-927c-7d7e74e7994f', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/9e2e7f88-e597-41a4-927c-7d7e74e7994f/resource/ab049f50-971a-402e-995f-3d3a34e640d2/download/co2true.csv', 'url_type': 'upload'}], 'tags': [{'display_name': 'CO2', 'id': 'a9d41fd1-f5a9-4b03-ab45-c97ae5953840', 'name': 'CO2', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'carbon dioxide', 'id': '869a1d7c-d27f-42fc-9aae-cb07ab987230', 'name': 'carbon dioxide', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '6ddf61bb-2f9a-424a-8775-e23ebaa55afb', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-03T22:22:07.371002', 'metadata_modified': '2017-02-06T02:15:58.837914', 'name': 'airs-co2-data-may-2003', 'notes': 'Description:\r\n---------------\r\n\r\nData from the Atmospheric Infrared Sounder (AIRS) from May 1 2003 to June 1 2003.\r\n\r\nFormat:\r\n---------\r\n\r\nThe file is in csv format with 8 columns, \r\n\r\n- `year`: year\r\n- `month`: month\r\n- `day`: day\r\n- `lat`: latitude\r\n- `lon`: longitude\r\n- `solzen`: solar zenith angle\r\n- `co2avgret`: co2 concentration\r\n- `co2std`: co2 uncertainty (sd).\r\n\r\nReferences:\r\n---------------\r\n\r\nKatzfuss, M. and Cressie, N. (2011), Spatio-temporal smoothing and EM estimation for massive remote-sensing data sets. Journal of Time Series Analysis, 32: 430–446.', 'num_resources': 1, 'num_tags': 0, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'AIRS CO2 data, May 2003', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2014-12-04T09:23:06.121688', 'datastore_active': False, 'description': '', 'format': 'CSV', 'hash': '', 'id': 'e1206e1c-9dca-42b6-8455-3cdd98c6a943', 'last_modified': None, 'metadata_modified': '2014-12-04T09:23:06.121688', 'mimetype': None, 'mimetype_inner': None, 'name': 'AIRS data', 'package_id': '6ddf61bb-2f9a-424a-8775-e23ebaa55afb', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/6ddf61bb-2f9a-424a-8775-e23ebaa55afb/resource/e1206e1c-9dca-42b6-8455-3cdd98c6a943/download/airs2003may116.csv', 'url_type': 'upload'}], 'tags': [], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '1b68ae89-455d-43d7-83ba-b85ead48439f', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-05-09T09:13:36.900473', 'metadata_modified': '2017-02-06T02:15:33.231222', 'name': 'isea3h-all-res', 'notes': 'Description:\r\n-------\r\n\r\nThese data were taken from [here](http://webpages.sou.edu/~sahrk/dgg/isea.old/gen/isea3h.html) and contain ISEA discrete global grids (DGGs) generated using the [DGGRID software](http://webpages.sou.edu/~sahrk/dgg/dggrid/dggrid.html). The available grids below correspond to the Aperture 3 Hexagons. Grids for other ISEA DGG topologies are available from the original website.\r\n\r\nFormat:\r\n--------\r\n\r\nThe grids are in ARC/INFO generate format, which is a simple text file format. All vertices are given in longitude and latitude in decimal degrees. Each file contains the cell boundaries for the entire globe at the specified resolution. Since cell boundaries are only true regular polygons in the ISEA projection space 3 additional points were added to each edge to better preserve the true boundary shape after projection into longitude/latitude coordinates. \r\n\r\nUsage:\r\n-----\r\n\r\nTo read the data into R use the following code\r\n\r\n library(dplyr)\r\n library(ggplot2)\r\n library(foreach)\r\n library(zoo)\r\n\r\n isea3h <- NULL\r\n isea3h <- foreach(j = 0:8,.combine = "rbind") %do% {\r\n print(paste0("Processing resolution ",j))\r\n\r\n X <- read.table(paste0("isea3h",j,".gen"),\r\n sep=" ",\r\n fill=T,header=F,\r\n col.names = c("id","lon","lat")) \r\n X <- filter(X,!