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191 results for “Open Research”
GreenCharge Open Research Data
<p>These datasets are collected from the pilots in the H2020 GreenCharge project. The data format and content is described in the GreenCharge Deliverable D5.6 Open Research Data.</p>
Core bibliometric Covid19 and comparable research dataset and code for the study "From intent to impact: Investigating the effects of open sharing commitments"
<p>This document provides the underlying dataset for the bibliometric component for the 2022 study "From intent to impact: Investigating the effects of open sharing commitments" by Research Consulting and Science-Metrix.</p> <p>Before reproducing the study findings or re-using the underlying datasets for other purposes, please cautiously review their limitations in the study's technical annex and main report, available at: https://zenodo.org/communities/data-sharing-in-public-health-emergencies/ </p> <p>Particularly, note that there is an error rate in attribution of signatory status to journal publications and preprints; in their location within specific thematic disease-based areas; or computing of dimension such as identification of data availability statement sections; identification of data depisition mentions within data availability statement sections; or matching of preprints and journal publications.</p> <p>These error rates are expected and have been estimated, please consult the technical report for full details.</p> <p> </p> <p>Definition of data fields is provided is the table below:</p> <table> <tbody> <tr> <td>Column name </td> <td>Definition</td> </tr> <tr> <td>document_type</td> <td>preprint or journal publication</td> </tr> <tr> <td>doi</td> <td>digital object identifier</td> </tr> <tr> <td>arxiv_id</td> <td>arXiv preprint server's unique identifier for its preprints</td> </tr> <tr> <td>ssrn_id</td> <td>SSRN preprint server's unique identifier for its preprints. Note that some of these IDs are contained within the DOIs also assigned to some (but not all) SSRN preprints , in the form of "10.2139/ssrn." + 'ssrn_id'</td> </tr> <tr> <td>coalesce_id</td> <td>coalesce function applied to the DOI, arxiv_id and ssrn_id. Redundant for journal publications.</td> </tr> <tr> <td>preprint_server</td> <td>Preprint platform on which a preprint has been published, restricted to arXiv, bioRxiv, medRxiv and SSRN for this study.</td> </tr> <tr> <td>journal_title</td> <td>Publishing journal name in the case of a journal publication.</td> </tr> <tr> <td>year</td> <td>The set is restricted to 2020 and 2021 for Covid19 preprints and journal publications. HVRD journal publications restricted to 2018-2019. HVRD preprints were restricted to 2020-2021 instead, to compensate for the lac of year-normalization for preprints, and generally better control findings against the launch of medRxiv in 2019.</td> </tr> <tr> <td>publication_title</td> <td>Title of the individual journal publication or preprint, not that of the publishing journal or preprint server.</td> </tr> <tr> <td>authors</td> <td>First 100 researchers that appear as authors of a preprint or journal publication. These are not parsed and provided for qualitative validation or assessments rather than for further quantitative treatment.</td> </tr> <tr> <td>Covid19</td> <td>Journal publications or preprints are coded 1 if they has been identified as falling into this thematic area through our queries (see the technical annex), 0 otherwise</td> </tr> <tr> <td>HVRD</td> <td>Human viral respiratory disease, the thematic area considered to be the closest to Covid19. Journal publications or preprints are coded 1 if they has been identified as falling into this thematic area through our queries (see the technical annex), 0 otherwise</td> </tr> <tr> <td>Journal_sig</td> <td>Journal publications where the publishing journal and/or its publishing house are Joint Statement signatories. Coded as 1 if they are signatories, 0 if not signatory, null if status could not be determined due to insufficient metadata. Not that all preprint servers included in this study are Joint Statement signatories. This category was fully removed from the models for preprints, rather than all preprints being assigned automatic signatory status.</td> </tr> <tr> <td>RPO_sig</td> <td>Journal publications and preprints where at least one author is affiliated with at least one research performing organization that is a Joint Statement signatory. Coded as 1 ifor signatory, 0 if not signatory, null if status could not be determined due to insufficient metadata.