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15 results for “open citations”
Dataset related to the manuscript: "An open-source integrated framework for the automation of citation collection and screening in systematic reviews"
<p>Dataset related to the manuscript: “An open-source integrated framework for the automation of citation collection and screening in systematic reviews”, to be used together with the code stored at https://github.com/AD-Papers-Material/BART_SystReviewClassifier to reproduce the results.</p> <p>There are three datasets:<br> - The Record data collected from the online scientific databases;<br> - The session journal which describes the search session, i.e., how many records were collected and from which source, for each query/session pairs.<br> - The session data which is the outcome of the classification and review tasks;</p>
Types, open citations, closed citations, publishers, and participation reports of Crossref entities
<p>This publication contains several datasets that have been used in the paper "Crowdsourcing open citations with CROCI – An analysis of the current status of open citations, and a proposal" submitted to the <a href="https://www.issi2019.org/">17th International Conference on Scientometrics and Bibliometrics (ISSI 2019)</a>, available at <a href="https://opencitations.wordpress.com/2019/02/07/crowdsourcing-open-citations-with-croci/">https://opencitations.wordpress.com/2019/02/07/crowdsourcing-open-citations-with-croci/</a>.</p> <p>Additional information about the analyses described in the paper, including the code and the data we have used to compute all the figures, is available as a Jupyter notebook at <a href="https://github.com/sosgang/pushing-open-citations-issi2019/blob/master/script/croci_nb.ipynb">https://github.com/sosgang/pushing-open-citations-issi2019/blob/master/script/croci_nb.ipynb</a>. The datasets contain the following information.</p> <p><strong>non_open.zip:</strong> it is a zipped (~5 GB unzipped) CSV file containing the numbers of open citations and closed citations received by the entities in the Crossref dump used in our computation, dated October 2018. All the entity types retrieved from Crossref were aligned to one of following five categories: journal, book, proceedings, dataset, other. The open CC0 citation data we used came from the CSV dump of <a href="https://doi.org/10.6084/m9.figshare.6741422.v3">most recent release of COCI dated 12 November 2018</a>. The number of closed citations was calculated by subtracting the number of open citations to each entity available within COCI from the value “is-referenced-by-count” available in the Crossref metadata for that particular cited entity, which reports all the DOI-to-DOI citation links that point to the cited entity from within the whole Crossref database (including those present in the Crossref ‘closed’ dataset).</p> <p>The columns of the CSV file are the following ones:</p> <ul> <li><em>doi:</em> the DOI of the publication in Crossref;</li> <li><em>type:</em> the type of the publication as indicated in Crossref;</li> <li><em>cited_by:</em> the number of open citations received by the publication according to COCI;</li> <li><em>non_open:</em> the number of closed citations received by the publication according to Crossref + COCI.</li> </ul> <p><strong>croci_types.csv:</strong> it is a CSV file that contains the numbers of open citations and closed citations received by the entities in the Crossref dump used in our computation, as collected in the previous CSV file, alligned in five classes depening on the entity types retrieved from Crossref: <em>journal</em> (Crossref types: journal-article, journal-issue, journal-volume, journal), <em>book</em> (Crossref types: book, book-chapter, book-section, monograph, book track, book-part, book-set, reference-book, dissertation, book series, edited book), <em>proceedings</em> (Crossref types: proceedings-article, proceedings, proceedings-series), <em>dataset</em> (Crossref types: dataset), <em>other</em> (Crossref types: other, report, peer review, reference-entry, component, report-series, standard, posted-content, standard-series).</p> <p>The columns of the CSV file are the following ones:</p> <ul> <li><em>type:</em> the type publication between "journal", "book", "proceedings", "dataset", "other";</li> <li><em>label:</em> the label assigned to the type for visualisation purposes;</li> <li><em>coci_open_cit</em>: the number of open citations received by the publication type according to COCI;</li> <li><em>crossref_close_cit:</em> the number of closed citations received by the publication according to Crossref + COCI.</li> </ul> <p><strong>publishers_cits.csv:</strong> it is a CSV file that contains the top twenty publishers that received the greatest number of open citations. The columns of the CSV file are the following ones:</p> <ul> <li><em>publisher</em>: the name of the publisher;</li> <li><em>doi_prefix</em>: the list of DOI prefixes used assigned by the publisher;</li> <li><em>coci_open_cit</em>: the number of open citations received by the publications of the publisher according to COCI;</li> <li><em>crossref_close_cit</em>: the number of closed citations received by the publications of the publishers according to Crossref + COCI;</li> <li><em>total_cit</em>: the total number of citations received by the publications of the publisher (= <em>coci_open_cit</em> + <em>crossref_close_cit</em>).