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49 results for “disciplines”
ORCID data to accompany Study of ORCID Adoption Across Disciplines and Locations
<p>Data gathered in January 2017 from the ORCID registry in support of Study of ORCID Adoption Across Disciplines and Locations. Study conducted as part of Horizon 2020 project THOR (http://project-thor.eu).</p> <p><strong>ORCID uptake by discipline and region.xlsx</strong> : Master file of all processed metrics with breakdowns by discipline and region. (For description of selection of disciplinary taxonomy and processing steps, see associated paper.)</p> <p><strong>All other .csv files</strong> : Underlying data for processed metrics. (For description of "full counts" and other factors of data gathering, see associated paper.)</p>
Data from systematic audit for paper: Insights into the quantification and reporting of model-related uncertainty across different disciplines
<p>This upload contains 7 data files (each contains cleaned and compiled data for a given scientific field) and 2 R scripts. These files support the paper: Insights into the quantification and reporting of model-related uncertainty across different disciplines.</p> <p> </p> <p><strong>Description of the data</strong></p> <p>Compiled data files for each field contain all reviewers audit answers for eligible papers. All papers that met exclusion criteria have been removed.</p> <p>Data checks have been performed and formatting errors corrected either in R or manually, following steps detailed in the STAR methods.</p> <p>Column names and description:</p> <ul> <li>Number: number of question from 1 to 9</li> <li>Questions: question text – question to be answered by the reviewer</li> <li>QuestionCode: shortened code for each question</li> <li>Paper: paper code - first author surname/initial and surname and year</li> <li>Initials: initials of reviewer</li> <li>Answer: answer to the question</li> <li>Details: extra details to support the answer</li> <li>Location: where in the text the uncertainty was presented</li> <li>Presentation: how the uncertainty was presented</li> <li>ModelType: type of model (focal model)</li> <li>Comments: any other comments from the reviewer</li> <li>Checks: checks of whether NA or no have been included in correct places e.g. if answers to questions 1:4 are no then question 9 is NA, if question 7 is no then 8 is NA</li> <li>Check 1 = when Answer = No, Location is NA</li> <li>Check 2 = when Answer to Number 1-4, 6 or 8-9 is Yes that Details are not NA</li> <li>Check 3 = when Answer = No, Presentation = NA</li> <li>Check 4 = when Location is not NA, presentation is not NA</li> <li>Check 5 = if the Answer to 5 or 7 is "No" then Answer to 6 and 8 = "NA"</li> <li>Check 6 = if Answer for 1-4 is "No", then Answer for 9 = "NA"</li> </ul> <p><strong>Code description</strong></p> <p>Two scripts are included, the first is theme_script.R, this includes code to set up a ggplot theme for the figures. The second is Figure_code.R, this script contains all code to plot and save the three figures from the paper.</p>
Prevalence of Creative Commons licenses in the Directory of Open Access Journals by discipline, author fees, number of journals per country and publisher
<p>An analysis on the prevalence of Creative Commons licenses in the Directory of Open Access Journals by discipline, author fees, country and publisher according to the number of journals.</p>
Numbers and shares of Open Access Journals from all disciplines and from the discipline Sociology using Creative Commons Licenses as listed by the Directory of Open Access Journals (2014-06-08)
<p>These files contains the data on frequencies and shares of Open Access journals using Creative Commons Licenses (comparing journals from all disciplines and sociologial journals). Date of data collection: 2014-06-08.</p>
Typology of academic disciplines in the Modern China Biographical Database
<p>This table presents the bilingual typology of academic disciplines used in the Modern China Biographical Database. It is based mainly on the typology created by Yuan T'ung-li in his three bibliographical volumes about the doctoral dissertations by Chinese students in the United States, the United Kingdom, and continental Europe. We adapted this typology to include other disciplines that were present in historical sources.</p> <p><strong>Dataset Description: Typology of Disciplines (Level 2)</strong></p> <p><strong>Overview:</strong> This dataset provides a bilingual typology of academic disciplines, specifically focusing on Level 2 classifications. The terms are extracted from various Chinese sources, with English translations provided. It is structured hierarchically, connecting each Level 2 discipline to broader categories (Level 1 and Level 0), facilitating multilingual academic classification.