</td> </tr> <tr> <td>Funder_sig</td> <td>Journal publications and preprints where at least one funder supporting the research is a Joint Statement signatory. Coded as 1 ifor signatory, 0 if not signatory, null if status could not be determined due to insufficient metadata. Although funding is attributed to researchers rather than publications, funding metadata is more readily available at the second level. This approach also captures the flexible usage of financial resources that researchers may make accross mulitple concurrently ongoing research projects.</td> </tr> <tr> <td>overton_norm</td> <td>Year and subfield-normalized binary score of whether the journal publications has been cited by one or more policy-related documents from the Overton database. Null scores for journal publications not covered by the database.</td> </tr> <tr> <td>overton</td> <td>Normalizations being unable for preprints, binary score of whether the preprint has been cited by one or more policy-ralated documents from the Overton database. Null scores for preprints not covered by the database.</td> </tr> <tr> <td>daswriting_binary</td> <td>Binary score capturing identification of a data availability statement in the journal publication or preprint using the queries presented in the technical annex. Null scores are for publications and preprints where records of full texts were unavailable for text mining, or were this analysis could not be performed due to licensing restrictions. </td> </tr> <tr> <td>deposition_binary</td> <td>Binary score capturing identification of a data availability statement and data deposition mention therein in the journal publication or preprint using the queries presented in the technical annex. Null scores are for publications and preprints where records of full texts were unavailable for text mining, or were this analysis could not be performed due to licensing restrictions. </td> </tr> <tr> <td>is_oa</td> <td>Binary score capturing OA or free-to-read (also so-calleod "bronze OA" and "green OA") status of journal publications. Unpaywall categories have been used in a mutually exclusive implementation, with the best (gold > hybrid>bronze>green) possible applicable category being retained. Null scores for journal publications not covered in our Unpaywall dataset. Scores of 0 denote journal publications not available under an OA or free-to-read category.</td> </tr> <tr> <td>is_gold</td> <td>as above</td> </tr> <tr> <td>is_hybrid</td> <td>as above</td> </tr> <tr> <td>is_bronze</td> <td>as above</td> </tr> <tr> <td>is_green</td> <td>as above</td> </tr> <tr> <td>matched_journal_binary</td> <td>For preprints, whether one or more matching journal publications could be identified using the queries identified in the technical, or preprint servers' own lists of preprint-journal publication matches. Null scores for preprints with insufficient metadata information to perform the matching operation.</td> </tr> <tr> <td>matched_journal_doi</td> <td>For those preprints with or more matching journal publications, the DOI(s) of the matching journal publication(s). Note that some of the maching journal publications identified do not have DOIs.</td> </tr> <tr> <td>matched_preprint_binary</td> <td>For journal publications, whether one or more matching preceding preprints could be identified using the queries identified in the technical annex, or preprint servers' own lists of preprint-journal publication matches. Null scores for journal publications without sufficient metadata to run the analysis.</td> </tr> <tr> <td>matched_preprint_id</td> <td>For those journal publications preceded with one or more arXiv, bioRxiv, medRxiv or SSRN preprints, the DOI(s), arXiv ID and/or SSRN ID of the matching preprint(s). </td> </tr> <tr> <td>hasdoi</td> <td>Only journal publications with DOIs were retained in the core quantitative analyses.</td> </tr> <tr> <td>hasacknowledgements</td> <td>Only journal publications with funding acknowledgements (to determine funding-based signatory status) were retained in the core quantitative analyses.</td> </tr> <tr> <td>funder_array</td> <td>Array (but cast as string) of names of the funders on the basis of whose idenitification signatory status has been attributed, where relevant. Null if non-signatory or unknown signatory status.</td> </tr> <tr> <td>RPO_array</td> <td>Array (but cast as string) of names of the research performing organizations on the basis of whose idenitification signatory status has been attributed, where relevant. Null if non-signatory or unknown signatory status.</td> </tr> <tr> <td>DAS_excerpt</td> <td>Journal publication or preprint text excerpt on which succesful identifcation of data availability statements and/or data deposition mentions have been made. Null both where the query could not be run at all, or where the query was negative.