(id == "END"))\r\n X <- mutate(X,res = j,\r\n id = as.numeric(as.character(id)),\r\n centroid = as.numeric(!is.na(id)))\r\n X <- transform(X,id = na.locf(id))\r\n X\r\n }\r\n save(isea3h,file="./isea3h.rda")\r\n ggplot(subset(isea3h,res==5)) +\r\n geom_point(aes(lon,lat,colour=centroid)) + \r\n coord_map("ortho")\r\n\r\n\r\n\r\nReferences:\r\n----------\r\n\r\nSahr, K. (2008) Location coding on icosahedral aperture 3 hexagon discrete global grids. Computers, Environment and Urban Systems, 32(3):174-187.', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'ISEA Aperture 3 Hexagon (ISEA3H) DGG', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-05-09T19:27:17.870280', 'datastore_active': False, 'description': '', 'format': 'TAR.GZ', 'hash': '', 'id': 'e57d5c13-c666-4550-8761-cee3098e1467', 'last_modified': None, 'metadata_modified': '2015-05-09T19:27:17.870280', 'mimetype': None, 'mimetype_inner': None, 'name': 'ISEA Aperture 3 Hexagon Resolutions 0--9', 'package_id': '1b68ae89-455d-43d7-83ba-b85ead48439f', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/1b68ae89-455d-43d7-83ba-b85ead48439f/resource/e57d5c13-c666-4550-8761-cee3098e1467/download/isea3h.tar.gz', 'url_type': 'upload'}], 'tags': [{'display_name': 'DGGRID', 'id': 'f6e9960b-29c5-47d1-9264-6107785f86e7', 'name': 'DGGRID', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'hexagons', 'id': 'd43e800c-5ddb-450f-9eab-f60069eead4c', 'name': 'hexagons', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatial', 'id': '34c44f4a-146c-426d-80f1-9b2f284d2767', 'name': 'spatial', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '2660ac80-628f-4e28-97d3-d5dc8cdd4509', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-10-27T00:58:51.403161', 'metadata_modified': '2017-02-06T02:12:05.743343', 'name': 'example-dataset-for-atmospheric-trace-gas-inversion', 'notes': 'These data are required to reproduce the results in the paper titled Spatio-temporal bivariate statistical models for atmospheric trace-gas inversion by Zammit-Mangion et al., which has been accepted for publication in the journal **Chemometrics and Intelligent Laboratory Systems** in early 2016. The ZIP file contains many files that need to be placed in a "../data/" folder as described on the project software homepage [here](https://github.com/andrewzm/atminv). \r\n\r\nContents:\r\n-----------\r\n\r\nThe ZIP file contains many files\r\n\r\n* CH4_emissions_scaled_natural: This contains the emissions inventory used\r\n* UK_gridcells.txt: Indices on emissions map that correspond to sea/land UK territory\r\n* Ireland_gridcells.txt: Indices on emissions map that correspond to sea/land Irish territory\r\n* MHD_model_date.txt: NAME model output (source-receptor relationship) for a given month/year at Mace Head (MHD)\r\n* RGL_model_date.txt: NAME model output (source-receptor relationship) for a given month/year at Ridge Hill (RGL)\r\n* TAC_model_date.txt: NAME model output (source-receptor relationship) for a given month/year at Tacolneston (TCL)\r\n* TTA_model_date.txt: NAME model output (source-receptor relationship) for a given month/year at Angus (TTA)\r\n* MHD_obs_date.txt: Methane mole-fraction observations for a given month/year at Mace Head (MHD)\r\n* RGL_obs_date.txt: Methane mole-fraction observations for a given month/year at Ridge Hill (RGL)\r\n* TAC_obs_date.txt: Methane mole-fraction observations for a given month/year at Tacolneston (TAC)\r\n* TTA_obs_date.txt: Methane mole-fraction observations for a given month/year at Angus (TTA)\r\n* xxx_obs_date_filtered.txt: As above but with suspect mole fractions filtered out as described in the paper\r\n\r\nThe locations of the stations are given in the following figure\r\n\r\n\r\n\r\nAn overview of the methodology is given [here](http://niasra.uow.edu.au/cei/research/UOW202715) and the software page is [here](https://github.com/andrewzm/atminv).