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103 results for “GBIF”
Global taxonomic occurrence grids using GBIF data for species distribution models.
<p>To achieve large geographic coverage, species occurrence databases that are composed of ad hoc species data collections such as that provided by the Global Biodiversity Information Facility (GBIF) are often used. A drawback to using these data is their geographic sampling bias, in which some regions are more intensively sampled than others, while other areas have very little to none reported sampling effort. Uneven sampling effort can mislead conclusions about biodiversity patterns and species distributions (Gotelli & Colwell, 2001; Lobo, 2008).</p> <p>Here we provide taxonomic occurrence grids to help mitigate the effects of sampling bias in species distribution modeling. These grids can be used to exclude areas of (a custom-defined) low sampling effort from the background when sampling for pseudo-absences’ (Phillips et al., 2009; Barbet-Massin et al.,2012). The occurrence grids have a 1 degree spatial resolution using WGS 84 as the geographic coordinate system. Each 1 degree grid cell contains the number of records present in GBIF corresponding to a specific taxonomic group: plants, mammals, reptiles, amphibians, birds and molluscs.</p> <p>To construct the occurrence grids, we used the 1- by 1-degree world latitude and longitude vector grid provided by ESRI (Redlands, California). It has a custom license which permits it reuse as long as ESRI is cited. It was downloaded from : <a href="https://www.arcgis.com/home/item.html?id=f11bcdc5d484400fa926dcce68de3df7">https://www.arcgis.com/home/item.html?id=f11bcdc5d484400fa926dcce68de3df7</a></p> <p>To map spatial sampling effort, the number of georeferenced occurrences corresponding to each taxonomic group contained by each 1- by 1-degree grid cell were counted. The grids were then converted to GeoTIFFs. The raster values correspond to the number of occurrences reported for the grid cells. For the purposes of the <a href="https://osf.io/7dpgr/">TrIAS project</a>, grid cells with fewer than 5 occurrences were removed. The TrIAS taxonomic occurrence grids are used as inputs to the TrIAS risk modelling and mapping workflow: https://github.com/trias-project/risk-modelling-and-mapping. Full (with all grid cells containing at least one occurrence) taxonomic occurrence grids are also provided.</p> <p>GBIF data for each taxonomic group were downloaded using the following criteria: “Basis of Record”: Observation, Machine Observation, Human Observation, Specimen, Material sample, Literature Occurrence, Unknown evidence., "HasCoordinate is true", "HasGeospatialIssue is false", "TaxonKey is Amphibia", "Year 1975-2005".</p> <p><strong>Raster Attributes</strong></p> <table> <tbody> <tr> <td> <p>Attribute</p> </td> <td> <p>Description</p> </td> </tr> <tr> <td> <p>OID</p> </td> <td> <p>numeric row ID</p> </td> </tr> <tr> <td> <p>Value</p> </td> <td> <p>the number of records contained in the grid cell</p> </td> </tr> <tr> <td> <p>Count</p> </td> <td> <p>the number of times the value appears in the raster</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p>The extent of each taxonomic occurrence grid:</p> <ul> <li> <p>longitude -180.0; latitude -90.0 (southwest corner)</p> </li> <li> <p>longitude 180.0; latitude 90.0 (northeast corner)</p> </li> </ul> <p> </p> <p><strong>Files:</strong></p> <p>TrIAS taxonomic occurrence grids</p> <p>amphib_1deg_min5.tif</p> <p>birds_1deg_min5.tif</p> <p>mammals_1deg_min5.tif</p> <p>molluscs_1deg_min5.tif</p> <p>reptiles_1deg_min5.tif</p> <p> </p> <p>Raw taxonomic occurrence grids</p> <p>amphib_1deg_grid.tif</p> <p>birds_1deg_grid.tif</p> <p>mammals_1deg_grid.tif</p> <p>molluscs_1deg_grid.tif</p> <p>reptiles_1deg_grid.tif</p> <p><br> </p> <p> </p> <p> </p>
NMNH Images: NMNH images from GBIF export
Public records of accessioned specimens and observations curated by the National Museum of Natural History, Smithsonian Institution. These data are from the Departments of Botany, Entomology, Invertebrate Zoology and Vertebrate Zoology (Amphibians & Reptiles, Birds, Fishes, and Mammals) and include more than 270,000 primary type specimen records. <p></p>https://collections.nmnh.si.edu/ipt/resource?r=nmnh_extant_dwc-a<p></p>