</td> </tr> <tr> <td>big5</td> <td>Journal publication published in a journal owned by one of the following five publishing houses: Elsevier, Sage, Springer Nature, Taylor-Francis, Wiley.</td> </tr> <tr> <td>LMIC</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a lower-middle income country as defined by the World Bank</td> </tr> <tr> <td>LIC</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a low income country as defined by the World Bank</td> </tr> <tr> <td>SouthNorth</td> <td>Journal publication whose authors include at least one researcher affiliated with at least one institution located in a upper-middle income country, a lower-middle income country, or a low income country as defined by the World Bank; as well as at least one researcher affiliated with at least one institution located in a high income country. For the purpose of this indicator, Sicnece-Metrix exceptionally includes China and Bulgaria in the list of high income countries.</td> </tr> <tr> <td>DID_allauthors_OR</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as EITHER holding journal-based signatory status OR funding-based signatory status, and where no filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_authorcontrol_OR</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as EITHER holding journal-based signatory status OR funding-based signatory status, and where a filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_authorcontrol_AND</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as holding journal-based signatory status AND funding-based signatory status, and where a filter has been applied to control for author-level biases.</td> </tr> <tr> <td>DID_allauthors_AND</td> <td>Journal publication is included in the difference-in-difference model defining signatory publication as holding journal-based signatory status AND funding-based signatory status, and where no filter has been applied to control for author-level biases.</td> </tr> <tr> <td>Preprint_authorcontrol</td> <td>Preprint is included in the the analytical breakdowns where a filter has been applied to control for author-level biases. Note that authors have been kept constant in preprints on the basis of their belonging to all analytical breakdowns in journal publications rather than in preprint-based groups.</td> </tr> </tbody> </table> <p> </p>
PLOS ONE – a case study of citation analysis of research papers based on the data in an open citation index (The OpenCitations Corpus)
<p>This is a dataset used in and produced by research described in article "PLOS ONE - a case study of citation analysis of research papers based on the data in an open citation index (The OpenCitations Corpus)" that is translation of the original Polish text "PLOS ONE – studium przypadku analizy cytowań prac naukowych na podstawie danych otwartego indeksu cytowań (OpenCitations Corpus)" published by EBiB bulletin (2017, No 176).</p> <p>Data were extracted, as nodes (PLOS_cited_nodes.csv) and edges (PLOS_edges.csv) files from the OpenCitations Corpus (http://opencitations.net/download) on 2017.07.25 and describe all cited papers published by PLOS ONE (nodes), and all citing relations (edges). The research was conducted using Gephi (https://gephi.org/) platform so the same source data are also avaiable as GEXF file (for "one-click" import capabilities). In addition, the same data are published in NET format (but be warned that due to this format limitations, information about the publication year of papers has been lost) used by PAJEK platform, as it is very popular tool for analysis of network data.</p> <p>Published figures have prefix names corresponding to figures captions in the original paper, where they have been thoroughly discussed. This data set contains also the additional figure not published in the article, showing most cited paper with citing chains of articles of lenght not greater than 3.<br> These pictures have much better quality than those published in the article, which allows for "drill down"/zoom-in analysis and large format printing.</p>
washopenresearch: Dataset about open research data information in Water, Sanitation, and Hygiene
The goal of washopenresearch is to provide an overview of open research data related to Water Sanitation and Hygiene (WASH). The package provides access to two datasets `washdev` and `uncnewsletter`. Each dataset collects information on scientific articles about (1) article metadata (e.g. title, first author, correspondence author), (2) supplementary material information, (3) data availability statement, and (4) semantic information (e.g. keywords).
