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130 results for “online database”
Phlorest phylogeny derived from Greenhill 2015 'TransNewGuinea.org: An Online Database of New Guinea Languages'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Greenhill, S. J. (2015). TransNewGuinea.org: An Online Database of New Guinea Languages. PLOS ONE, 10(10), e0141563. doi:10.1371/journal.pone.0141563</p> </blockquote>
SAN Online Databases
<p>Collection of online resources of interest to SAN topics. The database is available at SAN website. This is an evolving database. Latest version=V1</p>
Online trust in Information Society. Four representative database and questionnaire (Hungary, Romania, Poland, Czech Republic
<p>This data collection was conducted by the Institute of the Information Society of the University of Public Service - Ludovika, and covered four Central European countries: the Czech Republic, Hungary, Poland, and Romania, with the aim of examining the characteristics of the use of information technology by the adult population in the region, mainly for communication purposes. A telephone survey was conducted in October and November 2019, and the results are representative of the population over 18 years of age in the four countries, categorized by age, gender, education, type of settlement and region.</p> <p><br>The data set contains:</p> <ul> <li>Questionnaires in the original languages (Hungarian, Czech, Romanian and Polish), and all questionnaires in English language, too.</li> <li>The four databases with variables in English</li> <li>Merged database of four databases</li> <li>Code table about variables </li> </ul>
Figure 1 in The Tydeoidea (Ereynetidae, Iolinidae, Triophtydeidae and Tydeidae) - An online database in the Wikispecies platform
Figure 1 Diachronic classification of Tydeoidea. Abbreviations: pcp = post-cunliffean period, Pseudot. = Pseudotydeinae, R = Riccardoellinae, s = synonymy, subfam. = subfamilies, Trioph. = Triophtydeidae.
Figure 4 A-B in The Tydeoidea (Ereynetidae, Iolinidae, Triophtydeidae and Tydeidae) - An online database in the Wikispecies platform
Figure 4 A-B – Tetranychus urticae; C – T. viburni; D – Tydeus goetzi; A – Dissecting microscope view; B-C – Facsimile of Koch's figures (same magnification) with some dorsal setae notation added; D – Compound microscope view, Agroscope Changins [Switzerland], routine black chlorazol coloration by Marc Baillod, scale bar = 100 µm. Koch's "Schulterborsten" correspond to scapular setaesc(1 andsc2) plus the subhumeral seta (c3). A – photoghraphy by Gilles San Martin. CC-BY.
Figure 3 in The Tydeoidea (Ereynetidae, Iolinidae, Triophtydeidae and Tydeidae) - An online database in the Wikispecies platform
Figure 3 The number of ereynetid mites described by Fain and by other acarologists (data grouped by decade).
Figure 2. The structures of the two tables from the Dex Online database-ADX – Agent for Morphologic Analysis of Lexical Entries in a Dictionary
<p>Dex Online is a project initiated and coordinated by Catalin Francu [3]. He intended to<br> realise an online database for all the words in the Romanian language, using the main explanatory<br> dictionaries, dictionaries of synonyms, neologisms, published by the Romanian Academy and other<br> scientific forums.<br> The database was completed by volunteers, similarly to the Wikipedia system. They actually<br> transcribed the information from different important dictionaries, but many words have been<br> electronically entered by two companies (Siveco and Litera International Publishing House).</p>
Figure 1. A in Online database "See The Sea" for the Caspian Sea
Figure 1. A satellite view (true color) of the Caspian Sea on 22 August 2019 from MODIS-Terra (©NASA, 2019).