</p> <p><strong>Structure:</strong> The dataset consists of the following key columns:</p> <ul> <li> <p><strong>Level 2 Discipline (English & Chinese):</strong> The specific sub-discipline classification.</p> </li> <li> <p><strong>Level 1 Discipline (English & Chinese):</strong> A broader category that groups multiple Level 2 disciplines.</p> </li> <li> <p><strong>Level 0 Discipline (English & Chinese):</strong> The highest-level classification representing major academic domains.</p> </li> <li> <p><strong>Level 1 Code:</strong> A numerical or coded identifier for Level 1 disciplines, supporting structured data processing.</p> </li> </ul> <p><strong>Purpose & Applications:</strong></p> <ul> <li> <p><strong>Hierarchical Classification:</strong> Enables structured categorization of academic fields across multiple levels.</p> </li> <li> <p><strong>Multilingual Standardization:</strong> Supports bilingual terminology consistency in academic and research contexts.</p> </li> </ul> <p>Main sources:</p> <p> </p> <p>Yuan, T’ung-li. <em>A Guide to Doctoral Dissertations by Chinese Students in America, 1905-1960</em>. Washington, D.C.: Published under the auspices of the Sino-American Cultural Society, 1961.</p> <p>———. <em>A Guide to Doctoral Dissertations by Chinese Students in Continental Europe, 1907-1962</em>. S.l., 1964.</p> <p>———. <em>Doctoral dissertations by Chinese students in Great Britain and Northern Ireland, 1916-1961.</em> Uden sted og forlag, 1963.</p>
Raw and aggregated data for the study introduced in the paper "The way we cite: common metadata used across disciplines for defining bibliographic references"
<p>These data have been gathered in the context of a study aiming to investigate citation practices for referencing different types of entities and, in particular, for understanding the most used metadata in bibliographic references. The data are stored in two documents in XLSX format:</p> <ul> <li>file "links-intext-pointers-and-cited-entity-types.xlsx" - it contains information about whether the in-text reference pointers of the various PDF articles of the corpus have specified hypertextual links from the in-text reference pointers to the denoted bibliographic reference, plus information about the types of all the entities cited by each article in the corpus;</li> <li>file "metadata-bibliographic-references.xlsm" - it contains information about the metadata used to identify the various descriptive elements of all the bibliographic references defined in the article of the corpus.</li> </ul> <p>The methodology used to gather all these data is described in:</p> <blockquote> <p>Santos, E. A. d., Peroni, S., Mucheroni, M. L.: Workflow for retrieving all the data of the analysis introduced in the article "Citing and referencing habits in Medicine and Social Sciences journals in 2019". (2020), <a href="https://doi.org/10.17504/protocols.io.bbifikbn">https://doi.org/10.17504/protocols.io.bbifikbn</a></p> </blockquote>
Sources used for content analysis in Crespy, A. and Szabo, I. : Healthcare reforms and fiscal discipline in Europe: Responsibility or responsiveness? forthcoming: European Policy Analysis
<p>Sources used for content analysis in Crespy, A. and Szabo, I. : Healthcare reforms and fiscal discipline in Europe: Responsibility or responsiveness? forthcoming: European Policy Analysis. Data from the ENLIGHTEN project (H2020 #649456).</p>
Raw and aggregated data for the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors"
<p>This dataset contains all the raw data and aggregated data subject of the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors". The study is based on the bibliographic and citation data contained in 729 articles published in 147 journals in 27 subject areas. The articles contained a total amount of 34,140 bibliographic references and 55,100 mentions and quotations overall.</p> <p>The dataset is composed of a series of files:</p> <ul> <li>the files "subject_area_<discipline-name>.csv" contain the raw data of the articles published in the journals of all the disciplines considered in the study;</li> <li>the file "article_data_summary.csv" contains the aggregated data created considering the raw data in the previous files, which have been used to creating all the tables and figures in the article;</li> <li>the file "starred_metadata_set.csv" contains information about the most used subset of bibliographic metadata;</li> <li>the file "journals_selection.csv" contains information about all the journals selected for the study.</li> </ul>
Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESULTS DATASET (with Mega Journals)
<p>The dataset contains all the data produced running the research software for the study:"Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta".</p> <p>Disclaimer: these results are not considered to be representative, because we have fount that Mega Journals skewed significantly some of the data. The result datasets without Mega Journals are published <a href="https://zenodo.org/record/8249907">here</a>.</p> <p>Description of datasets:</p> <ul> <li><strong>SSH_Publications_in_OC_Meta_and_Open_Access_status.csv: </strong>containing information about OpenCitations Meta coverage of ERIH PLUS Journals as well as their Open Access availability. In this dataset, every row holds data for a Journal of ERIH PLUS also covered by OpenCitations Meta database. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li><strong>SSH_Publications_by_Discipline.csv:</strong> containing information about number of publications per discipline (in addition, number of journals per discipline are also included). The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>SSH_Publications_and_Journals_by_Country:</strong> containing information about number of publications and journals per country. The dataset has three columns, the first, labeled <strong>"Country",</strong> contains single countries of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>result_disciplines.json:</strong> the dictionary containing all disciplines as key and a list of related ERIH PLUS venue identifiers as value.</li> <li><strong>result_countries.json:</strong> the dictionary containing all countries as key and a list of related ERIH PLUS venue identifiers as value.</li> <li><strong>duplicate_omids.csv: </strong>a dataset containing the duplicated Journal entries in OpenCitations Meta, structured with two columns: "<strong>OC_omid"</strong>, the internal OC Meta identifier; "<strong>issn", </strong>the issn values associated to that identifier</li> <li><strong>eu_data.csv: </strong>contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"Original_Title"</strong>,<strong> "Country_of_Publication"</strong>,<strong>"ERIH_PLUS_Disciplines"</strong>, <strong>"disc_count"</strong>, the number of disciplines per Journal.</li> <li><strong>eu_disciplines_count.csv: </strong>containing information about number of publications per discipline and number of journals per discipline of european countries. The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>meta_coverage_eu.csv: </strong>contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li><strong>us_data.csv: </strong>contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"Original_Title"</strong>,<strong> "Country_of_Publication"</strong>,<strong>"ERIH_PLUS_Disciplines"</strong>, <strong>"disc_count"</strong>, the number of disciplines per Journal.</li> <li><strong>us_disciplines_count.csv: </strong>containing information about number of publications per discipline and number of journals per discipline of the United States. The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>meta_coverage_us.csv: </strong>contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> </ul> <p> </p> <p><strong>Abstract of the research: </strong></p> <p><strong>Purpose:</strong> this study aims to investigate the representation and distribution of Social Science and Humanities (SSH) journals within the OpenCitations Meta database, with a particular emphasis on their Open Access (OA) status, as well as their spread across different disciplines and countries. The underlying premise is that open infrastructures play a pivotal role in promoting transparency, reproducibility, and trust in scientific research.<br> <strong>Study Design and Methodology:</strong> the study is grounded on the premise that open infrastructures are crucial for ensuring transparency, reproducibility, and fostering trust in scientific research. The research methodology involved the use of secondary data sources, namely the OpenCitations Meta database, the ERIH PLUS bibliographic index, and the DOAJ index. A custom research software was developed in Python to facilitate the processing and analysis of the data.<br> <strong>Findings:</strong> the results reveal that 78.1% of SSH journals listed in the European Reference Index for the Humanities (ERIH-PLUS) are included in the OpenCitations Meta database. The discipline of Psychology has the highest number of publications. The United States and the United Kingdom are the leading contributors in terms of the number of publications. However, the study also uncovers that only 38% of the SSH journals in the OpenCitations Meta database are OA.