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79 results for “plant database”
AusTraits: a curated plant trait database for the Australian flora
<p>AusTraits is a transformative database, containing measurements on the traits of Australia's plant taxa, standardised from hundreds of disconnected primary sources. So far, data have been assembled from > 300 distinct sources, describing > 500 plant traits and > 34,000 taxa.</p> <p>To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource are also available on the project's GitHub repository, <a href="https://github.com/traitecoevo/austraits.build/">https://github.com/traitecoevo/austraits.build/</a>.</p> <p>Further information on the project is available at the project website <a href="https://austraits.org">austraits.org</a> and in the associated publication (see below).</p> <p><strong>CONTRIBUTORS</strong></p> <p>The project is jointly led by Dr Daniel Falster (UNSW Sydney), Dr Rachael Gallagher (Western Sydney University), Dr Elizabeth Wenk (UNSW Sydney), and Dr Hervé Sauquet (Royal Botanic Gardens and Domain Trust Sydney), with input from > 300 contributors from over > 100 institutions (see full list above). The project was initiated by Dr Rachael Gallagher and Prof Ian Wright while at Macquarie University.</p> <p>We are grateful to the following institutions for contributing data Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium, Department of Environment Land Water and Planning Victoria and the Royal Botanic Gardens Victoria.</p> <p>AusTraits has been supported by investment from the Australian Research Data Commons (ARDC), via their "Transformative data collections" (https://doi.org/10.47486/TD044) and "Data Partnerships" (https://doi.org/10.47486/DP720, https://doi.org/10.47486/DP720A) programs; and grants from the Australian Research Council (FT160100113, DE170100208, FT100100910) and Macquarie University, The ARDC is enabled by National Collaborative Research Investment Strategy (NCRIS).</p> <p><strong>ACCESSING AND USE OF DATA</strong></p> <p>The compiled AusTraits database is released under an open source licence (CC-BY), enabling re-use by the community.</p> <p>A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors:</p> <blockquote> <p>Falster, Gallagher et al (2021) <em>AusTraits, a curated plant trait database for the Australian flora</em>. Scientific Data 8: 254, <a href="https://doi.org/10.1038/s41597-021-01006-6">https://doi.org/10.1038/s41597-021-01006-6</a></p> </blockquote> <p>In addition, we encourage users you to cite the original data sources, wherever possible.</p> <p>Note that under the license data may be redistributed, provided the attribution is maintained.</p> <p>The downloads below provide the data in two formats:</p> <ul> <li>austraits-X.X.X.zip: data in plain text format (.csv, .bib, .yml files). Suitable for anyone, including those using Python.</li> <li>austraits-X.X.X.rds: data as compressed R object. Suitable for users of R (see below).</li> <li> <div>austraits-X.X.X-flattened.rds: contains a flattened version of the dataset for direct loading in R; all data tables are joined into a wider format</div> </li> <li> <div>austraits-X.X.X-flattened.parquet: contains a flattened version of the dataset in parquet format; all data tables are joined into a wider format </div> </li> </ul> <p>For R users, access and manipulation of data is assisted with the <a href="http://github.com/traitecoevo/austraits">austraits R package</a>. The package can both download data and provides examples and functions for running queries.<br><br><strong>STRUCTURE OF AUSTRAITS</strong></p> <p>The compiled AusTraits database contains a series of relational tables and files. These elements include all the data, contextual information submitted with each contributed datasets, database schema, and trait definitions. The file dictionary.html provides the same information in textual format. Similar information is available at <a href="https://traitecoevo.github.io/traits.build-book/">https://traitecoevo.github.io/traits.build-book/</a>.</p> <p><strong>CONTRIBUTING</strong></p> <p>We envision AusTraits as an on-going collaborative community resource that:</p> <ol> <li>Increases our collective understanding the Australian flora;</li> <li>Facilitates accumulation and sharing of trait data;</li> <li>Builds a sense of community among contributors and users; and</li> <li>Aspires to fully transparent and reproducible research of the highest standard.