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C). in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica
Рис. 3. Фотографии Laternula elliptica, сделанные около cтанции «Прогресс», ВосточнаЯ Антарктида. L. elliptica на морском дне с медкими камнЯми или гравием, глубина 27 м (А); несколько сифональных отверстий L. elliptica над поверхностью мЯгких осадков вокруг голотурии Staurocucumis turqueti, глубина 27 м (В); раковина L. elliptica (длина около 110 мм) на снегу около майны сраЗу после иЗвлечениЯ иЗ воды (С); пустые раковины L. elliptica на морском дне, глубина 56 м (D); раковина L. elliptica (вид с дорсального краЯ) на мЯгких осадках с камнЯми, покрытыми иЗвестковыми водорослЯми, глубина 30 м (Е); пара сифональных отверстий L. elliptica на поверхности мЯгких осадков, глубина 27 м (F). Фотографии О. Савинкина (A, B, D–F) и В. Потина (С). Fig. 3. Photographs of Laternula elliptica taken near «Progress» Research Station (East Antarctica). Softshelled clam L. elliptica on sea bottom with small stowns or gravel, depth 27 m (A); several open siphons of L. elliptica above soft bottom sediments around holothurian Staurocucumis turqueti, depth 27 m (B); a shell of L. elliptica (length about 110 mm) on snow near a dive hole just after dragging out of water (C); empty shells of L. elliptica on seafloor, depth 56 m (D); a shell of Laternula elliptica (dorsal view) on soft deposits among stones, covering by Lithothamnion, depth 30 m (E); pair of siphonal opening of L. elliptica on surface of soft sediments, depth 27 m (F). Photographs are taken by O. Savinkin (A, B, D–F) and V. Potin (C).
Open Research Data in Medicine - Polish scientists' attitudes towards data sharing
<p>The survey on the attitudes and beliefs of research staff has been carried out at selected Polish medical universities. The purpose of the questionnaire was to collect respondents' opinions on opening research data created during their scientific work. The research was aimed at preparing the necessary educational, technical and legal support for scientists after launching the Polish Medical Platform, when Polish scientists will be asked to deposit their data in local repositories.</p>
Data underlying the research paper "Articulating Social Issues with Open Data: Exploring a Game Jam Approach"
<p>Contains research data underlying the following research paper:</p> <blockquote> <p>Davide Di Staso, Lærke Christiansen, Fernando Kleiman, and Marijn Janssen. 2024. Articulating Social Issues with Open Data: Exploring a Game Jam Approach. In Proceedings of the 8th International Conference on Game Jams, Hackathons and Game Creation Events (ICGJ ’24), October 11, 2024, Copenhagen, Denmark. ACM, New York, NY, USA, 7 pages. https://doi.org/10.1145/3697789.3697798</p> </blockquote> <p>The authors acknowledge the financial support from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 955569, "Towards a sustainable Open Data ECOsystem" (ODECO).</p>
Description of the Features of the Open Research Knowledge Graph as a Crowdsourcing Platform based on the 4 Pillars of Crowdsourcing
<p>This dataset provides the description of the features of the <a href="https://www.orkg.org/orkg/">Open Research Knowledge Graph</a> (ORKG) based on the 4 pillars of crowdsourcing according to the reference model for crowdsourcing by Hosseini et al. [1]. This overview represents the features of the current implementation status of ORKG as a crowdsourcing platform.</p> <p>[1] M. Hosseini, K. Phalp, J. Taylor, and R. Ali, "<a href="https://ieeexplore.ieee.org/abstract/document/6861072?casa_token=zWTHNBHeH6kAAAAA:1n3EJjajqgSkSk154g4DlNFAmJs_7o3KY7LnobvP_W7AUIr-FvM5OyGP1FaRn68zUX-2oYHh7A">The Four Pillars of Crowdsourcing: A Reference Model</a>", in 2014 IEEE 8th International Conference on Research Challenges in Information Science (RCIS). IEEE, 2014, pp. 1–12.</p>
Monitoring open access publishing of NWO funded research (data)
<p>This is the dataset underlying the report "Monitoring open access publishing of NWO funded research" (https://doi.org/10.5281/zenodo.5055609). </p> <p>The report presents statistics on the extent to which publications from the period 2015–2020 funded by NWO are available in Open Access . The analyses presented in this report also cover publications funded by the Netherlands Organisation for Health Research and Development ZonMw.</p> <p>This report builds on an <a href="https://doi.org/10.5281/zenodo.4446042">earlier report</a> published in 2020 covering publications from the period 2015–2018.</p> <p> </p>
Research Compendium for Harrington et al. (2021): "An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b"