Plantago patagonica occurrences from the Colorado Plateau, GBIF download 02/18/2022
<p><em>Plantago patagonica</em> occurrences from the Colorado Plateau, GBIF download 02/18/2022. Downloaded with <em>gbif</em> function from <em>dismo</em> package in R.</p>
gbif-norway/dataset_uio_nhm_nef_lepidoptera: UiO NHM NEF Lepidoptera dataset v1.100
<p><strong>UiO NHM NEF Lepidoptera dataset v1.100 prepared for archiving</strong></p> <p>This dataset included compiled Norwegian Lepidoptera information (65 902 occurrences) by the Norwegian Entomological Society and was published in GBIF between 30 July 2012 and 6 December 2017. In December 2017 [head engineer Leif Aarvik](http://www.nhm.uio.no/om/organisasjon/forskning-samlinger/personer/laarvi/) requested the dataset to be retracted from GBIF because all data points have been migrated to the Museum Collection Database (MUSIT) for Entomology and is now published in GBIF as part of this dataset. Metadata for the Lepidoptera dataset will of course remain available in GBIF as a so-called "metadata-only" dataset.</p>
GBIF map data latest examples: species Gadus morhua
Open the record for dataset details and reuse information.
GBIF map data latest examples: genus Gadus
Open the record for dataset details and reuse information.
GBIF map data latest examples: order Gadiformes
Open the record for dataset details and reuse information.
GBIF map data latest examples: family Gadidae
Open the record for dataset details and reuse information.
A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF)
<p>Publication date:<br> 2022-12-06T07:37:19-06:00</p> <p><br> A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF)<br> ---</p> <p>Global Biodiversity Information Facility (GBIF) facilitates access to billions of biodiversity data records. These records include detailed accounts of life on earth.</p> <p>To help records of specific life forms, GBIF provides a taxonomic backbone [1,2]. This backbone contains a long list of names used to describe species and associated hierarchies and taxonomic publications. These lists are sourced from datasets around the world.</p> <p>At time of writing (6 Dec 2022), GBIF publishes a simplified version of their taxonomic backbone at [https://hosted-datasets.gbif.org/datasets/backbone/](https://hosted-datasets.gbif.org/datasets/backbone/) [1].</p> <p>This repository provides script to pre-process https://hosted-datasets.gbif.org/datasets/backbone/current/simple.txt.gz to help facilitate access and improve performance of the creation of search indexes.</p> <p>Pre-process steps currently include:<br> 1. reducing amount of columns<br> 2. reverse sort by id<br> 3. reverse sort by name</p> <p><br> Contents<br> ---</p> <p>README:<br> this file</p> <p>repackage-gbif-backbone.sh:<br> script used to repackage GBIF Simple Backbone.</p> <p>repackage-gbif-backbone.log:<br> log of repackaging of GBIF Simple Backbone.</p> <p>backbone-current-simple.txt.gz:<br> original GBIF backbone archive</p> <p>gbif-backbone-by-name.tsv.gz:<br> two columns, gzipped, tab-separated text file with columns name, and id<br> reverse sorted by name </p> <p>gbif-backbone-by-name.tsv.sha256:<br> sha256 hash of the uncompressed gbif-backbone-by-name.tsv.gz</p> <p>gbif-backbone-by-id.tsv.gz:<br> 20 columns, gzipped, tab-separated text file with first 20 columns of repackaged GBIF backbone file<br> reverse sorted by id</p> <p>gbif-backbone-by-id.tsv.sha256:<br> sha256 hash of the uncompressed gbif-backbone-by-id.tsv.gz</p> <p>References<br> ---</p> <p>[1] Simplied GBIF Backbone Taxonomy. Accessed at https://hosted-datasets.gbif.org/datasets/backbone/ on 2022-12-06.<br> [2] GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2021-08-18.</p> <p><br> Hash URIs<br> ---<br> This publication includes the following content uris:</p> <p>hash://sha256/82d5f2153b4533322692d95eeb18b0f103e1b2297e38bd9ea935b07ba86cd7d5<br> hash://sha256/50c155f66efb2efba0b8b624f8541e81cbe16a701d420a5073791fb993f72919<br> hash://sha256/9cd7d4c91292d86c726210446cd6fe45602505a7c0ea3b7c4f4f481f85f193ad (uncompressed)<br> hash://sha256/f950dde25cce9ba9cce67caa1c68ce0c99cb31fe2dc9658fec85a987d9f31654<br> hash://sha256/f21c6b90f17c6083fcfb4853f3c581dcc2aadd291691fa128392a205321f420b (uncompressed)<br> hash://sha256/5e0a4d1d2d1cccbdcc6b2c9831fafe61c54eb055f2d13ec40d9ac161889b9f89<br> hash://sha256/f6e477133d0585706ee5522963b204200cb3cd198f011cbf62be0fa8519763b5 (uncompressed)<br> </p>