</li> </ol> <p>As a community resource, we are very keen for people to contribute. Assembly of the database is managed on GitHub at <a href="https://github.com/traitecoevo/austraits.build/">https://github.com/traitecoevo/austraits.build/</a>.</p> <p>Here are some of the ways you can contribute:</p> <p><strong>Reporting Errors</strong>: If you notice a possible error in AusTraits, please <a href="https://github.com/traitecoevo/austraits.build/issues">post an issue on GitHub</a>.</p> <p><strong>Refining documentation:</strong> We welcome additions and edits that make using the existing data or adding new data easier for the community.</p> <p><strong>Contributing new data</strong>: We gladly accept new data contributions to AusTraits. See full instructions on how to contribute at <a href="https://github.com/traitecoevo/austraits.build/">https://github.com/traitecoevo/austraits.build/</a>.</p>
Wisconsin Lake Plants - multi source database of lake plant abundance 1930 - 2004
This data set provides sampling-point by sampling-point macrophyte data for lakes sampled by a number of agencies in Wisconsin. The relational tables in this dataset were originally used to generate plant community tables. This dataset contains detailed and recent data from approximately the 1970s onward. Sampling timing and intensity varied. Table DATSOUR contains sources of data for tables AQUAPLT2 and LAKEHAB. Table AQUAPLT2 gives an estimate of plant density at each sample point. Table MAXDEPLNG has initial lake parameters derived from data in AQUAPLT2 and LAKEHAB Table LAKEHAB contains habitat characteristics at macrophyte sampling locations. Table PLTNAME has species information for plants in tables AQUAPLT2 and LAKESPEC. Table LAKES contains information for lakes included in this dataset. Table COUNTY contains information associated with the counties where the lakes in the AQUAPLT2 dataset and the LAKESPEC dataset are located. . Sampling Frequency: varies Number of sites: 1938
S29 | PHYTOTOXINS | Toxic Plant Phytotoxin (TPPT) Database
<p>This is the collection associated with list S29 PHYTOTOXINS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>S29 PHYTOTOXINS <strong>Toxic Plant Phytotoxin (TPPT) Database</strong></p> <p>A comprehensive toxic plant-phytotoxin (TPPT) database provided by Günthardt et al 2018, DOI: <a href="https://pubs.acs.org/doi/10.1021/acs.jafc.8b01639">10.1021/acs.jafc.8b01639</a><br>More information on the <a href="https://www.agroscope.admin.ch/agroscope/en/home/publications/apps/tppt.html">Agroscope TPPT website</a>.</p> <p>Updated 20/11/2019 to correct InChIKey errors; updated 16/7/2022 to create merged SMILES column for PubChem deposition. 27/6/2025 added new CSV without duplicate CAS headers. </p>
Data from 'Tracability of Forest Reproductive Material with the quality label 'Plant van Hier': A DNA database with genetic profiles of native autochthonous tree and shrub species of Flanders, Belgium'
<h2>Background</h2> <p>Indigenous trees and shrubs play an important role in multifunctional forest management. They form a significant part of the biodiversity in our forests. Forest reproductive material (FRM) of autochthonous Flemish origin is sold under the quality label ‘Plant van Hier’, a certification mark of the Agency for Nature and Forests. To ensure the provenance of the seedlings, we developed a DNA-database of genetic profiles of potential parent trees, using species-specific genetic markers. This database enables the traceability of FRM of the ‘Plant van Hier’ label throughout the entire production chain; from seed harvesting and cultivation to planting by the end user.</p> <p>This database contains the genetic profiles of almost all possible parent trees present within 27 Flemish autochthonous seed orchards of eight ecologically important tree and shrub species: <em>Carpinus betulus</em>, <em>Corylus avellana</em>, <em>Frangula alnus</em>, <em>Populus tremula</em>, <em>Sorbus aucuparia</em>, <em>Tilia cordata</em>, <em>Tilia platyphyllos,</em> and <em>Ulmus laevis</em>. The profiles were established using microsatellite markers (11 to 24 markers per species). New genetic markers were developed for <em>Carpinus betulus</em> and <em>Ulmus laevis</em>. PCR products were run on an ABI 3500 Genetic Analyser (Thermo Fisher Scientific).