<br> <strong>Originality:</strong> this research adds to the existing body of knowledge by providing insights into the representation of SSH in open bibliographic databases and the role of open access in this domain. The study highlights the necessity for advocating OA practices within SSH and the significance of open data for bibliometric studies. It further encourages additional research into the impact of OA on various facets of citation patterns and the factors leading to disparity across disciplinary representation.</p> <p><strong>Related resources:</strong></p> <p>Ghasempouri S., Ghiotto M., & Giacomini S. (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESEARCH ARTICLE. <a href="https://doi.org/10.5281/zenodo.8263908">https://doi.org/10.5281/zenodo.8263908</a></p> <p>Ghasempouri, S., Ghiotto, M., Giacomini, S., (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - DATA MANAGEMENT PLAN (Version 4). Zenodo. <a href="https://doi.org/10.5281/zenodo.8174644">https://doi.org/10.5281/zenodo.8174644</a></p> <p>Ghasempouri, S., Ghiotto, M., Giacomini, S. (2023e). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - PROTOCOL. V.5. (<a href="https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5">https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5</a>)</p>
Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESULTS DATASET (without Mega Journals)
<p>The dataset contains all the data produced running the research software for the study <em>Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta</em>, a research carried out in the contest of the Open Science course 22/23 at the University of Bologna.</p> <p>Mega Journals have been excluded form the datasets, since we found they were significantly skewing the results, the only datasets not interested by this exclusion are <strong>SSH_Publications_in_OC_Meta_and_Open_Access_status </strong>and<strong> duplicate_omids.</strong> The result datasets with Mega Journals included are published <a href="https://doi.org/10.5281/zenodo.8250858">here</a><br> The Journals excluded from the results are: PLOS ONE (issn:1932-6203), PNAS (issn:1091-6490), Science (issn:1095-9203), Nature(issn:0028-0836).</p> <p>Description of datasets:</p> <ul> <li><strong>SSH_Publications_in_OC_Meta_and_Open_Access_status.csv: </strong>containing information about OpenCitations Meta coverage of ERIH PLUS Journals as well as their Open Access availability. In this dataset, every row holds data for a Journal of ERIH PLUS also covered by OpenCitations Meta database. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li><strong>SSH_Publications_by_Discipline.csv:</strong> containing information about number of publications per discipline (in addition, number of journals per discipline are also included). The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>SSH_Publications_and_Journals_by_Country:</strong> containing information about number of publications and journals per country. The dataset has three columns, the first, labeled <strong>"Country",</strong> contains single countries of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>result_disciplines.json:</strong> the dictionary containing all disciplines as key and a list of related ERIH PLUS venue identifiers as value.</li> <li><strong>result_countries.json:</strong> the dictionary containing all countries as key and a list of related ERIH PLUS venue identifiers as value.</li> <li><strong>duplicate_omids.csv: </strong>a dataset containing the duplicated Journal entries in OpenCitations Meta, structured with two columns: "<strong>OC_omid"</strong>, the internal OC Meta identifier; "<strong>issn", </strong>the issn values associated to that identifier</li> <li><strong>eu_data.csv: </strong>contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"Original_Title"</strong>,<strong> "Country_of_Publication"</strong>,<strong>"ERIH_PLUS_Disciplines"</strong>, <strong>"disc_count"</strong>, the number of disciplines per Journal.</li> <li><strong>eu_disciplines_count.csv: </strong>containing information about number of publications per discipline and number of journals per discipline of european countries. The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>meta_coverage_eu.csv: </strong>contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> <li><strong>us_data.csv: </strong>contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"Original_Title"</strong>,<strong> "Country_of_Publication"</strong>,<strong>"ERIH_PLUS_Disciplines"</strong>, <strong>"disc_count"</strong>, the number of disciplines per Journal.