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.
8
datasets available to search
ShareScore release 0.9.0
Dataset results
8 results for “software citation”
Checklists for Software Citation: what you need to know
<p>The FORCE11 Software Citation Implementation working group has been developing practical guidance in the form of checklists, which are aimed at authors, reviewers, developers, editors and publishers. The checklists help these audiences to implement software citation principles in their workflows. This talk will give a quick introduction to these checklists and explain how they can be used to improve the practice of open research by giving credit for software.</p>
Citations to software and data in Zenodo via open sources
<p>In January 2019, the Asclepias Broker harvested citation links to Zenodo objects from three discovery systems: the NASA Astrophysics Datasystem (ADS), Crossref Event Data and Europe PMC. Each row of our dataset represents one unique link between a citing publication and a Zenodo DOI. Both endpoints are described by basic metadata. The second dataset contains usage metrics for every cited Zenodo DOI of our data sample. </p> <p> </p>
Zenodo data and software citation links captured by the Asclepias Broker
<p>The dataset was retrieved from the Asclepias Broker early January 2019 after having performed a full harvesting and deduplication cycle from a clean database with zero citation links.</p> <p>The dataset contains citation links from three discovery systems: the NASA Astrophysics Datasystem (ADS), Crossref Event Data and Europe PMC. Only citation links with a target DOI in the DOI prefix 10.5281 (Zenodo’s DOI prefix) were kept.</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>
Don't mention it: challenges to using software mentions to investigate citation and discoverability - Data and Notebooks
<p>This deposit contains the data and Jupyter notebooks used for sampling and annotation analysis of our submission to the PeerJ Computer Science special issue <em>Software Citation, Indexing, and Discoverability </em>(<a href="https://peerj.com/collections/84-software">https://peerj.com/collections/84-software</a>):</p> <blockquote> <p>Stephan Druskat, Neil P. Chue Hong, Sammie Buzzard, Olexandr Konovalov, and Patrick Kornek. Don’t mention it: challenges to using software mentions to investigate citation and discoverability.</p> </blockquote> <p>See the README in this deposit.</p> <p>The contents of this deposit can also be browsed at <a href="https://github.com/softwaresaved/habeas-corpus/tree/main/replication-package">https://github.com/softwaresaved/habeas-corpus/tree/main/replication-package</a>.</p>
Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software and Other Digital Artifacts
<p><strong>The Research Resource Identifier was introduced in biomedicine in 2014 to more precisely identify the reagents and tools used in published biomedical research and to track use of tools across the breadth of the biomedical literature. The current RRID specification covers key biological and digital resources. Authors are instructed to include an RRID after the first mention of any resource used. RRIDs are designed to be easy to find using a full text search search engine. </strong></p> <p><strong>The published data sets were used in our comparative study where comparing the output of our RRID curation workflow with the outputs of automated text mining systems that have been used to identify mentions of resources in the text of publications. All files in tab-separated format (tsv). </strong></p> <p><strong>Scibot.tsv: Records of the RRID curation workflow using SciBot. </strong></p> <p>Each record shows that a resource RRID was identified in paper PMID with curator tags (Tag1, Tag2, both optional)</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p> Tag1: Curator tags (optional)</p> <p> Tag2: Additional curator tags (optional)</p> <p><strong>rdwsorted.tsv: Records of the output from RDW, a text mining software. </strong></p> <p>RDW identifies mentions of research resources in papers. Each record shows that a resource RRID was identified in paper PMID.</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p><strong>rridbyrdw05282019.tsv: Records of the output of the RRID-by-RDW in RDW. </strong></p> <p>RRID-by-RDW is a component in RDW that identifies mentions of research resources in papers by matching patterns of RRID specifications. Each record shows that a resource RRID was identified in paper PMID.</p> <p><strong> </strong>PMID: Pubmed ID</p> <p> RRID: Research Resource Identifier</p> <p> Context: Snippet where the RRID was found</p> <p><strong>resource_metadata20190418.tsv: Metadata of RRIDs</strong></p> <p>This file contains metadata of resources and their RRIDs. See file header for column definitions.</p> <p><strong>RRIDCUR-definitions.tsv: Definitions of curator tags used in Scibot.tsv.</strong></p> <p><strong> </strong>tag: Tag name</p> <p> definition: Definition of the tag</p>
Quality and Trackability of Author Indicated Software Citations (NEST Case Study)
<p>This dataset contains a randomly selected minimal sample of 471 NEST software citations, which were provided by authors and published on the NEST software page as a publication list. The software citations were analyzed on their quality and trackability.</p> <p>The data was collected in 2020 for a PhD thesis on research data and software (re)use indications in scholarly works.</p>
Software Citation workshop panel session voting data
<p>This data was captured from an interactive panel discussion session at the Software Citation workshop at the British Library on Monday 13 June. The audience were asked to vote on a series of questions via <a href="https://mentimeter.com/">Mentimeter</a>, with the panel (and audience members) then discussing the results. Mentimeter allows export of raw voting data, so we are making this available to supplement the workshop outputs.</p> <p>There are two files:</p> <ul> <li><code>Software Citation Workshop Panel.pdf</code> is the slides presented at the workshop, which gives the questions used.</li> <li><code>Software-Citation-Workshop-Panel-Cleaned.xlsx</code> includes the (anonymous) raw data (with test data removed) and simple visualisations of the results.</li> </ul> <p>The format of the spreadsheet is <a href="https://help.mentimeter.com/after-the-presentation/export-results-to-excel">described on the Mentimeter help site</a> (<a href="https://web.archive.org/web/20181010033759/https://help.mentimeter.com/after-the-presentation/export-results-to-excel">archived version on the Internet Archive</a>).</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.