Bibliographic dataset characterizing studies that use online biodiversity databases
<p>This dataset includes bibliographic information for 501 papers that were published from 2010-April 2017 (time of search) and use online biodiversity databases for research purposes. Our overarching goal in this study is to determine how research uses of biodiversity data developed during a time of unprecedented growth of online data resources. We also determine uses with the highest number of citations, how online occurrence data are linked to other data types, and if/how data quality is addressed. Specifically, we address the following questions:</p> <p>1.) What primary biodiversity databases have been cited in published research, and which</p> <p> databases have been cited most often?</p> <p>2.) Is the biodiversity research community citing databases appropriately, and are</p> <p> the cited databases currently accessible online?</p> <p>3.) What are the most common uses, general taxa addressed, and data linkages, and how </p> <p> have they changed over time?</p> <p>4.) What uses have the highest impact, as measured through the mean number of citations</p> <p> per year?</p> <p>5.) Are certain uses applied more often for plants/invertebrates/vertebrates?</p> <p>6.) Are links to specific data types associated more often with particular uses?</p> <p>7.) How often are major data quality issues addressed?</p> <p>8.) What data quality issues tend to be addressed for the top uses? </p> <p>Relevant papers for this analysis include those that use online and openly accessible primary occurrence records, or those that add data to an online database. Google Scholar (GS) provides full-text indexing, which was important to identify data sources that often appear buried in the methods section of a paper. Our search was therefore restricted to GS. All authors discussed and agreed upon representative search terms, which were relatively broad to capture a variety of databases hosting primary occurrence records. The terms included: “species occurrence” database (8,800 results), “natural history collection” database (634 results), herbarium database (16,500 results), “biodiversity database” (3,350 results), “primary biodiversity data” database (483 results), “museum collection” database (4,480 results), “digital accessible information” database (10 results), and “digital accessible knowledge” database (52 results)--note that quotations are used as part of the search terms where specific phrases are needed in whole. We downloaded all records returned by each search (or the first 500 if there were more) into a Zotero reference management database. About one third of the 2500 papers in the final dataset were relevant. Three of the authors with specialized knowledge of the field characterized relevant papers using a standardized tagging protocol based on a series of key topics of interest. We developed a list of potential tags and descriptions for each topic, including: database(s) used, database accessibility, scale of study, region of study, taxa addressed, research use of data, other data types linked to species occurrence data, data quality issues addressed, authors, institutions, and funding sources. Each tagged paper was thoroughly checked by a second tagger.</p> <p>The final dataset of tagged papers allow us to quantify general areas of research made possible by the expansion of online species occurrence databases, and trends over time. Analyses of this data will be published in a separate quantitative review.</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.
Figure 1 in EphemBrazil: a curated online database and dashboard to explore the distribution of mayflies (Insecta: Ephemeroptera) from Brazil
Figure 1 General view of the website and interactive map view tab showing filters on the top and family subtitles in the right corner. Note that no filter is applied and all records are shown.
The mOTUs online database provides web-accessible genomic context to taxonomic profiling of microbial communities - Supplementary Tables