</p> <h2>Files</h2> <p>The files will be updated when new genotypes are added to the seed orchards. The current data files contain data from genotypes collected in the period 2018-2023. </p> <h3>Species_genotypes</h3> <p>These files contain the genetic fingerprints of the parent trees of autochthonous Flemish seed orchards. Missing data is indicated as ‘MD’. For <em>Carpinus betulus</em>, an octoploid species, the allelic phenotype is given instead of the genotype as the number of times that an allele occurs on a specific locus is not known.</p> <p>The next metadata is additionally given:<br>- Species: the Latin name of the species<br>- Seed_orchard: the name of the seed orchard in which the genotypes are located<br>- Code_seed_orchard: the code of the seed orchard in which the genotypes are located as given in the Register of Flemish Forest Reproductive Material (‘Register bosbouwkundig uitgangsmateriaal’; inbo.be)<br>- Genotype: the fieldname given to the genotype<br>- Origin: the location where the genotype was collected in Flanders, Belgium. Genotypes were collected from natural stands which are assumed to have an autochthonous origin. When the specific location is unknown, the location ‘Flanders’ is given. <br>- Year_sampled: the year in which the genotypes were sampled in the respective seed orchard for genetic analysis.</p> <h3>Species_binsets</h3> <p>These files contain the binsets and allele names that are used to score the alleles of the genotypes in the programme Geneious Prime 2019.3.2 (<a href="https://www.geneious.com">https://www.geneious.com</a>). For <em>Tilia platyphyllos </em>and <em>Tilia cordata</em>, the same binsets were used.</p>
Update of the Xylella spp. host plant database
<p>Following a request from the European Commission, in 2018 EFSA released a renovated database of host plant species of <em>Xylella</em> spp. (<em>including both species</em> <em>X. fastidiosa </em>and <em>X. taiwanensis</em><em>) together with a scientific report</em> (EFSA, 2018). EFSA was tasked to maintain and update this database periodically. The mandate now covers the period 2021-2026 and EFSA is requested to release an update of the database twice per year.</p> <p>In July 2025 EFSA released the twelfth update of the <em>Xylella</em> spp. host plant database (VERSION 12) with information retrieved from literature search up to December 2024 and recent Europhyt outbreak notifications (EFSA, 2025). The protocol applied for the extensive literature review, data collection and reporting, as well as results and lists of host plants are described in detail in the related scientific report (EFSA, 2025).</p> <p>The overall number of <em>Xylella</em> spp. host plants determined with at least two different detection methods or positive with one method (between: sequencing, pure culture isolation) reaches now 463 plant species, 210 genera and 71 families (category A – see section 2.4.2 of EFSA (2025)). Such numbers rise to 727 plant species, 319 genera and 91 families if considered regardless of the detection method applied (category E, see section 2.4.2 of EFSA (2025)).</p> <p>The Excel files here attached represent the VERSION 12 of the <em>Xylella</em> spp. host plants database. For a detailed description of the information included in the database, please consult the related scientific report (EFSA, 2025).</p> <p>The Excel file “<em>Xylella</em> spp. host plants database – VERSION 12” contains several sheets: the LEGENDA (with extensive description of each table), the full detailed raw data of the <em>Xylella</em> spp. host plant database (sheet “observation”) and several examples of data extraction.</p> <p>Additional Excel files contain the lists of host plant species of <em>X. fastidiosa</em> (subsp. unknown (i.e. not reported), <em>fastidiosa</em>, <em>multiplex</em>, <em>pauca</em>, <em>morus</em>, <em>sandyi</em>, <em>tashke</em>, <em>fastidiosa/sandyi</em>) and <em>X. taiwanensis</em> infected naturally, artificially and in not specified conditions, and according to different categories (A, B, C, D, E – see section 2.4.2 of EFSA (2025)). The Excel file “new_host_plant_species_v12” contain the list of new host plant species added to the database in this new update.