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15 results for “co-authorship”
Original dataset for "A validation of co-authorship credit models with empirical data from the contributions of PhD candidates"
<p><strong>Publication reference:</strong><br> Donner, P. (2020). A validation of co-authorship credit models with empirical data from the contributions of PhD candidates. Quantitative Science Studies, v. 1, i. 2, p. 551-564. <a href="https://doi.org/10.1162/qss_a_00048">https://doi.org/10.1162/qss_a_00048</a>.</p> <p> </p> <p>The file contains one row per authorship contribution statement. Rows of publications and theses are grouped.</p> <p><strong>Description of columns:</strong></p> <p>dissertation_id - an integer identifying each dissertation thesis</p> <p>university - university at which the dissertation thesis was written and PhD degree conferred</p> <p>year - publication year of the dissertation thesis</p> <p>author - dissertation thesis author name</p> <p>title - dissertation thesis title</p> <p>subject - the field of research</p> <p>publication_id - an integer identifying each publication; publication associated with more than one thesis have the same id across theses</p> <p>reference - bibliographic reference for the publication associated with the thesis</p> <p>author_count - number of authors of the publication</p> <p>author_position - position in the author byline of the credited author</p> <p>credit - claimed credit of the author in percent</p> <p>corresponding_author - flag for whether the publication author of this row is a orresponding author</p>
Colombia researchers co-authorship network and adjacency matrix.
<p>OpenAlex subset of papers published by researchers affiliated with an institution in Colombia.</p> <p>* gml file containing the coauthorship network with the metadata: Researcher name, one affiliation, list of OpenAlex concepts of level 0.</p> <p>* Adjacency matrix of type scipy sparse saved in a npz file</p> <p>*npz file with the concepts the author ar marked with</p> <p>*npz file with a map of 200 words and the affiliation each author reports</p> <p>*npz file with a dict that has the mappings from numbers to string for each variable (X with words and affiliations and Z with concepts)</p>
University of Turin IRIS-registered Publications for co-authorship networks
<p>Data extracted from the University of Turin (UNITO) IRIS publication database (available at <a href="https://iris.unito.it/">www.iris.unito.it</a>) regarding publication authorship.<br>This data was generated in order to produce co-authorship networks of authors inside of UNITO.<br><br>The JSON-formatted dataset includes data regarding UNITO affiliated authors that have published from the year 2012 to roughly September 2023, along with a list of all of their publications in the same time period.The dataset encompasses 15807 authors and 66313 articles.<br><br>The JSON has the following structure:</p><ul><li>`authors` (list): A list of objects representing authors, each with the following structure:<ul><li>`name` (string): The author's given name, all in lowercase letters. This field is always populated;</li><li>`surname` (string): The author's family name, all in lowercase letters. This field is always populated;</li><li>`affiliation` (string): The string "university of turin";</li><li>`department` (string or NULL): Empty (`null`) or with a string indicating the author's <strong>current</strong> (as of data collection, roughly September 2023) work department;</li><li>`id` (string): Unique UUID4 of the author.</li></ul></li><li>`papers` (list): A list of object representing published articles, each with the following structure:<ul><li>`id` (string): Unique IRIS ID of the publication. This field is always populated;</li><li>`title` (string): Title of the publication. This field is always populated;</li><li>`year` (numeric): Year of the article's publication date. This field is always populated;</li><li>`authors` (list): A non-empty list of strings. Each string is one ID of one of the authors in the `authors` list.</li></ul></li></ul><p>The data was kindly provided by the IRIS office in September 2023 and preprocessed by Luca Visentin to a digestible JSON.</p>
Network visualisation of co-authorship analysis of countries
<p>VOSviewer mapping shows network visualisation of co-authorship analysis of countries for <span>focusing on MICP research in the context of hydrodynamics (1999-2024).</span></p>
International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases
<p>In innovation strategy, a type of Schumpeterian competitive strategy in business administration, "intra-individual diversity" has attracted attention as one factor for creating innovation. In this study, we redefine "framework for identifying researchers' areas of expertise" as "a framework for quantifying intra-individual diversity among researchers. Note that diversity here refers to authorship of articles in multiple research fields. The application of this framework then made it possible to visualize organizational diversity by accumulating the intra-individual diversity of researchers and to discuss the innovation strategy of the organization. The analysis in this study discusses how countries are promoting research on the topics of artificial intelligence (AI), big data, and Internet of Things (IoT) technologies, which are at the core of Industry 4.0, from an innovation perspective. Note that Industry 4.0 is a technological framework that aims to "improve the efficiency of all social systems," "create new industries," and "increase intellectual productivity." For the analysis, we used 19-year bibliographic data (2000–2018) from the top 20 countries in terms of the number of papers in AI, big data, and IoT technologies. As the results, this study classified the styles of cross-disciplinary fusion into four patterns in AI and three patterns in big data. This study did not consider the results in IoT because of only small differences between countries. Furthermore, regional differences in the style of cross-disciplinary fusion were also observed, and the global innovation patterns in Industry 4.0 were classified into seven categories. In Europe and North America, the cross-disciplinary integration style was similar to that between the United States, Germany, the Netherlands, Spain, England, Italy, Canada, and France. In Asia, the cross-disciplinary fusion style was similar between China, Japan, and South Korea.</p>