GBIF animal distribution in Spain
<p>CSV that contains 1.000 GBIF observations of animals than have been involved in wildlife–vehicle collision on interurban roads in Spain and a buffer of each species distribution calculated with these data. If you are interested in the whole country, please do not hesitate to contact me and I will forward it to you.</p> <p>Each record describes the observation by the following fields:</p> <ul> <li><strong> gbifid: </strong>the unique identifier for an occurrence record in GBIF.</li> <li><strong> datasetkey: </strong>the local dataset id within the GBIF network.</li> <li><strong> occurrenceid: </strong>a unique identifier for the occurrence, allowing the same occurrence to be recognized across dataset versions as well as through data downloads and use.</li> <li><strong> kingdom: </strong>the full scientific name specifying the kingdom that the occurrence's scientific name is classified under.</li> <li><strong> phylum: </strong>the full scientific name of the phylum or division in which the taxon is classified<strong>.</strong></li> <li><strong> class: </strong>the full scientific name of the class in which the taxon is classified.</li> <li><strong> order: </strong>the full scientific name of the order in which the taxon is classified.</li> <li><strong> </strong><strong>family: </strong>the full scientific name of the family in which the taxon is classified.</li> <li><strong> genus: </strong>the full scientific name of the genus in which the taxon is classified.</li> <li><strong> species: </strong>species classification key.</li> <li><strong> infraspecificepithet: </strong>the name of the lowest or terminal infraspecific epithet of the scientificName, excluding any rank designation.</li> <li><strong> taxonrank: </strong>the taxonomic rank of the supplied scientific name.</li> <li><strong> scientificname: </strong>the full scientific name of the organism, to the lowest level taxonomic rank that is possible to supply, and including authorship and year of the name where applicable.</li> <li><strong> verbatimscientificname: </strong>the taxonomic rank of the most specific name in the scientificName as it appears in the original record.</li> <li><strong> verbatimscientificnameauthorship: </strong>non described.</li> <li><strong> countrycode: </strong>a two-letter standard abbreviation for the country of the occurrence locality.</li> <li><strong> locality: </strong>the specific description of the place.</li> <li><strong> stateprovince: </strong>the name of the next smaller administrative region than country (state, province, canton, department, region, etc.) in which the Location occurs.</li> <li><strong> occurrencestatus: </strong>a statement about the presence or absence of a Taxon at a Location.</li> <li><strong> individualcount: </strong>to record the quantity of a species occurrence, e.g. as the number of individuals, percentage of vegetation coverage, or the biomass .</li> <li><strong> publishingorgkey: </strong>the publishing organization key (a uuid).</li> <li><strong> decimallatitude: </strong>the geographic latitude, resp., in decimal degrees. </li> <li><strong> decimallongitude: </strong>the geographic longitude, resp., in decimal degrees. </li> <li><strong> coordinateuncertaintyinmeters: </strong>the horizontal distance from the given decimalLatitude and decimalLongitude in meters, describing the smallest circle containing the whole of the Location.</li> <li><strong> coordinateprecision: </strong>a decimal representation of the precision of the coordinates given in the decimalLatitude and decimalLongitude.