\r\n\r\nAcknowledgments and disclaimer:\r\n---------------------------------------------\r\n\r\nThese measurements were funded by the UK\'s Department of Energy and Climate Change and partly by NASA funding for the Advanced Global Atmospheric Gases Experiment. This data was accessed on 25 Jul 2014 and is subject to change. Any use of this data for other studies should first be downloaded directly from the EBAS repository (http://ebas.nilu.no) to ensure that the most up-to-date data is used. Data inquiries or permission for use of this data should be directed to Prof Simon O’Doherty, University of Bristol (S.ODoherty@bristol.ac.uk). Model output was generated by the UK Met Office NAME model 3 version 6.3 (Jones, et al., 2007, http://www.metoffice.gov.uk/research/modelling-systems/dispersion-model). UK inventory estimates of methane emissions were provided by the UK\'s National Atmospheric Emissions Inventory for 2012, which can be downloaded at http://naei.defra.gov.uk. \r\n', 'num_resources': 1, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Atmospheric trace-gas inversion example dataset (Methane in the UK and Ireland 2014)', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-10-27T12:03:04.566345', 'datastore_active': False, 'description': '', 'format': 'ZIP', 'hash': '', 'id': 'a9b40a10-25ea-47d8-874e-7246c82a28b0', 'last_modified': None, 'metadata_modified': '2015-10-27T12:03:04.566345', 'mimetype': None, 'mimetype_inner': None, 'name': 'Trace-gas inversion example dataset', 'package_id': '2660ac80-628f-4e28-97d3-d5dc8cdd4509', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/2660ac80-628f-4e28-97d3-d5dc8cdd4509/resource/a9b40a10-25ea-47d8-874e-7246c82a28b0/download/tracegasinversionexampledataset.zip', 'url_type': 'upload'}], 'tags': [{'display_name': 'NAME', 'id': '79d628c9-abe2-4c39-9a85-63205df1a68a', 'name': 'NAME', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'atmospheric trace gas inversion', 'id': '1a2d70b8-a6c8-4ec9-a412-ed5f89e994b1', 'name': 'atmospheric trace gas inversion', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'methane', 'id': 'd4b20d39-0c92-4bbb-9324-0f4c59600084', 'name': 'methane', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '04c51cd9-5e7b-40fb-9023-b7109b88665c', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-02-06T02:17:09.999194', 'metadata_modified': '2017-02-06T02:11:27.520087', 'name': 'wind-speed-data', 'notes': 'Description:\r\n-------\r\n\r\nEast-west component of the wind speed over a region in the tropical western Pacific ocean. The data was collected on a regular grid of 17 x 17 sites with grid spacing of about 210 km. Observations were taken every six hours from November 1992 through February 1993, that is, there are 289 spatial locations and 480 time\r\npoints. We thank Chris Wikle for his help in obtaining these data.\r\n\r\nFormat:\r\n------\r\n\r\nThis dataset contains two files. The first, `NCEP_U.dat,` contains u-wind (east-west) component (in m/s). There are 480 rows and 289 columns corresponding to 480 time points and 289 spatial locations.\r\n\r\nThe second, `NCEPlatlon.dat,` contains the lat and long coordinates (in degrees) for the 289 locations.\r\n\r\nReferences:\r\n----\r\n\r\nCressie, N., & Huang, H. C. (1999). Classes of nonseparable, spatio-temporal stationary covariance functions. Journal of the American Statistical Association, 94(448), 1330-1339.', 'num_resources': 2, 'num_tags': 3, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Wind-speed in the tropical western Pacific ocean between 1992-1993', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-02-06T13:17:27.923273', 'datastore_active': False, 'description': '', 'format': 'DAT', 'hash': '', 'id': '570e6652-faeb-4067-aa3a-9ba958c6b555', 'last_modified': None, 'metadata_modified': '2015-02-06T13:17:27.923273', 'mimetype': None, 'mimetype_inner': None, 'name': 'NCEP_U.dat', 'package_id': '04c51cd9-5e7b-40fb-9023-b7109b88665c', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/04c51cd9-5e7b-40fb-9023-b7109b88665c/resource/570e6652-faeb-4067-aa3a-9ba958c6b555/download/ncepu.dat', 'url_type': 'upload'}, {'cache_last_updated': None, 'cache_url': None, 'created': '2015-02-06T13:17:38.030445', 'datastore_active': False, 'description': '', 'format': 'DAT', 'hash': '', 'id': 'c1f30515-c8aa-4226-a8ea-7031f4a3306e', 'last_modified': None, 'metadata_modified': '2015-02-06T13:17:38.030445', 'mimetype': None, 'mimetype_inner': None, 'name': 'NCEPlatlon.dat', 'package_id': '04c51cd9-5e7b-40fb-9023-b7109b88665c', 'position': 1, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/04c51cd9-5e7b-40fb-9023-b7109b88665c/resource/c1f30515-c8aa-4226-a8ea-7031f4a3306e/download/nceplatlon.dat', 'url_type': 'upload'}], 'tags': [{'display_name': 'environmental data', 'id': '55a440f8-d242-4fb6-84b3-4a7c78b56ccd', 'name': 'environmental data', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'spatio-temporal', 'id': 'f06bfac9-bff8-4613-8da7-921880f75326', 'name': 'spatio-temporal', 'state': 'active', 'vocabulary_id': None}, {'display_name': 'wind speed', 'id': 'cf82f0c9-597e-4c60-a37f-aa1989eb8fd5', 'name': 'wind speed', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': 'f241884c-b19a-4264-9a6e-501af8dd68da', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit-Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2015-11-09T22:10:28.479378', 'metadata_modified': '2017-02-06T02:11:00.747373', 'name': 'aod', 'notes': 'Aerosol Optical Depth data used in Kang et al. (2010) and Cressie et al. (2010). The zip file contains multiple files in hdf format. A MATLAB helper file is also enclosed in the zip file to allow for ease of extraction.\r\n\r\nReferences:\r\n----------------\r\n\r\nKang, E.L., Cressie, N., and Shi, T. (2010). Using temporal variability to improve spatial mapping with application to satellite data. Canadian Journal of Statistics, 38, 271-289.\r\n\r\nCressie, N., Shi, T., and Kang, E.L. (2010). Fixed rank filtering for spatio-temporal data. Journal of Computational and Graphical Statistics, 19, 724-745. ', 'num_resources': 1, 'num_tags': 1, 'organization': {'id': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'name': 'cei', 'title': 'Centre for Environmental Informatics (CEI)', 'type': 'organization', 'description': '', 'image_url': 'http://niasra.uow.edu.au/content/groups/webasset/@web/@inf/@math/documents/mm/uow170808.png', 'created': '2014-11-25T12:33:11.014268', 'is_organization': True, 'approval_status': 'approved', 'state': 'active'}, 'owner_org': '4207b363-dfff-475d-a24c-fd97ca7f9e9a', 'private': False, 'state': 'active', 'title': 'Aerosol optical depth dataset', 'type': 'dataset', 'url': '', 'version': '', 'resources': [{'cache_last_updated': None, 'cache_url': None, 'created': '2015-11-10T09:10:50.910859', 'datastore_active': False, 'description': '', 'format': 'ZIP', 'hash': '', 'id': '671af826-98d1-496f-b795-ed600a16b99f', 'last_modified': None, 'metadata_modified': '2015-11-10T09:10:50.910859', 'mimetype': None, 'mimetype_inner': None, 'name': 'Aerosol Optical Depth HDF files and MATLAB helper file', 'package_id': 'f241884c-b19a-4264-9a6e-501af8dd68da', 'position': 0, 'resource_type': None, 'size': None, 'state': 'active', 'url': 'https://hpc.niasra.uow.edu.au/ckan/dataset/f241884c-b19a-4264-9a6e-501af8dd68da/resource/671af826-98d1-496f-b795-ed600a16b99f/download/aod.zip', 'url_type': 'upload'}], 'tags': [{'display_name': 'environmental data', 'id': '55a440f8-d242-4fb6-84b3-4a7c78b56ccd', 'name': 'environmental data', 'state': 'active', 'vocabulary_id': None}], 'extras': [], 'groups': [], 'relationships_as_subject': [], 'relationships_as_object': []}, {'author': '', 'author_email': '', 'creator_user_id': '0ed6839a-e7cd-4504-9192-fa73b3cc8756', 'id': '50b19b04-5681-458c-b421-76466e867b79', 'isopen': True, 'license_id': 'cc-by-sa', 'license_title': 'Creative Commons Attribution Share-Alike', 'license_url': 'http://www.opendefinition.org/licenses/cc-by-sa', 'maintainer': 'Andrew Zammit Mangion', 'maintainer_email': 'azm [at] uow.edu.au', 'metadata_created': '2014-12-24T00:05:24.200510', 'metadata_modified': '2017-02-06T01:58:21.359471', 'name': 'doctor-prescription-amounts-per-consultation', 'notes': 'Description:\r\n----\r\n\r\nThese data, analysed in Cressie, Perrin, and Thomas-Agnan (2005) and Cressie and Wikle (2011) Section 4.2, represent the average doctor-prescription amounts per consultation in cantons of the Midi-Pyrenees Department in southwest France. There are 268 cantons in the Midi-Pyrenees where average doctor-prescription amounts (per consultation) were reported for the period January 1, 1999-December 31, 1999. There are 32 "missing cantons" in the Midi-Pyrenees (MP) with no doctor-prescription data. Not all of the "missing cantons" in the files correspond to actual cantons; see below.