</li> <li><strong>us_disciplines_count.csv: </strong>containing information about number of publications per discipline and number of journals per discipline of the United States. The dataset has three columns, the first, labeled <strong>"Discipline",</strong> contains single disciplines of the ERIH classificaton, the second and the third, labeled <strong>"Journal_count" </strong>and <strong>"Publication_count", </strong>respectively, the number of Journals and the number of Publications counted for each discipline.</li> <li><strong>meta_coverage_us.csv: </strong>contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "<strong>EP_id", </strong>the internal ERIH PLUS identifier; <strong>"Publications_in_venue", </strong>the<strong> </strong>numbers of Publications counted in each venue; <strong>"</strong><strong>OC_omid", </strong>the internal OpenCitations Meta identifier for the venue;<strong> "issn",</strong> numbers of publications in each venue;<strong> "Open Access",</strong> a value to represent if the journal is OA or not, either "True" or "Unknown".</li> </ul> <p> </p> <p><strong>Abstract of the research: </strong></p> <p><strong>Purpose:</strong> this study aims to investigate the representation and distribution of Social Science and Humanities (SSH) journals within the OpenCitations Meta database, with a particular emphasis on their Open Access (OA) status, as well as their spread across different disciplines and countries. The underlying premise is that open infrastructures play a pivotal role in promoting transparency, reproducibility, and trust in scientific research.<br> <strong>Study Design and Methodology:</strong> the study is grounded on the premise that open infrastructures are crucial for ensuring transparency, reproducibility, and fostering trust in scientific research. The research methodology involved the use of secondary data sources, namely the OpenCitations Meta database, the ERIH PLUS bibliographic index, and the DOAJ index. A custom research software was developed in Python to facilitate the processing and analysis of the data.<br> <strong>Findings:</strong> the results reveal that 78.1% of SSH journals listed in the European Reference Index for the Humanities (ERIH-PLUS) are included in the OpenCitations Meta database. The discipline of Psychology has the highest number of publications. The United States and the United Kingdom are the leading contributors in terms of the number of publications. However, the study also uncovers that only 38% of the SSH journals in the OpenCitations Meta database are OA.<br> <strong>Originality:</strong> this research adds to the existing body of knowledge by providing insights into the representation of SSH in open bibliographic databases and the role of open access in this domain. The study highlights the necessity for advocating OA practices within SSH and the significance of open data for bibliometric studies. It further encourages additional research into the impact of OA on various facets of citation patterns and the factors leading to disparity across disciplinary representation.</p> <p><strong>Related resources:</strong></p> <p>Ghasempouri S., Ghiotto M., & Giacomini S. (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESEARCH ARTICLE. <a href="https://doi.org/10.5281/zenodo.8263908">https://doi.org/10.5281/zenodo.8263908</a></p> <p>Ghasempouri, S., Ghiotto, M., Giacomini, S., (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - DATA MANAGEMENT PLAN (Version 4). Zenodo. <a href="https://doi.org/10.5281/zenodo.8174644">https://doi.org/10.5281/zenodo.8174644</a></p> <p>Ghasempouri, S., Ghiotto, M., Giacomini, S. (2023e). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - PROTOCOL. V.5. (<a href="https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5">https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5</a>)</p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 3. Symbols definition for a graph-based test
<p>In this scenario, we intend to generate a random graph and compute a deep first-search node list. The first defined random symbol is n, namely the number of nodes in the graph as an integer from 5 to 9. The next symbol is named g and denotes the graph object created randomly using 3 parameters: the number of nodes, the minimum, and the maximum value for the weight. For the number of nodes, we used the previously computed value of n, whereas for the weights, we used two constants 0 and 1 since the graph is not weighted</p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 2. Auto-generative Learning Object Model Definition