</li> <li><strong> elevation: </strong>elevation (altitude) in meters above sea level. Supports range queries.</li> <li><strong> elevationaccuracy: </strong>non described.</li> <li><strong> depth: </strong>depth in meters relative to altitude. For example 10 meters below a lake surface with given altitude. Supports range queries.</li> <li><strong> depthaccuracy: </strong>non described.</li> <li><strong> eventdate: </strong>the date or date interval during which the occurrence record was collected, following ISO 8601 date-time standard.</li> <li><strong> day: </strong>the integer day of the month on which the Event occurred.</li> <li><strong> month:</strong> the integer month in which the Event occurred.</li> <li><strong> year: </strong>the four-digit year in which the Event occurred, according to the Common Era Calendar.</li> <li><strong> taxonkey: </strong>a taxon key from the GBIF backbone.<strong> </strong></li> <li><strong> specieskey: </strong>species classification key.</li> <li><strong> basisofrecord: </strong>the type of the individual record, e.g. observation, physical specimen, fossil, living ex-situ, culture collection specimen.</li> <li><strong> institutioncode: </strong>the name (or acronym) in use by the institution having custody of the object(s) or information referred to in the record.</li> <li><strong> collectioncode: </strong>the name, acronym, coden, or initialism identifying the collection or data set from which the record was derived.</li> <li><strong> catalognumber: </strong>an identifier (preferably unique) for the record within the data set or collection.</li> <li><strong> recordnumber: </strong>an identifier given to the Occurrence at the time it was recorded. Often serves as a link between field notes and an Occurrence record, such as a specimen collector's number.</li> <li><strong> identifiedby: </strong>a list (concatenated and separated) of names of people, groups, or organizations who assigned the Taxon to the subject.</li> <li><strong> dateidentified: </strong>the date on which the subject was determined as representing the Taxon.</li> <li><strong> license: </strong>a machine-readable statement of the rights assigned to the published dataset.</li> <li><strong> rightsholder: </strong>a person or organization owning or managing rights over the resource.</li> <li><strong> recordedby: </strong>the name of the institution or organization listed as the data publisher on GBIF.org.</li> <li><strong> typestatus:</strong> a list (concatenated and separated) of nomenclatural types (type status, typified scientific name, publication) applied to the subject.</li> <li><strong> establishmentmeans: </strong>The process by which the biological individual(s) represented in the Occurrence became established at the location.</li> <li><strong> lastinterpreted: </strong>this date the record was last modified in GBIF, in ISO 8601 format: yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. </li> <li><strong> mediatype: t</strong>he kind of multimedia associated with an occurrence as defined in GBIF MediaType enum</li> <li><strong> issue:</strong> a specific interpretation issue as defined in GBIF OccurrenceIssue enum.</li> <li><strong> geom (geometry):</strong> geometry from latitude and longitude position. Developed for this project.</li> <li><strong> buff (geometry): </strong>buffer around 'geom' taking into account 'coordinateuncertaintyinmeters' and 'coordinateprecision'.<strong> </strong>Developed for this project.</li> </ul> <p>The context is the Final Master's Degree Project 'Analysis and Predictive Modelling of Wildlife–Vehicle Collision on Interurban Roads in Spain' (Data Science Master’s Degree of Universitat Oberta de Catalunya - UOC).</p> <p>This dataset is the output of the animal analysis and the <a href="https://github.com/alba620/analisis-prediccion-accidentes-trafico-animales">code repository</a> is available on GitHub.</p>
Global Biodiversity Information Facility (GBIF): an exhaustive list of gbif record ids, dataset keys, and their associated Occurrence IDs, Institution Code, Collection Codes and Catalog Numbers. hash://sha256/ea88f03a7bfd1ba853fdbea3203d54ab81ac3cdc8e8da7c96bbbba9c4b05d933 hash://md5/c49fe34785354847b37ea4509261e130