\r\n\r\nThere are two datasets created from the original ones sent by Christine Thomas-Agnan: "Canton_neighbor.csv" and "Canton_vertex.csv". "Canton_neighbor.csv" is the dataset with cantons and their neighbours in the Midi-Pyrenees Region of France; note that only cantons with prescription data are included. "Canton_vertex.csv" is the dataset with cantons and vertices of the polygons; note that all cantons from the Midi-Pyrenees region are included, whether or not there were prescription data associated with them. The first 268 cantons in the dataset are those with prescription data. The same canton in both "Canton_neighbor.csv" and "Canton_vertex.csv" has the same value of "No.". The explanation of variables associated with each dataset is given as follows:\r\n\r\nFormat:\r\n----\r\n\r\n**Canton_neighbor.csv**\r\n\r\n`Variable` Variable Explanation\r\n\r\n`No.`: ID number from 1 to 268 (number of cantons with prescription data)\r\n\r\n`INSEE_ID`: INSEE code\r\n\r\n`CANTON_NAME`: Canton name\r\n\r\n`X`: X-coordinate of the centroid (in meters according to NTF)\r\n\r\n`Y`: Y-coordinate of the centroid (in meters according to NTF)\r\n\r\n`Z`: Variable Z (average prescription amount per consultation in 1999, in French Francs)\r\n\r\n`X2`: Variable X2 (percentage of patients 70 or older)\r\n\r\n`X1`: Variable X1 (per-capita income)\r\n\r\n`E`: Variable E (number of consultations in 1999)\r\n\r\n`N1-N12`: INSEE_IDs of the neighbour cantons (up to 12 neighbors)\r\n\r\n\r\n**Canton_vertex.csv**\r\n\r\n`Variable` Variable Explanation\r\n\r\n`No.`: ID number from 1 to 300 (number of all cantons in Midi-Pyrenees Region)\r\n\r\n`INSEE_ID`: INSEE code\r\n\r\n`CANTON_NAME`: Canton name\r\n\r\n`X`: X-coordinate of the centroid (in meters according to NTF)\r\n\r\n`Y`: Y-coordinate of the centroid (in meters according to NTF)\r\n\r\n`X1,Y1 - X76,Y76`: (X,Y) coordinates of vertices of the corresponding CANTON (up to 76 vertices) \r\n\r\nIn addition to Cressie et al. (2005) and Section 4.2 of Cressie and Wikle (2011), these data have been analysed and modeled in Kang et al. (2009).\r\n\r\n\r\n\r\nCanton_neighbor.csv: Doctor-Prescription Amounts per Consultation and other covariates in Midi-Pyrenees cantons. Also included are the cantons\' neighbors. Note: only the 268 cantons with prescription data are included in this file. \r\n\r\nCanton_vertex.csv: Verticies of the polygons describing all cantons, including "missing cantons"; the first 268 cantons in the dataset are those with doctor-prescription data. \r\n\r\nUsage:\r\n-----------------\r\n\r\n\r\n\r\n**All Cantons**: there are 32 "missing cantons" in the Midi-Pyrenees that do not have doctor-prescription data. Recall there are 268 cantons with doctor-prescription data. Then, there are 300 cantons in total. \r\n\r\n\r\n\r\n**Missing Cantons**: the centroids of 32 "missing cantons"; since there are a total of 294 administrative cantons in the Midi-Pyrenees, 6 of the so-called missing cantons must be small polygons formed by digitization error. It is not known which of the 32 \'cantons\' whose centroids are shown in this file are real and which are artefacts of the digitization. This does not affect our analysis of the 268 cantons with data.\r\n\r\nReferences:\r\n--------\r\n\r\nN. Cressie, O. Perrin, and C. Thomas-Agnan. Likelihood-based estimation for Gaussian MRFs. Statistical Methodology, 2:1-16, 2005.\r\n\r\nE. L. Kang, D. Liu, and N. Cressie. Statistical analysis of small-area data based on independence, spatial, non-hierarchical, and hierarchical models. Computational Statistics and Data Analysis, 53:3016-3032, 2009.\r\n\r\nN. Cressie, and C. K. Wikle. Statistics for Spatio-temporal Data. 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