<p><strong>Supplementary Table 1:</strong></p> <p>A map between each of the genomes in mOTUs-db (3’747’151), the associated study and its metagenomic sample (in case of MAGs).</p> <p>Columns:</p> <p><code> GENOME → Unique mOTUs-db name of the genome</code><br><code> STUDY → Unique mOTUs-db name of the study</code><br><code> IS_MAG → True if genome is a MAG, otherwise False </code><br><code> METAGENOMIC_SAMPLE → Unique name of the metagenomic sample or NA in case of non-MAG genome</code></p> <p>Example:</p> <p><code> GENOME STUDY IS_MAG METAGENOMIC_SAMPLE</code><br><code> ---------------------------------------------------------------------------------------------</code><br><code> ACIN21-1_SAMN05421555_MAG_00000001 ACIN21-1 True ACIN21-1_SAMN05421555_METAG</code><br><code> RSGB23-1_GCA-006096615-V1_GENO_10000001 RSGB23-1 False NA</code></p> <p><strong>Supplementary Table 2:</strong></p> <p>A map between all non-MAG genomes (919’090) and their source (e.g. Refseq or JGI).</p> <p>Columns:</p> <p><code> GENOME → Unique mOTUs-db name of the genome</code><br><code> SOURCE_SAMPLE_LINK → Link to the original location of this genome</code></p> <p>Example:</p> <p><code> #GENOME SOURCE_SAMPLE_LINK</code><br><code> --------------------------------------------------------------------------------------------------------</code><br><code> JGIG23-1_GA0055041_GENO_10000001 https://gold.jgi.doe.gov/analysis_project?id=Ga0055041</code><br><code> RSGB23-1_GCA-006717865-V1_GENO_10000001 https://www.ncbi.nlm.nih.gov/datasets/genome/GCA_006717865.1</code></p> <p><strong>Supplementary Table 3:</strong></p> <p>A list of all metagenomic studies processed for the mOTUs-db, their number of samples, the number of reconstructed MAGs and the associated publication.</p> <p>Columns:</p> <p><code> STUDY --> Unique mOTUs-db study identifier</code><br><code> BIOPROJECT --> Public identifier (NCBI/JGI) of metagenomic sequencing project</code><br><code> SAMPLES --> Number of metagenomic samples</code><br><code> MAGs --> Number of reconstructed MAGs</code><br><code> PUBLICATION --> Link to publication</code></p> <p>Example:</p> <p><code> STUDY BIOPROJECT SAMPLES MAGs PUBLICATION</code><br><code> -------------------------------------------------------------------------------------------------</code><br><code> ACIN21-1 PRJEB44456 58 1,110 https://www.nature.com/articles/s42003-021-02112-2</code></p> <p><strong>Supplementary Table 4:</strong></p> <p>Mapping between mOTUs-db sample identifier, the associated biosample and the environment.</p> <p>Columns:</p> <p><code> SAMPLE --> Unique mOTUS-db sample identifier</code><br><code> BIOSAMPLE --> Public identifier (NCBI/JGI) of metagenomic sample</code><br><code> STUDY --> Unique mOTUs-db study identifier</code><br><code> ENVIRONMENT --> Environment of metagenomic sample</code><br><code> SOURCE_SAMPLE_LINK --> Link to the original location of this sample</code></p> <p>Example:</p> <p><code> #SAMPLE BIOSAMPLE STUDY ENVIRONMENT SOURCE_SAMPLE_LINK</code><br><code> ---------------------------------------------------------------------------------------------------------------------</code><br><code> ACIN21-1_SAMN05421555_METAG SAMN05421555 ACIN21-1 marine https://www.ncbi.nlm.nih.gov/biosample/SAMN05421555/</code></p> <p><strong>Supplementary Table 5:</strong></p> <p>A list of environments covered in the mOTUs-db mapped to the respective NCBI taxonomy (if possible)</p> <p>Columns:</p> <p><code> TERM --> Unique environment name</code><br><code> NCBI TAXONOMY ID --> Link to the NCBI taxonomy</code></p> <p>Example:</p> <p><code> TERM NCBI TAXONOMY ID</code><br><code> ----------------------------------------------</code><br><code> activated sludge metagenome NCBI:txid942017</code><br><code> air metagenome NCBI:txid655179</code></p>
Online example database generated representing nuclear astrophysics models predictions of correlations between stable/stable abundances of specific isotopes.