</li> </ul> <p><strong>20publishers_cr.csv: </strong>it is a CSV file that contains the numbers of the contributions to open citations made by the twenty publishers introduced in the previous CSV file as of 24 January 2018, according to the data available through the Crossref API. The counts listed in this file refers to the number of publications for which each publisher has submitted metadata to Crossref that include the publication’s reference list. The categories 'closed', 'limited' and 'open' refer to publications for which the reference lists are not visible to anyone outside the Crossref Cited-by membership, are visible only to them and to Crossref Metadata Plus members, or are visible to all, respectively. In addition, the file also record the total number of publications for which the publisher has submitted metadata to Crossref, whether or not those metadata include the reference lists of those publications.</p> <p>The columns of the CSV file are the following ones:</p> <ul> <li><em>publisher: </em>the name of the publisher;</li> <li><em>open: </em>the number of publications in Crossref with an 'open' visibility for their reference lists;</li> <li><em>limited: </em>the number of publications in Crossref with an 'limited' visibility for their reference lists;</li> <li><em>closed: </em>the number of publications in Crossref with an 'closed' visibility for their reference lists;</li> <li><em>overall_deposited:</em> the overall number of publications for which the publisher has submitted metadata to Crossref.</li> </ul>
[review paper] Sustaining the 'Frozen Footprints' of Scholarly Communication through Open Citations_Dataset
<p>This dataset belongs to the review titled <em>Sustaining the ‘Frozen Footprints’ of Scholarly Communication through Open Citations</em>. The review explores the developments in the open citations movement, the OpenCitations infrastructure, and the Initiative for Open Citations (I4OC), providing a comprehensive overview of key milestones and initiatives.</p> <p>The dataset includes bibliographic and citation data for 174 scholarly outputs and 149 blogposts analyzed in the review. These outputs were drawn from a range of sources, including journal articles, conference proceedings, and other scholarly materials. The data has been curated to adhere to open citation principles, ensuring it is structured, separable, and openly accessible. It is provided in accordance with the licenses and terms of use of the original databases.</p> <p>Researchers, practitioners, and policymakers can use this dataset to explore the evolution of open citations and to further their understanding of the connections between scholarly works in the field of open research.</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>
Data for "Open Access impact on citations: a case study"
<p>This dataset is a list of 347 papers published in 2010 and retrieved from the Web of Science, Scopus and Google Scholar. For each paper, the number of citations and the citation date(s) have been collected. If the full-text is available online, the date of "liberation" and the URL of the file have been retrieved as well. The objective was to assess the impact of Open access on citation rate and more particularly the impact before and after full-text "liberation".</p> <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>
Open access in Africa: scopus citation data
<p>The following citation dataset was retrieved from Scopus in June 24, 2017 (3am, Western Indonesian time).</p> <p>It consists of 3 sets of data based on our searches. Each search was saved both in 'csv' and 'bib':</p> <ol> <li>OA_Africa_inTitle.xxx: "Open Access" AND Africa IN TITLE</li> <li>OA_Africa_inTitle_inAbstract_inKeywords.xxx: "Open Access" AND Africa IN TITLE, IN ABSTRACT, IN KEYWORDS</li> <li>OAmovement_Africa_inTitle_inAbstract_inKeywords.xxx: "Open Access movement" AND Africa IN TITLE, IN ABSTRACT, IN KEYWORDS</li> </ol> <p>The access to Scopus was provided by The Central Library of Institut Teknologi Bandung (Indonesia)</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>
Coronavirus Open Citations Dataset
<p>The Coronavirus Open Citations Dataset curated by OpenCitations currently contains (as of 16 May 2020) information about 189,697 citations and about the 49,719 citing or cited articles involved in these citations. A subset of these data (stored in the "_partial.json" files introduced below) is used for creating the visualization available at <a href="https://opencitations.github.io/coronavirus/">https://opencitations.github.io/coronavirus/</a>.</p> <p>Each item in both the JSON files storing citations ('citations_full.json' and 'citations_partial.json') contains the following fields:</p> <ul> <li>"id", a numeric identifier of the citation;</li> <li>"source", the citing entity;</li> <li>"target", the cited entity.</li> </ul> <p>Each item in both the JSON files storing article metadata ('metadata_full.json' and 'metadata_partial.json') contains the following fields:</p> <ul> <li>"id", the DOI of the article;</li> <li>"author", the surname of all the authors of the article;</li> <li>"year", the year of publication;</li> <li>"title", the title of the article;</li> <li>"source_title", the title of the venue where the article has been published.</li> </ul> <p>In addition, any item in the file 'metadata_partial.json' contains another field:</p> <ul> <li>"count": the overall number of citations that the article received.</li> </ul>
