Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “Open Bibliometrics”
Corresponding spreadsheet to the Paper 'An intersectional approach to analyse gender productivity and open access: a bibliometric analysis of the Italian National Research Council' submitted to the Scientometric journal by Roberta Ruggieri, Fabrizio Pecoraro and Daniela Luzi from National Research Council, Italy.
<p>Gender equality and Open Access (OA) are priorities within the European Research Area (ERA) and cross-cutting issues in European research program H2020. Gender and openness are also key elements of Responsible Research and Innovation (RRI). However, despite the common underlying targets of fostering an inclusive, transparent and sustainable research environment, both issues are analysed as independent, unrelated topics.<br> This paper represents a first exploration of the inter-linkages between gender and OA analysing the scientific production of researchers of the Italian National Research Council under a gender perspective integrated with the different OA publications modes. A bibliometric analysis was carried out for articles published in the period 2016-2018 and retrieved from the Web of Science. Results are presented constantly analysing CNR scientific production in relation to gender, disciplinary fields and OA publication modes. These variables are also used when analysing articles that receive financial support.<br> Our results indicate that gender disparities in scientific production still persist in particularly in STEM disciplines (Science, Technology, Engineering and Mathematics), while in medical and agricultural sciences the gender gap is the closest to parity. A positive dynamic toward OA publishing and women scientific production is shown when open disciplines with well-established practices are related to articles supported by funds. A slightly higher women propensity toward OA is shown when considering Gold OA,OA or authorships with women in the first and last article by-line position. Moreover, the prevalence of Italian funded articles with women’s contributions published in Gold OA journals seems to confirm this tendency, especially if considering the week enforcement of the Italian OA policies.</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>
A bibliometric study on Parkinson's Disease based on the open access data of the Michael J. Fox Foundation
<h1>Description</h1> <p>This repository contains a comprehensive dataset focused on Parkinson's Disease. We provide data extracted via web scraping, along with metadata resulting from the extraction process using the NCBI API. The data pertains to the article titled 'A bibliometric study on Parkinson's Disease based on the open access data of the Michael J. Fox Foundation'.</p> <h2>Metadata Description</h2> <ul> <li> <h3>Analisys_MJFF_05_04_2024.xlsx</h3> </li> </ul> <table> <tbody> <tr> <th>Field</th> <th>Description</th> <th>Data Type</th> </tr> </tbody> <tbody> <tr> <td>AU</td> <td>List of authors in abbreviated format.</td> <td>Text</td> </tr> <tr> <td>AF</td> <td>List of authors with full names.</td> <td>Text</td> </tr> <tr> <td>TI</td> <td>Full title of the article.</td> <td>Text</td> </tr> <tr> <td>SO</td> <td>Name of the journal or publication.</td> <td>Text</td> </tr> <tr> <td>SO_CO</td> <td>Country of origin of the publication.</td> <td>Text</td> </tr> <tr> <td>LA</td> <td>Language of the article.</td> <td>Text</td> </tr> <tr> <td>DT</td> <td>Type of document, such as "Journal Article".</td> <td>Text</td> </tr> <tr> <td>DE</td> <td>Keywords or descriptors associated with the article.</td> <td>Text</td> </tr> <tr> <td>MESH</td> <td>MeSH terms that describe the content of the article.</td> <td>Text</td> </tr> <tr> <td>DI</td> <td>Digital Object Identifier (DOI).</td> <td>Text</td> </tr> <tr> <td>PG</td> <td>Number of pages or page range.</td> <td>Numeric</td> </tr> <tr> <td>GRANT_ID</td> <td>Identification of funding, when available.</td> <td>Text</td> </tr> <tr> <td>GRANT_ORG</td> <td>Organization that provided the funding.</td> <td>Text</td> </tr> <tr> <td>UT, PMID</td> <td>Unique identifiers of the article.</td> <td>Numeric</td> </tr> <tr> <td>DB</td> <td>Name of the database where the article is indexed.</td> <td>Text</td> </tr> <tr> <td>AU_UN</td> <td>Information about the academic unit or institution of the authors.</td> <td>Text</td> </tr> </tbody> </table> <ul> <li> <h3>References_MJFF_v2_Final_Corrected.csv</h3> </li> </ul> <table> <tbody> <tr> <th>Field</th> <th>Description</th> <th>Data Type</th> </tr> </tbody> <tbody> <tr> <td>Title</td> <td>Name of the article or publication.</td> <td>Text</td> </tr> <tr> <td>Authors</td> <td>List of authors who contributed to the article.</td> <td>Text</td> </tr> <tr> <td>Journal Name</td> <td>Name of the journal or periodical where the article was published.</td> <td>Text</td> </tr> <tr> <td>Publisher</td> <td>Name of the publisher who published the article.</td> <td>Text</td> </tr> <tr> <td>Volume</td> <td>Volume number of the journal in which the article appears.</td> <td>Numeric or Text</td> </tr> <tr> <td>Edition Number</td> <td>Number of the edition of the journal in which the article is found.</td> <td>Numeric or Text</td> </tr> <tr> <td>Starting Page</td> <td>Number of the first page of the article in the publication.</td> <td>Numeric</td> </tr> <tr> <td>Ending Page</td> <td>Number of the last page of the article.</td> <td>Numeric</td> </tr> <tr> <td>Publication Date</td> <td>Date on which the article was published.</td> <td>Date</td> </tr> <tr> <td>Open Access Status</td> <td>Indicates whether the article is available in open access.</td> <td>Text</td> </tr> <tr> <td>License</td> <td>Type of license under which the article was published.</td> <td>Text</td> </tr> <tr> <td>DOI (Digital Object Identifier)</td> <td>Unique identifier for the article that provides a permanent link to the online access.</td> <td>Text</td> </tr> <tr> <td>OA Location URL</td> <td>Direct URL to the article, if available in open access.</td> <td>Text</td> </tr> <tr> <td>Citation Count</td> <td>Number of times the article has been cited by other publications.</td> <td>Numeric</td> </tr> </tbody> </table> <p> </p>
Open and Reproducible Dataset of Bibliometric Indicators of Russia
<p>Version 1. Data collected on 03-04 November 2023.</p><p><i>by Ivan Sterligov, HSE University, </i><a href="mailto:ivan.sterligov@gmail.com"><i>ivan.sterligov@gmail.com</i></a></p><p>See readme.md for details</p><p>The dataset comes with python code that lets anyone collect and update all the data automatically, provided they set up a free access to Scopus API and conform to the rules of API usage set by Elsevier.</p><p>The dataset is a part of a broader academic project aimed at tracking dramatic changes in Russian publication output after 2022 and generally focuses on the period starting at 2018. This is an academic non-commercial research project and includes no Scopus metadata "as is", and no matadata on any particular paper, author or journal, only publication counts obtained using proprietary queries and journal lists constructed by its author. No citation metrics are used or published.</p><p>Dataset will be hopefully updated and new versions posted at Zotero. You can cite specific version DOI to be sure that you reference particular values. Also, the dataset as a whole has a common DOI which resolves to the newest version.</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.