<p>The Global Biodiversity Information Facility (GBIF) indexes thousands of biodiversity datasets from Natural History Collections, citizen science initiatives (e.g., iNaturalist, eBird), and other sources. As part of the index process, GBIF associates at least two identifiers with indexed records: a record id (aka gbifID) and a dataset id (aka dataset key). These ids are central to do lookup, reference data, and package interpreted data products.</p> <p>This publication contains an exhaustive list of GBIF IDs and ids associated by their data providers as derived from:</p> <p>GBIF.org (01 March 2023) GBIF Occurrence Download https://doi.org/10.15468/dl.pk3trq</p> <p>The resource (size: ~260GB) provided by GBIF had content id hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 and was used to generate the resource included in this publication using</p> <pre><code class="language-bash">preston cat 'zip:hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97!/0015281-230224095556074.csv'\ | cut -f 1,2,3,37,38,39\ | gzip\ > gbifid.tsv.gz </code></pre> <p>with the content id of gbifid.tsv.gz (size: ~35GB) being hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8 .</p> <p>the first 10 lines of gbifid.tsv.gz as extracted via</p> <pre><code>preston cat --remote https://zenodo.org/record/7789866/files,https://linker.bio hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8\ | gunzip\ | head</code></pre> <p>are:</p> <pre><code>gbifID datasetKey occurrenceID institutionCode collectionCode catalogNumber 2997162320 c71c8000-9fc7-422c-804a-ce6abe751771 3399442 CEPEC CEPEC CEPEC00109669 2997162309 c71c8000-9fc7-422c-804a-ce6abe751771 2733085 CEPEC CEPEC CEPEC00000818 2997162317 c71c8000-9fc7-422c-804a-ce6abe751771 2733086 CEPEC CEPEC CEPEC00000888 2997162313 c71c8000-9fc7-422c-804a-ce6abe751771 3399443 CEPEC CEPEC CEPEC00109744 2997162306 c71c8000-9fc7-422c-804a-ce6abe751771 2733087 CEPEC CEPEC CEPEC00000889 2997162316 c71c8000-9fc7-422c-804a-ce6abe751771 3399440 CEPEC CEPEC CEPEC00109605 2997162324 c71c8000-9fc7-422c-804a-ce6abe751771 2733088 CEPEC CEPEC CEPEC00000890 2997162308 c71c8000-9fc7-422c-804a-ce6abe751771 3399441 CEPEC CEPEC CEPEC00109615 2997162303 c71c8000-9fc7-422c-804a-ce6abe751771 2733089 CEPEC CEPEC CEPEC00000891</code></pre> <p>Note that at time of writing, the html resource associated with the occurrence id 2997162320, and data set key c71c8000-9fc7-422c-804a-ce6abe751771 (extracted from of the first data row example above) are available via:</p> <p>https://gbif.org/occurrence/2997162320</p> <p>and</p> <p>https://gbif.org/dataset/c71c8000-9fc7-422c-804a-ce6abe751771</p> <p>respectively.</p> <p>This resource was initially created to help integrate with Bionomia (https://bionomia.net) to help associate people identifiers provided by bionomia to their original records via their GBIF ids. Bionomia re-uses GBIF records ids as a way to define links between records and the people (e.g., curators, collectors, identifiers) that worked on them. </p> <p>In other words, this resource provides a versioned translation table from the GBIF data universe (as defined by GBIF record ids, and dataset keys) to the data collections that exist (and evolve) independent of it. </p> <p>Note that the resource identified by hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 was not included in this publication it was too big (260GB) to fit. You may be able to retrieve the resource from its original location at https://api.gbif.org/v1/occurrence/download/request/0015281-230224095556074.zip .</p>
Native North American Silene (L.) Occurrences Filtered from GBIF
<p>This is a dataset including all Native <em>Silene</em> species accepted in taxonomic nomenclature and considered to inhabit the North American range. Data was downloaded using rgbif::occ_download and accessed from R via rgbif (https://github.com/ropensci/rgbif) on 2023-03-29. The original unfiltered GBIF occurrences can be download at https://doi.org/10.15468/dl.g89y2y, and https://api.gbif.org/v1/occurrence/download/request/0128277-230224095556074.zip. The data is filtered to have coordinates in North America, no geospatial issues, no spatial duplicates filtered to the infraspecific epithet, no coordinate uncertainty greater than 100000 meters, and no occurrences lying within 1km of a college or university. This dataset is incomplete as it does not include ALL observations that occur in North American countries as observations lacking a continent field of "north_america" in GBIF are not included.</p>