</p> <p><strong>Question number: EFSA-Q-2025-00045</strong></p> <p><strong>Output number: EN-9564</strong></p> <p><strong>Contacts: plants@efsa.europa.eu</strong></p> <p><em>Bibliography:</em></p> <p>EFSA (European Food Safety Authority). (2018). Scientific report on the update of the <em>Xylella</em> spp. host plant database. <em>EFSA Journal 2018</em>, <em>16</em>(9), 5408, 87 pp. <a href="https://doi.org/10.2903/j.efsa.2018.5408">https://doi.org/10.2903/j.efsa.2018.5408</a> </p> <p>EFSA (European Food Safety Authority), Cavalieri, V., Fasanelli, E., Furnari, G., Gibin, D., Gutierrez Linares, A., La Notte, P., Pasinato, L., & Stancanelli, G. (2025). Update of the <em>Xylella</em> spp. host plant database – Systematic literature search up to 31 December 2024. <em>EFSA Journal</em>, <em>23</em>(7), e9563. <a href="https://doi.org/10.2903/j.efsa.2025.9563">https://doi.org/10.2903/j.efsa.2025.9563</a></p>
Compiled database, code and raw data for the article "A Comprehensive Database of Leaf Temperature, Water, and CO2 Fluxes in Young Oil Palm Plants Across Diverse Climate Scenarios for the Evaluation of Functional-Structural Models"
<p>This dataset results from an experiment on young oil palm plants (<em>Elaeis guineensis</em>) in the Ecotron facility from CNRS in Montpellier. Four plants were put in a microcosm one by one with varying climatic conditions to investigate the effect of climate on leaf temperature, CO2, and H2O fluxes at the plant scale. The conditions were defined based on typical daily conditions from a location where it is grown (Libo, Indonesia), <em>i.e.</em>, a day with no rainfall and near-average air temperature and humidity. This base condition was then modified by adding more CO2 (400, 600 and 800ppm), less radiation (typical cloudy sky), and more or less temperature and vapour pressure deficit (± 30%).</p> <p>Find more details from the <code>README.md</code> file in the repository or from the associated <a href="https://github.com/PalmStudio/Biophysics_database_palm" target="_blank" rel="noopener">Github repository</a>.</p>
A database of plant-pollinator networks
<p>This database assembles different published datasets of observed interaction networks between plants and pollinators, which were extracted from articles, theses and existing online databases.</p> <p>Each row in the data table corresponds to an interaction between a plant and a pollinator species reported at a given site by a given publication.</p>
SEV-LTER Plant Traits Database
This dataset contains measurements of morphological (leaf, stem, root, and seed), nutrient, and isotopic traits for plant species growing in the Sevilleta National Wildlife Refuge. Approximately 104 species were sampled in or near four core sites of the SEV-LTER (core_blue, core_black, core_creosote, and core_PJ) plus the Sevilleta Field Station between 2017 and 2021. In addition, seed masses were measured from a 2016-era seed collection provided by Jenny Noble and added to the dataset; for these, site = NA.
Gene/Protein BridgeDb ID Mapping Database (Ensembl Plants 49)
<p>Ensembl Plants 49 derived ID mapping database for use with BridgeDb.<br> The scripts used to create these databases based on Ensembl BioMart can be found at <a href="https://github.com/bridgedb/create-bridgedb-genedb">https://github.com/bridgedb/create-bridgedb-genedb</a>.</p> <p>This work was funded by the <a href="https://fairplus-project.eu/">FAIRplus project</a> (grant agreement no 802750) and <a href="https://www.nwo.nl/en/researchprogrammes/open-science/open-science-fund/open-science-fund-2021-awarded-grants">NWO Open Science Fund</a> (grant no <a href="https://www.nwo.nl/en/projects/203001121">203.001.121</a>).</p>
CINWA: Database of Cultivated plants and their names in the indigenous languages of South America
<p>This repository contains source data for CINWA - Database of Cultivated plants and their names in the indigenous languages of South America</p> <p><br> If you use these data please cite the database</p> <p>Aguilar Panchi, Evelyn Michelle, Saetbyul Lee, Evgenia Brodetsky, and Matthias Urban (eds.). 2022. CINWA - Database of Cultivated plants and their names in the indigenous languages of South America. Version 0.9. Available online at cinwa.org.</p> <p><br> If you would like to cite specific data entries, please also acknowledge the original source by consulting the reference that is associated with that entry. For example: Cook, Dorothy M., and Frances L. Gralow. 2001. Diccionario bilingüe koreguaje-español español-koreguaje. Santafé de Bogotá: Editorial Alberto Lleras Camargo. In: Aguilar Panchi, Evelyn Michelle, Saetbyul Lee, Evgenia Brodetsky, and Matthias Urban (eds.). 2022. CINWA - Database of Cultivated plants and their names in the indigenous languages of South America. Version 0.9. Available online at cinwa.org.</p>