<p>Library of figures created using the SIMPLE code (Stellar Interpretation for Meteoritic data and PLotting). The SIMPLE stellar database includes 18 core-collapse supernova models with 3 different initial masses of 15, 20, 25 solar masses, all of solar metallicity and non-rotating stars. The 6 sets are the following:</p> <ul> <li>Rauscher et al. 2002 [Ra02]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2002ApJ...576..323R/abstract">https://ui.adsabs.harvard.edu/abs/2002ApJ...576..323R/abstract</a>),</li> <li>Pignatari et al. 2016 [Pi16]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2016ApJS..225...24P/abstract">https://ui.adsabs.harvard.edu/abs/2016ApJS..225...24P/abstract</a>),</li> <li>Sieverdin et al. 2018 [Si18]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2018ApJ...865..143S/abstract">https://ui.adsabs.harvard.edu/abs/2018ApJ...865..143S/abstract</a>),</li> <li>Limongi & Chieffi 2018 [LC18]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2018ApJS..237...13L/abstract">https://ui.adsabs.harvard.edu/abs/2018ApJS..237...13L/abstract</a>),</li> <li>Ritter et al. 2018 [Ri18]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2018MNRAS.480..538R/abstract">https://ui.adsabs.harvard.edu/abs/2018MNRAS.480..538R/abstract</a>),</li> <li>Lawson et al. 2022 [La22]<br>(<a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.511..886L/abstract">https://ui.adsabs.harvard.edu/abs/2022MNRAS.511..886L/abstract</a>)</li> </ul> <p>The figures can be divided into two types. The first shows the structure of the ejecta and the abundance of the selected isotopes. The layers are automatically detected using SIMPLE based on the abundances of the main fuels (H-1, He-4, C-12, O-16, Ne-20, Si-28) from the supernova model ejecta. The code names the different layers based on the schematic diagram in Schofield et al. 2022 (<a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.1803S/abstract">https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.1803S/abstract</a>). <br>Ni and Fe isotopes are plotted in the figures. The abundances shown include the radiogenic contribution from unstable isotopes.</p> <p>The SIMPLE code is designed to compare stellar data with measurements from meteorites. To achieve this, abundances in mass fractions need to be converted into isotopic ratios using specific units. See Lugaro et al. 2023 (<a href="https://ui.adsabs.harvard.edu/abs/2023EPJA...59...53L/abstract">https://ui.adsabs.harvard.edu/abs/2023EPJA...59...53L/abstract</a>) for details. For the specific case of Ni64 ratios, in comparison with model data we report the measured meteoritic anomaly by Steele et al 2012 (<a href="https://ui.adsabs.harvard.edu/abs/2012ApJ...758...59S/abstract">https://ui.adsabs.harvard.edu/abs/2012ApJ...758...59S/abstract</a>) as a continuous horizontal line. The same is done for the Fe54 ratios, with reference measurements by Hopp et al 2022 (<a href="https://ui.adsabs.harvard.edu/abs/2022E%26PSL.57717245H/abstract">https://ui.adsabs.harvard.edu/abs/2022E%26PSL.57717245H/abstract</a>). </p> <p>In the database the abundance plots are identified as <strong>structure_<model refe<em>rence>_<initial mass>_<element>_<decayed or undecayed>.png</em></strong><em>. In particular, the available reference model options are Ra02, Pi16, Si18, LC18, Ri18, La22; the initial mass of the progenitors are 15, 20 or 25 (solar masses). The third part of the filenames are the plotted elements (in this case Ni or Fe) and then if they are decayed or undecayed. In this database we only consider the decayed species, which means that the radioactive isotopes whose decay can add to the abundance of the selected isotopes were considered. In this plots the x-axis represents the total mass from the core and the y-axis is the mass fraction on a logarithmic scale. For the slopes the same name scheme applies, but they are identified as <strong>slopes_<model reference>_<initial mass>_<element>_<decayed or undecayed></strong></em><strong>.png,</strong> and on the y-axis there are the slope values insteas of abundances.</p>
Linked collectors and determiners for: An Online Database of the Immatures of Coleoptera (Arthopoda, Insecta) Described from Brazil.
Natural history specimen data linked to collectors and determiners held within, "An Online Database of the Immatures of Coleoptera (Arthopoda, Insecta) Described from Brazil". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/8e0e9330-e1b2-475a-9891-4fa8e5c6f57f">https://bionomia.net/dataset/8e0e9330-e1b2-475a-9891-4fa8e5c6f57f</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/8e0e9330-e1b2-475a-9891-4fa8e5c6f57f">https://gbif.org/dataset/8e0e9330-e1b2-475a-9891-4fa8e5c6f57f</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Historical review, catalog of type specimens and online database of the ichthyology collection of the Instituto de Ciencias Naturales of the Universidad Nacional de Colombia (ICN-MHN).