Dataset of "Gender analysis and co-authorship networks in the scientific production of oncology in Spain (2011–2021)"
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A visualization of co-authorship network of mathematicians with an Erdős number of at most 2
<p>Co-authorship network of mathematicians with an Erdős number of at most 2</p> <p>Based on the data available at: https://oakland.edu/enp/thedata/erdos1.</p> <p>As can be seen, Erdős has collaborated directly or through an intermediary with different groups of scientists.<br> Researchers in the field of graph and computer science (gold), specialists in number theory (pink), mathematicians in the field of set theory (blue), researchers in the field of computer engineering (green) and the isolated group of Peter Salamon and his colleagues are the main groups of these researchers.<br> The names of researchers with more than 190 colleagues in the network (the first 10% of researchers) are written in the figure.</p> <p>See https://sites.google.com/oakland.edu/grossman/home/the-erdoes-number-project/the-erdoes-number-project-data-files.</p> <p>This artifact is a part of https://math-sci.ui.ac.ir/article_25684.html.</p>
Dataset for proceedings paper: How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium
<p>This is an anonymized dataset containing data on international collaboration in the social sciences and humanities (SSH) in Flanders, Belgium. It is based on all peer-reviewed publications in <a href="https://www.ecoom.be/en/data-collections/vabb-shw">VABB-SHW</a>, regardless of their indexation in WoS or other databases.</p> <p>The dataset accompanies the conference paper 'How international is co-authorship outside of Web of Science? The case of social sciences and humanities in Flanders, Belgium,' which was submitted to <a href="https://cns-iu.github.io/workshops/2023-07-02_issi/index.html">ISSI 2023</a>.</p>
International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases
Open the record for dataset details and reuse information.
FIGURE 4 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 4. Barplot showing the production of South American authors, including collaborative works. Production measured as number of valid species described.
FIGURE 3 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 3. Characteristic fraction of author production measured for different intervals. The fractions R/Wt and R/Ws represent the prevalence and representativeness of regional author production respectively. R= Number of valid species described by regional authors within the target time interval; Wt= Total number of valid species described within the target time interval: Ws= Total number of valid species described solely by regional authors. Dashed line corresponds to coefficient ς and its maximum corresponds to the period [1999, 2012]. In this period: (i) the overall production is dominated by South American authors, and (ii) the bulk of South American production is included.
FIGURE 1 in Co-authorship networks (and other contextual factors) behind the growth of taxonomy of South American Ephemeroptera: A scientometric approach
FIGURE 1. Number of valid species described by period. Species described by foreign (F), regional (R) and mixed (M) authors are represented by different tones. Note that binned time intervals do not represent equal periods.
Open access and international co-authorship: a longitudinal study of the United Arab Emirates research output
<p>Enriched data from Scopus used for the article: Open access and international co-authorship: a longitudinal study of the United Arab Emirates research output</p>
Research collaboration patterns in sustainable mining – a co-authorship analysis of publications
<p>This dataset includes data related to 4220 articles on sustainable mining published from 1983 to 2018. The Scopus database was selected as a data source. Detailed data applies to co-authored articles. The number of authors and affiliations (country, institution, sector) were taken into account. Data has been cleaned in terms of names of institutions and countries.<br> In given sets the following data were included:<br> - Distribution of articles in sustainable mining from 1983 to 2018<br> - Distribution of joint articles and the types of joint articles from 1983 to 2018<br> - Team size in terms of the number of authors of articles in sustainable mining from 1983 to 2018<br> - Team size in terms of the number of authors' institutions in articles in sustainable mining from 1983 to 2018<br> - Team size in terms of the number of authors' countries in articles in sustainable mining from 1983 to 2018</p> <p><strong>Please note, the field separator used in these files is a semicolon, while the decimal separator is a comma. Each of the files has two header lines.</strong></p>
Data from: The co-authorship networks of the most productive European researchers
<p>This individual-level data-set describes the most productive European Union (EU) researchers (in terms of articles), during 2007 - 2018, irrespective of their research field. Specifically, in the data-set file, i.e. "iconic_5000", we profile the most productive 4,588 EU researchers using the following variables: number of papers; number of citations; repeated collaborations; number of co-authors; number of co-authors from the same country (as the author), from the same city, from the same institution and from different countries; geographical dispersion (number of unique countries wherein co-authors are based in), star (the largest number of articles published by one of an author's collaborators), godfather (the largest number of citations received by one of an author's collaborators), co-authors' citations and co-authors' papers. Variables are yearly measured.</p>
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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.