<p>In this section, we will present the structure of AGLOs in the context of our approach. The AGLO meta-model is structured in XML as in Figure 2,a refinement from Chirila, Ciocarlie, and Stoicu (2015). The AGLO definition contains several sections like name, scenario, theory, question, answers, and feedback (line 01). The name element contains the name of the AGLO, possibly a small description in the human language (line 02). The section of the scenario (line 03) contains a comment (line 04) followed by a set of symbol definitions. The comment should describe the imagined scenario in details and it has the same role as code comments. The symbol is the central element of the AGLO model. The symbol has a name and is very similar to programming language variables. Symbols may be called also parameters since they control the content of the AGLO content in the process of instantiation. </p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 1. The AGLO online assessment approach
<p>In Figure 1, we present the lifetime of AGLOs in the context of online student assessment following a set of steps. In the backend, the tutor develops an AGLO model respecting a predefined meta-model. The model is intuitive, it has a few sections where symbols are defined using formulas and random numbers and then used in a section of a presentation for the student. When such models are created they are stored in a storage facility like a database to be selected by the student through the web application frontend. In the frontend, the students access the web application using a web browser from a workstation, tablet or smartphone. In the assessment process, the student will access several AGLOs. At this step, the accessed AGLOs are instantiated with random numbers, formulas are evaluated to fulfill the designed learning or testing scenario and to create the presentation content for the student. Nevertheless, the instantiated symbols will be used for the automatic assessment of the answers correctness</p>
BRAIN Journal-Auto-generative Learning Objects in Online Assessment of Data Structures Disciplines-Figure 4. Online test assessment example
<p>Thus, applying these restrictions the computed solution is C, E, G, J, L, H, I and is unique. Node C is the starting node since it is the first from the lexicographical point of view. The first step CE is the only choice coping with the restrictions from the [CE, CG, and CJ] edges. Next, EG is the first edge in the list of [EG, EJ]. The next step is GJ which is the only choice. Edge JL is another unique choice. Edge LH is the next step from the list [LH, LI]. Finally, the last edge is obtained by backtracking to node L and then taking edge LI. These restrictions allow us to drive the student to build only one solution from the possible set of solutions. This will determine an easier way of comparing the student’s answer with the answer of the computer. Another more general solution is to use validation functions which require implementation in domain libraries written in JavaScript. </p>
Wikipedia Academic Disciplines Network
<p>This network is a result of scraping Wikipedia (using <a href="https://scrapy.org/">scrapy</a>), starting at the <a href="https://en.wikipedia.org/wiki/Outline_of_academic_disciplines">Outline of Academic Disciplines</a> and following every link until a page is reached (i.e. if an outline is reached, all the links there are followed, when a page is reached, the links there are recorded, but not followed). Each page/article visited is recorded as a node. If one page/article links to another, the nodes are connected with an edge. The edges are weighted by the number of links between the pages. An example of a weight greater than 1 is if two pages both link to each other, or if there are multiple links to the same page in an article. </p> <p>This process resulted in 640,031 nodes and 4,503,438 edges. The network is undirected, so each edge only appears once. </p> <p> </p>
Are there good ethical reasons why for profit publishers should no longer exist under the conditions of digital infrastructures? And what does this have to do with ethics as a reflexive discipline?
<p>Talk at the <a href="https://www.digital-philosophy.org/">Philosophy [in:of:for:and] Digital Knowledge Infrastructures</a> online workshop (08/09/2022).</p>
Regression data for "Bank Risk-Taking and Market Discipline: Evidence from CoCo Bonds in Korea"
<p>This repository contains the main regression data for the paper "Bank Risk-Taking and Market Discipline: Evidence from CoCo Bonds in Korea" by Younghwan Lee and Alex Haerang Park.</p>
Research on the benefits of nature to people: How much overlap is there in citations and terms for 'nature' across disciplines?