Natural history specimen data linked to collectors and determiners held within, "Historical review, catalog of type specimens and online database of the ichthyology collection of the Instituto de Ciencias Naturales of the Universidad Nacional de Colombia (ICN-MHN)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/264fca2e-af6c-427c-8edd-853280f9b607">https://bionomia.net/dataset/264fca2e-af6c-427c-8edd-853280f9b607</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/264fca2e-af6c-427c-8edd-853280f9b607">https://gbif.org/dataset/264fca2e-af6c-427c-8edd-853280f9b607</a>. Formatted as a Frictionless Data package.
Tallo database with World Flora Online taxonomic matches, also including information on presence in the TreeGOER and GlobalUsefulNativeTrees databases
<p>The <strong>Tallo database</strong> (v 1.0.0) provides tree measurements for 5,163 tree species and 61,856 globally distributed sites. The database can be accessed via <a href="https://zenodo.org/record/6637599">https://zenodo.org/record/6637599</a> and has been fully described in Jucker <em>et al.</em> 2022. <strong>Tallo: A global tree allometry and crown architecture database</strong>. Global Change Biology, 28, 5254–5268. <a href="https://doi.org/10.1111/gcb.16302">https://doi.org/10.1111/gcb.16302</a>. Data provided in this archive show the taxonomic matches with <a href="https://www.worldfloraonline.org/">World Flora Online</a> (Borsch et al. <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">2020</a>) for two versions of its taxonomic backbone data set. The first version (<a href="https://www.worldfloraonline.org/downloadData">v. 2021.12</a>) was used also to standardize species names for the latest version of the <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">Agroforestry Species Switchboard</a> and during the compilation of the <strong>TreeGOER</strong> (<a href="https://zenodo.org/record/8052331">Tree Globally Observed Environmental Ranges</a>; Kindt <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">2023</a>) and <strong>GlobalUsefulNativeTrees</strong> (<a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobUNT</a>; Kindt <em>et al.</em> <a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) databases. The second version (<a href="https://www.worldfloraonline.org/downloadData">v. 2023.03</a>) was the most recent version available online. Taxonomic matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> R package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/10.1002/aps3.11388">2020</a>, see example scripts for a different taxonomic matching exercise <a href="https://rpubs.com/Roeland-KINDT/996500">here</a>).</p> <p>Taxonomic matching was achieved for all taxa listed in the Tallo database, except for <em>Lithocarpus orocola</em>.</p> <p>Presence of a taxon in the TreeGOER and GlobalUsefulNativeTrees databases has been flagged by showing the number of records used in TreeGOER to calculate ranges for environmental variable bio01 and by the number of native countries in GlobUNT, respectively.</p> <p>The development of this archive was supported by the Darwin Initiative to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, and by the Green Climate Fund through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project.</p>
Province of Cremona - Environment and Territory Department - Online digital library database
<p>The province of Cremona lies in Northern Italy, along the left bank of the River Po floodplain. This is the database of the online digital library of the Province Administration Environment and Territory Department. At present the library comprises 610 contributions concerning the environment, ecology, geography, history and landscape of the province, of the Po basin at large and of other areas as well. Most contributions have a short or extended abstract in English. Each publication in the library is freely downloadable as a PDF file from the library website http://bibliotecadigitale.provincia.cremona.it.</p> <p>The database fields are as follows: Publication code, Publication series, Publication title in Italian, Publication title in English, Publication type (magazine or monograph), ISSN number (if assigned), Issue number, Issue year, Contribution type (article, report or short note, monograph etc.), Title in Italian<em>,</em> Title in English, Topic, Subtopic 1, Subtopic 2, Pages, Author 1, Author 2, …, Author 16, Link to the file of each publication issue on the digital library website, Notes.</p> <p>Further information on the digital library and the database can be found in the open access article (in English) in V. 2 N. 1 (2022) of BORNH (Bullettin of Regional Natural History of the Società dei Naturalisti in Napoli): <a href="https://serena.sharepress.it/index.php/bornh/issue/view/653">https://serena.sharepress.it/index.php/bornh/issue/view/653</a></p> <p>Please note that upon opening the file with LibreOffice (and perhaps other softwares) it might be necessary to select Windows 1252 as the character type and the comma as the separator.</p>
Species numbers by country.pdf: a listing of total fish species numbers for locations compiled from http://www.fishbase.us online database.