Crossref open citations
<p>This text file contains citations between documents classified as journal article, book content, conference paper, or preprint in Crossref. Each line in the file contains the DOI of a citing document followed by the DOI of a cited document. There are 147,161,531 documents classified as journal article, book content, conference paper, or preprint in Crossref. There are 1,723,702,594 citations between these documents in Crossref. The data has been extracted from Crossref’s XML Metadata Plus Snapshot downloaded on February 10, 2025.</p>
Current and future sources of open citations
<p>Video recording of the presentation done in the context of the Austrian DataCite Consortium on 19 November 2021. The video finishes after the last question.</p>
Inputs and results of "A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s case"
<p>This repository contains the datasets and visualizations generated in our work: <strong>"A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.’s case"</strong>.</p> <p><strong>Note:</strong> the data are all contained inside the <strong><em>data.zip</em> </strong>file. You need to unzip the container to get access to all the files and directories listed below.</p> <p>The data (citations) gathered accompanied by their annotated characteristics are stored in <strong><em>data/</em>:</strong></p> <ul> <li><em><strong>"cits_features.csv": </strong></em>a dataset containing all the entities (rows in the CSV) which have cited the Wakefield et al. retracted article, and a set of features characterizing each citing entity (columns in the CSV). The features included are: DOI ("doi"), year of publication ("year"), the title ("title"), the venue identifier ("source_id"), the title of the venue ("source_title"), yes/no value in case the entity is retracted as well ("retracted"), the subject area ("area"), the subject category ("category"), the sections of the in-text citations ("intext_citation.section"), the value of the reference pointer ("intext_citation.pointer"), the in-text citation function ("intext_citation.intent"), the in-text citation perceived sentiment ("intext_citation.sentiment"), and a yes/no value to denote whether the in-text citation context mentions the retraction of the cited entity ("intext_citation.section.ret_mention").<br> <strong>Note: </strong>this dataset is licensed under a <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons public domain dedication (CC0)</a>.</li> <li><em><strong>"cits_text.csv": </strong>this dataset stores the abstract ("abstract") and the in-text citations context ("intext_citation.context") </em>for each citing entity identified using the DOI value ("doi").<br> <strong>Note: </strong>the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.</li> </ul> <p><strong>Topic modeling</strong></p> <p>We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the <em><strong>topic_modeling/</strong></em> directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The topic modeling results for each textual feature are separated into two different folders, <em><strong>abstract/</strong></em> for the abstracts, and <em><strong>intext_cit/</strong></em> for the in-text citation contexts. Both the directories contain the datasets and visualizations generated using MITAO. </p> <p> </p> <p><strong>References</strong></p> <p>[1] Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. <a href="https://doi.org/10.19245/25.05.pij.5.2.3">https://doi.org/10.19245/25.05.pij.5.2.3</a></p>
unarXive: All arXiv Publications Pre-Processed for NLP, Including Structured Full-Text and Citation Network (open subset)
<h2><strong>Description</strong></h2><p>unarXive is a scholarly data set containing publications' structured full-text, annotated in-text citations, linked non-text content (mathematical notation, figure/table captions) and a citation network.</p><p>The data is generated from all LaTeX sources on <a href="https://arxiv.org/">arXiv</a> and therefore of higher quality than data generated from PDF files.</p><p>Typical uses are</p><ul><li>Training of ML models (citation recommendation, summarization, LLMs)</li><li>Citation context analysis</li><li>Bibliographic analyses</li></ul><h2><strong>Access</strong></h2><p>┏━━━━━━━━━━━━━━━━━━━━━━━━━━┓<br>┃ <a href="https://github.com/IllDepence/unarXive/raw/master/doc/unarXive_data_sample.tar.gz"><strong>D O W N L O A D S A M P L E</strong></a> ┃<br>┗━━━━━━━━━━━━━━━━━━━━━━━━━━┛</p><p>Regarding the full data set, please note the following:</p><blockquote><p><strong>Note</strong>: this Zenodo record is the "open subset" of unarXive, which contains all permissively licensed papers from arXiv.org. You can find the <a href="https://doi.org/10.5281/zenodo.7752754">full version here</a>.</p></blockquote><p>The code used for generating the data set is <a href="https://github.com/IllDepence/unarXive">publicly available</a>.</p>
Open citations involving Computer Science publications listed in DBLP
<p>Data used in the presentation "Open citations in Informatics" held during ECSS 2021. It includes six different files obtained using the software available at <a href="https://github.com/essepuntato/ecss-2021">https://github.com/essepuntato/ecss-2021</a>.</p>
Data from: Data reuse and the open data citation advantage
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