<p>This archive is the Reproducible Research Compendium for<br> <br> An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b<br> <br> by Harrington et al. (2021), published in The Planetary Science Journal.<br> <br> BART is an atmospheric parameter retrieval code. It infers the properties of planetary atmospheres from spectroscopic observations. The compendium includes all the software, documentation, configuration files, plots, and data published in the paper. The compendium is under the Reproducible Research Software License; see LICENSE file. The README provides additional information and describes the contents of each compressed .tar.gz file.</p>
Data and Code for "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility"
<p>This snapshot contains code and data for the preprint "Value dissonance in research(er) assessment: Individual and institutional priorities in review, promotion and tenure criteria related to research quality, quantity, openness and responsibility".</p> <p>Instructions on re-using the data and running the code can be found in the README.md.</p> <p>Changes:</p> <ul> <li>Added survey instrument and informed consent.</li> </ul>
The LOTUS Initiative for Open Natural Products Research: wikidata query results
<p>Wikidata query results returned by the downloadLotus module of the <a href="https://github.com/lotusnprod/lotus-wikidata-interact">https://github.com/lotusnprod/lotus-wikidata-interact</a> program.</p> <p>See details of the module here <a href="https://github.com/lotusnprod/lotus-wikidata-interact/blob/main/downloadLotus/README.md">https://github.com/lotusnprod/lotus-wikidata-interact/blob/main/downloadLotus/README.md</a></p> <p>This dataset is constituted of 4 tables.</p> <ol> <li>compounds.tsv - chemical structures metadata (wikidataId, canonicalSmiles, isomericSmiles, inchi, inchiKey)</li> <li>references.tsv - bibliographical references metadata (wikidataId, pipe separated DOIs, titles)</li> <li>taxa.tsv - biological organisms metadata (wikidataId, pipe separated names, taxa rank)</li> <li>compound_reference_taxon.tsv - the documented structure-organism pairs</li> </ol> <p>This dataset includes not only the outputs of the LOTUS processing pipeline (available here <a href="https://doi.org/10.5281/zenodo.5665295">https://doi.org/10.5281/zenodo.5665295</a> ) but also any of wikidata chemical compounds having the found in taxon property (<a href="https://www.wikidata.org/wiki/Property:P703">https://www.wikidata.org/wiki/Property:P703</a>) and their associated organisms and documenting references.</p> <p> </p> <p><br> </p>
The LOTUS Initiative for Open Natural Products Research: frozen dataset
<p>Dataset used in the frame of the LOTUS Initiative: <a href="https://doi.org/10.7554/eLife.70780">https://doi.org/10.7554/eLife.70780</a></p>
A phenotyping weeds image dataset for open scientific research
<p>This in-house-built image dataset consists of 10810 weed images captured through a dedicated phenotyping activity in quasi-field conditions. The targets are seven of the most widespread and hard-to-control weeds in wheat (but also in other winter cereals) in the Mediterranean environment.</p> <p>In the framework of open scientific research, our aim is to share low-cost and high-resolution images representing challenging agricultural environments where weather, lighting and other factors can change by the hour and affect the quality of images. This way the dataset could be used to train Artificial Intelligence architectures designed for weed recognition, allowing the implementation of tools directly available in the field for farmers and technicians for effective and timely weed management.</p> <p>The dataset encompasses weed images ranging from the post-emergence phase (i.e. the complete cotyledons unfolding) until the pre-flowering stage. The weed selection was made by considering (i) bottom-up information and specific requests by farmers and technicians, (ii) weed susceptibility to commercial formulations for chemical control <50%, reported at least twice by field technicians, (iii) the difficulty of control considering any methods, and (iv) the type of growing season (overlapping or not with wheat). The final weeds selection encompassed both monocots (<em>Avena sterilis</em> and <em>Lolium multiflorum</em>) and dicots (<em>Convolvulus arvensis</em>, <em>Fumaria officinalis</em>, <em>Papaver rhoeas</em>, <em>Veronica persica</em> and <em>Vicia sativa</em>).