CINWA: Database of Cultivated plants and their names in the indigenous languages of South America
<p><strong>This repository contains source data for CINWA - Database of Cultivated plants and their names in the indigenous languages of South America. If you use these data please cite the database. Aguilar Panchi, Evelyn Michelle, Saetbyul Lee, Evgenia Brodetsky, and Matthias Urban (eds.). 2022. CINWA - Database of Cultivated plants and their names in the indigenous languages of South America. Version 0.9. Available online at cinwa.org. If you would like to cite specific data entries, please also acknowledge the original source by consulting the reference that is associated with that entry. For example: Cook, Dorothy M., and Frances L. Gralow. 2001. Diccionario bilingüe koreguaje-español español-koreguaje. Santafé de Bogotá: Editorial Alberto Lleras Camargo. In: Aguilar Panchi, Evelyn Michelle, Saetbyul Lee, Evgenia Brodetsky, and Matthias Urban (eds.). 2022. CINWA - Database of Cultivated plants and their names in the indigenous languages of South America. Version 0.9. Available online at cinwa.org.</strong></p>
K-mer databases of plant virus sequences for use with the Kodoja workflow
<p><strong>Details</strong></p> <p>This is a gzipped tar file that includes the plant virus database files required to run the Kodoja workflow (https://github.com/abaizan/kodoja)[1]. Kodoja is a workflow for the detection of plant virus sequences in RNA-seq data files that uses two previoulsy published tools Kraken[2] and Kaiju[3].</p> <p>This file contains databases for Kraken [2] and Kaiju [3]. The file includes the kraken database files: database.idx, database.kdb, nodes.dmp, names.dmp and the kaiju database file kaij_library.fmi.</p> <p>These k-mer databases are based on virus sequences in RefSeq [4] (ttps://www.ncbi.nlm.nih.gov/refseq/) with plant hosts as defined in the Virus-Host Database [5] (https://www.genome.jp/virushostdb/).</p> <p><strong>Version</strong><strong> 1.0</strong></p> <p>kodojaDB_v1.0 is based on RefSeq v89 and the Virus-Host Database (accessed 03/09/2018 which is based on RefSeq 89 and Genbank 226.0). The viral partition of RefSeq v89 genome comprises 7946 viruses (ftp://ftp.ncbi.nlm.nih.gov/genomes/refseq/viral/assembly_summary.txt).</p> <p>kodojaDB_v1.0 was created using kodoja_retrieve.py which is part of the kodoja workflow (v0.05) (https://github.com/abaizan/kodoja).</p> <p><strong>References</strong></p> <p>[1] Baizan-Edge, A, Cock, P, MacFarlane, S, McGavin, W, Torrance, T, Jones, S. Kodoja: A workflow for virus detection in plants using k-mer analysis of RNA-sequencing data (under review Nucleic Acids Research). </p> <p>[2] Wood,D.E. and Salzberg,S.L. (2014) Kraken: ultrafast metagenomic sequence classification using exact alignments. <em>Genome Biol.</em>, <strong>15</strong>, R46</p> <p>[3] Menzel,P., Ng,K.L. and Krogh,A. (2016) Fast and sensitive taxonomic classification for metagenomics with Kaiju. <em>Nat. Commun.</em>, <strong>7</strong>, 1–9.</p> <p>[4] O’Leary,N.A., Wright,M.W., Brister,J.R., Ciufo,S., Haddad,D., McVeigh,R., Rajput,B., Robbertse,B., Smith-White,B., Ako-Adjei,D., <em>et al.</em> (2016) Reference sequence (RefSeq) database at NCBI: Current status, taxonomic expansion, and functional annotation. <em>Nucleic Acids Res.</em>, <strong>44</strong>, D733–D745.</p> <p>[5] Mihara,T., Nishimura,Y., Shimizu,Y., Nishiyama,H., Yoshikawa,G., Uehara,H., Hingamp,P., Goto,S. and Ogata,H. (2016) Linking virus genomes with host taxonomy. <em>Viruses</em>, <strong>8</strong>, 10–15</p>
Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database. in The Integrated Plant Record Vegetation Analysis: Internet Platform And Online Application
Text-fig. 1. "Plant screen" scheme of complete results of the IPR-vegetation analysis derived from the database.