<p>Species numbers by country.pdf: a listing of total fish species numbers for locations compiled from http://www.fishbase.us online database.</p> <p>data from Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the<br> Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p>
African wood density database with matches to the taxonomic backbone data sets of World Flora Online (version 2023.12) and the World Checklist of Vascular Plants (version 11)
<p>The <strong><span>African Wood Density Database </span></strong><span>provides air-dry wood density data for over 750 tree species grown in Africa.</span></p> <p>This archive provides taxonomic matches with recent versions of <strong>World Flora Online</strong> (WFO; <a href="../records/10425161">version 2023.12 downloaded from Zenodo</a>; Borch et al. <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">2020</a>) and the <strong>World Checklist of Vascular Plants</strong> (WCVP; <a href="https://sftp.kew.org/pub/data-repositories/WCVP/Archive/">version 11 downloaded from the Kew data depository</a>; Govaerts et al. <a href="https://doi.org/10.1038/s41597-021-00997-6">2021</a>). Matching was done via the <strong>WorldFlora</strong> package (<a href="https://cran.r-project.org/package=WorldFlora">version 1.14-3</a>; Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>), using similar scripts as documented in this Rpub: <a href="https://rpubs.com/Roeland-KINDT/1134151">https://rpubs.com/Roeland-KINDT/1134151</a>.</p> <p> </p> <ul> <li><span>Carsan, S. Orwa, C. Harwood, C. Kindt, R. Stroebel, A. Neufeldt, H. and Jamnadass, R. 2012. African Wood Density Database. World Agroforestry Centre, Nairobi. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">https://apps.worldagroforestry.org/treesnmarkets/wood/#</a> </span></li> <li><span>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., Güner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></span></li> <li><span>Govaerts, R., Nic Lughadha, E., Black, N. <em>et al.</em> The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. <em>Sci Data</em> <strong>8</strong>, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></span></li> <li><span>Kindt, R. 2020. WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data. <em>Applications in Plant Sciences</em> 8(9): e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></span></li> </ul> <p> </p> <p>Original funding for the database was provided <span>by the Carbon Benefits Project (CBP) supported by The Global Environment Facility (GEF). Development of the 2024 version </span>was supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by <strong>Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia</strong> to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project and through the <em>Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso</em>, by the <strong>Bezos Earth Fund</strong> to the <em>Bezos Quality Tree Seed for Africa in Kenya and Rwanda</em> project and by the <strong>German International Climate Initiative (IKI)</strong> to the regional tree seed programme on <em>The Right Tree for the Right Place for the Right Purpose in Africa</em>. When using <strong>African Wood Density database</strong> in your work, cite the 2012 version (Carsan et al. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">2012</a>) as well as this repository using the DOI.</p>
Search for huntingtin interactors in online databases – 2018/08/08
<p><strong>Project</strong> - Huntingtin structure-function open lab notebook. </p> <p><strong>Rationale</strong> - To identify different huntingtin interaction partners. </p> <p><strong>Overview</strong> - Different online databases which detail protein interaction partners were searched for huntingtin protein interaction partners. Data detailing huntingtin interaction partners from 9 different databases was extracted and simplified – worksheets 1-15. The information from each database was collated – worksheet 16. Huntingtin protein interaction partners were ranked according to the number of databases they were found in as well as the number of different experiments detailing the interaction with huntingtin – worksheet 17. </p>
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.