GBIF: US bird locations for sightings in 2013
<p>A tab delimited file containing the coordinates rounded to 1 decimal place for U.S. bird observations for each day of 2013. Dataset holds data available through GBIF.org on 29th December 2014. </p> <p>Data schema: day,month,year,latitude,longitude,numberOfRecords</p>
GBIF Backbone matches - changes
<p>All GBIF occurrence records with changed species matches due to an improved matching service. See http://gbif.blogspot.com/2015/03/improving-gbif-backbone-matching.html for details</p>
JSTOR plant type specimens linked to GBIF occurrences
<p>A mapping between URLs for type specimens in JSTOR Global Plants and the corresponding occurrence in the Global Biodiversity Information Facility (GBIF).</p><p>Guide to fields:</p><ul><li><strong>doi</strong>: JSTOR identifier</li><li><strong>code</strong>: Barcode:</li><li><strong>gbif</strong>: GBIF occurrence id</li><li><strong>occurrenceUrl</strong>: URL to specimen in original herbarium database</li><li><strong>occurrenceID</strong>: occurrenceID stored in GBIF</li><li><strong>title</strong>: Title of specimen in JSTOR</li><li><strong>resource_type</strong>: Type of resource</li><li><strong>canonical</strong>: Canonical taxonomic name</li><li><strong>stored_under_name</strong>: Taxonomic name specimen is stored under</li><li><strong>type_status</strong>: What kind of type</li><li><strong>family</strong>: Family plant species belongs to</li><li><strong>collector</strong>: Collector</li><li><strong>date</strong>: Date of collection</li><li><strong>country</strong>: Country of collection</li><li><strong>herbarium</strong>: Herbarium where specimen is stored</li><li><strong>names</strong>: All taxonomic names associated with specimen as JSON array</li><li><strong>url</strong>: JSTOR URL</li><li><strong>thumbnailUrl</strong>: URL to thumbnail of image in JSTOR</li></ul>
Fig. 5 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?
Fig. 5: Das Suchportal des Botanik-Knotens von GBIF-Deutschland, einer der mehreren im Internet verfügbaren Zugangspunkte zu den Daten des GBIF-Netzwerks.
Fig. 2 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?
Fig. 2:Tatenflüsse über das Internet im GBIF-Netzwerk zwischen Nutzer, Suchportal und Datenlieferant.
Fig. 3 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?
Fig. 3: Die Zuordnung der Daten aus dem relationalen Datenschema der Sammlungsdatenbank zu den ABCD-Elementen wird im Mapping festgelegt und ist in einer komfortablen Oberfläche mit dem Internet- Browser möglich.
Fig. 1 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?
Fig. 1: Die Wrapper-Software umgibt die bestehenden Sammlungsdatenbanken mit einer zusätzlichen Abstraktionsschicht und bietet so eine definierte Schnittstelle zwischen den existierenden Datenbanksystemen und den GBIF-Suchportalen.
Fig.1 in Die Global Biodiversity Information Facility (GBIF) - Struktur, Aufgaben und Ziele
Fig.1: Das Knotensystem GBIF Deutschland und seine Anbindung an GBIF International. Die Daten fliessen aus den Teilprojekten in die Datenbanksysteme der einzelnen Knoten, denen ein BioCASE-Wrapper aufgesetzt ist, der auf dem ABCD-Datenmodell basiert. Damit ist es möglich, alle angebundenen Daten über das Datenportal von GBIF International im Internet abzurufen bzw. verfügbar zu machen. GBIF International stellt ausserdem die Wrapper-Software DiGIR, welche auf dem Darwin Core 2 aufbaut, zur Verfügung. Einzelne Teilprojekte, wie z.B. DIG mit BIODAT im Knoten Evertebraten I, setzen eigene Datenbanklösungen ein und fungieren daher als direkte GBIF Datenprovider. Die Angaben entsprechen dem Stand Anfang April 2005.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.