</p> <p>Image acquisition was facilitated by using a white panel as a background; this helped to (i) spread the light and thereby make the plants well-illuminated, while still avoiding strong shadows when using the flash and (ii) simplify image processing. The images were acquired with a Canon EOS 700D hand-held camera set in the macro mode with aperture, shutter speed, ISO and flash in auto mode. Photo capture timing, target distances and light conditions did not have a fixed pattern but were deliberately programmed to vary in such a way as to mimic field conditions. For image shooting at various times of the day, the only precaution was to frame the subject with homogeneous light conditions (full sunlight/full shade). The varied outdoor conditions (light, distance, timing) and camera type (RGB) with auto mode were essential features to make the images photos look similar to those that a user can take in a field, for example with a smartphone camera.</p> <p>After selection and categorization, images were cropped to select the region of interest following the 1:1 ratio but maintaining a minimum size of 512 x 512 pixels.</p> <p> </p> <p>More details on the dataset and its use for weed recognition tasks will be soon available in the proceedings of the forthcoming ECPA conference (2-6 July 2023, Bologna, Italy).</p>
Using Open Citation Databases for Snowballing in Software Engineering Research
<p>Dataset for our study on the coverage of software engineering articles in open citation databases:</p> <ul> <li>a list of the 23 sampled venues with their respective CORE ranks and publishers, <ul> <li>01-venues.csv,</li> </ul> </li> <li>a list of the 204 sampled articles with their respective number of references/citations per citation database, <ul> <li>02-articles.csv (articles with publication information),</li> <li>03-references-absolute.csv (number of references in published PDF & absolute numbers for reference coverage in databases),</li> <li>04-references-relative.csv (relative numbers for reference coverage in databases),</li> <li>05-citations-absolute.csv (absolute numbers for citation coverage in databases),</li> <li>06-citations relative.csv (relative numbers for citation coverage in databases),</li> </ul> </li> <li>a list of the 8 articles analyzed in more detail with complete references data from the citation databases, <ul> <li>07-selected-articles.csv (articles with publication information),</li> <li>08A–08H (comparison of references found in databases for each article),</li> </ul> </li> <li>and additional statistical measures and plots <ul> <li>09-Statistics.{pdf,xlsx} (statistical measures – i.e., minimum, maximum, median, average, variance – for the whole dataset and for subsets by publisher, CORE rank, or year of publication),</li> <li>10-Figures.zip (figures for references as shown in the study and additional figures for citations – each in EPS and PNG format).</li> </ul> </li> </ul>
Figures for RAE Editorial 'What Teachers and Researchers in the Area of Business Management Need to Know About Open Science'
<pre>This set of figures is related to an Editorial dedicated to Open Science, published by <a href="https://bibliotecadigital.fgv.br/ojs/index.php/rae/index">Revista de Administração de Empresas (RAE)</a>: </pre>
Open Science Policies as Regarded by the Communities of Researchers from the Basic Sciences in the Scientific Periphery: Major themes, subthemes and selected interview quotes
<p>Data annex containing major themes, subthemes and selected interview quotes of the article Open Science Policies as Regarded by the Communities of Researchers from the Basic Sciences in the Scientific Periphery.</p>
The value framework of open research data_Appendix-v3
<p>The supplementary data and the final version of the questionnaire "<strong>Survey on the 'Value of Open Research Data'".</strong></p>
Buprenorphine Pharmacometric Open Label Research Study of Drug Exposure
ClinicalTrials.gov study NCT03608696. IPD Sharing: YES. Countries: 1. Publications: 1.
SOils DAta Harmonization database (SoDaH): an open-source synthesis of soil data from research networks
This SOils DAta Harmonization (SoDaH) database is designed to bring together soil carbon data from diverse research networks into a harmonized dataset that can be used for synthesis activities and model development. The research network sources for SoDaH span different biomes and climates, encompass multiple ecosystem types, and have collected data across a range of spatial, temporal, and depth gradients. The rich data sets assembled in SoDaH consist of observations from monitoring efforts and long-term ecological experiments. The SoDaH database also incorporates related environmental covariate data pertaining to climate, vegetation, soil chemistry, and soil physical properties. The data are harmonized and aggregated using open-source code that enables a scripted, repeatable approach for soil data synthesis.
ScienceDex guides
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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.