Linked collectors and determiners for: Plant Specimen Database of Tama Forest Science Garden, Forestry and Forest Products Research Institute, Japan.
Natural history specimen data linked to collectors and determiners held within, "Plant Specimen Database of Tama Forest Science Garden, Forestry and Forest Products Research Institute, Japan". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/38e8b720-9074-4471-a016-73cae18a6c1c">https://bionomia.net/dataset/38e8b720-9074-4471-a016-73cae18a6c1c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/38e8b720-9074-4471-a016-73cae18a6c1c">https://gbif.org/dataset/38e8b720-9074-4471-a016-73cae18a6c1c</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Database on reference specimens for medicinal plants of the Meliaceae family, conserved at the CNARP herbarium.
Natural history specimen data linked to collectors and determiners held within, "Database on reference specimens for medicinal plants of the Meliaceae family, conserved at the CNARP herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/f0ad347c-dfaf-4326-9bb3-5e25f9b45514">https://bionomia.net/dataset/f0ad347c-dfaf-4326-9bb3-5e25f9b45514</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/f0ad347c-dfaf-4326-9bb3-5e25f9b45514">https://gbif.org/dataset/f0ad347c-dfaf-4326-9bb3-5e25f9b45514</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Database on reference specimens for medicinal plants of the Rubiaceae family, conserved at the CNARP herbarium.
Natural history specimen data linked to collectors and determiners held within, "Database on reference specimens for medicinal plants of the Rubiaceae family, conserved at the CNARP herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/c3caca74-616b-4bad-b795-b13adff022de">https://bionomia.net/dataset/c3caca74-616b-4bad-b795-b13adff022de</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/c3caca74-616b-4bad-b795-b13adff022de">https://gbif.org/dataset/c3caca74-616b-4bad-b795-b13adff022de</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Database of Native Plants in Taiwan.
Natural history specimen data linked to collectors and determiners held within, "Database of Native Plants in Taiwan". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/96c33790-a2b5-11de-9f79-b8a03c50a862">https://bionomia.net/dataset/96c33790-a2b5-11de-9f79-b8a03c50a862</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/96c33790-a2b5-11de-9f79-b8a03c50a862">https://gbif.org/dataset/96c33790-a2b5-11de-9f79-b8a03c50a862</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Botanical Museum, Denmark. Database of registrations of red listed plants.
Natural history specimen data linked to collectors and determiners held within, "Botanical Museum, Denmark. Database of registrations of red listed plants". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/84d94b5a-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/84d94b5a-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/84d94b5a-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/84d94b5a-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: The Himalayan Uplands Plant database (HUP Version 1).
Natural history specimen data linked to collectors and determiners held within, "The Himalayan Uplands Plant database (HUP Version 1)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/82a53efc-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/82a53efc-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/82a53efc-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/82a53efc-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Antarctic Plant Database.
Natural history specimen data linked to collectors and determiners held within, "Antarctic Plant Database". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/82d9ff5c-f762-11e1-a439-00145eb45e9a">https://bionomia.net/dataset/82d9ff5c-f762-11e1-a439-00145eb45e9a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/82d9ff5c-f762-11e1-a439-00145eb45e9a">https://gbif.org/dataset/82d9ff5c-f762-11e1-a439-00145eb45e9a</a>. Formatted as a Frictionless Data package.
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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.