<ol> <li class="ThesisAbstractCxSpFirst">Research on the diverse benefits of nature to people is characterised by a broad range of disciplines involved, encompassing a variety of approaches, methods and terminologies. While a diversity of approaches is valuable, it can lead to difficulties in integrating and sharing findings and could form a barrier to effective knowledge exchange, hindering the development and applications of research outputs.</li> <li class="ThesisAbstractCxSpMiddle">As a starting point for this scoping review, we chose four broad research areas (medicine, psychology, education and environment), selected to represent disparate approaches to research on the benefits of nature to people, within and across which to explore overlap in citations and terms used to describe nature.</li> <li class="ThesisAbstractCxSpMiddle">We conducted expert consultation and a snowball-based approach to source publications, resulting in a sample of 210 papers, spanning multiple disciplines within each of our four research areas. For each paper, we recorded the discipline of the journal in which it was published (publishing discipline), the discipline of its first author (first-author discipline), the number of times journals of each discipline were cited in its bibliography (cited discipline) and the term(s) used in the paper's title or abstract to describe the aspect of nature being explored (nature term).</li> <li class="ThesisAbstractCxSpMiddle">Cited disciplines were significantly different between publishing and first-author disciplines, with papers from psychology, education and public health citing distinct communities of papers. However, disciplines generally cited a wide range of other disciplines, with articles in medical journals being particularly broadly cited.</li> <li class="ThesisAbstractCxSpMiddle">Nature terms were significantly different between publishing and first-author disciplines, with some degree of consistency within disciplines (e.g., education papers consistently used a narrow range of nature terms, such as 'outdoor learning'). However, there was a notably high range of nature terms used within psychology and public health papers, indicating that research from these disciplines may be particularly prone to being overlooked by search strings.</li> <li class="ThesisAbstractCxSpLast">The wide range of disciplines cited is encouraging, since this indicates that diverse research areas are generally aware of each other's work. However, to avoid unnecessary expansion of nature terms and support searchability, we propose four key terms for nature: ('outdoor learning' OR 'outdoor education'), ('nature' OR 'natural'), ('green space' OR 'greenspace') and ('biodiversity' or 'trees'), which could be used across disciplines. We particularly propose that at least one of these be included in every paper, and all four should be included in review search strings. This is likely to result in better understanding of the valuable, disparate contributions made by different disciplines to this expanding and important topic.</li> </ol>
FEDORA. Corpus of literature review on limits and potential of the current organization of knowledge in disciplines
<p>Coded segments for literature review in FEDORA project (Grant Agreement no. 872841), WP1 tasks T1.1, T1.3, T1.6, T1.7. Manually coded segments by 4 coders that were extracted from MAXQDA file are based on the following topics:</p> <p>1. Potential and limits of the vertical disciplinary organization<br> 1.1. What skills are formed?<br> 1.2. What new skills are needed?<br> 1.3. Diversity-responsiveness of the current organization<br> 2. Suggestions to improve (all types of suggestions)<br> 2.1. Other forms of knowledge organization<br> 2.1.1. What thinking skills are they fostering?<br> 2.1.1.1. Are they fostering skills that are needed to citizens and professionals to participate in inter-multi-transdisciplinary, multi-actor and open contexts of RI?<br> 2.1.1.2. What are these skills?<br> 2.1.2. What barriers in implementation of suggestions to improve/other forms of knowledge organisation do stakeholders perceive and anticipate?<br> 2.1.3. How can the universities and schools be supported in order to break down the barriers?<br> 2.2. Forms of co-teaching and open-schooling<br> 2.2.1. Are they effective?<br> 3. The ways the young perceive, experience and cope with science and technology, their future and the range of motives<br> 4. Criteria for designing and/or revising teaching materials and activities for 11-19 year old students<br> 5. Examples of inter-multi-transdisciplinary teaching materials<br> 6. Examples of multi-actor co-teaching and open-schooling contexts<br> 7. Operational markers aimed to evaluate the impact of the inter-multi-transdisciplinary materials on students’ perception and engagement</p> <p>To note, only citations for code groups 1 - 2.1 are presented in this document.</p>
A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics
<p>The dataset is based on the paper: </p> <p>Hoang-Son Pham, Hanne Poelmans and Amr Ali-Eldin ‘’A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics’’, IEEE Access (2023).</p> <p>The dataset includes: </p> <p>1. a list of project metadata extracted from FRIS portal</p> <p>2. a list of VODS disciplines</p> <p>3. a distance matrix</p> <p> </p> <p>* Kindly refer to our paper for more details on the dataset.</p> <p>https://ieeexplore.ieee.org/document/10156853</p>
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.