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46 results for “Academic Research”
Research data supporting "Considerations for Implementing Electronic Laboratory Notebooks in an Academic Research Environment"
<p><em>Research data supporting the publication:</em></p> <p><em>Higgins SG, Nogiwa-Valdez AA, Stevens MM, Considerations for Implementing Electronic Laboratory Notebooks in an Academic Research Environment, Nature Protocols, 2021.</em></p> <p>This repository contains the raw survey data of 172 current and historic electronic laboratory notebook (ELN) software packages.</p> <p>Main files:</p> <ul> <li>"ELN_Review_Higgins_2021_Survey.csv" = raw survey data in 'tidy' data format</li> <li>"ELN_Review_Higgins_2021.Rmd" = an R Markdown File (R Notebook) that takes the survey data as input and produces summary statistics and plots. This file was written using R Studio as the IDE.</li> </ul> <p>Derived files, generated from those above:</p> <ul> <li>"ELN_Review_Higgins_2021.nb.html" = a self-contained HTML file that is automatically generated by R Studio, based on the markdown file. This can be opened in any web browser to allow manual inspection of the code and comments without the need for specialist software. Embedded within this file is also the original markdown script (i.e. a copy of the code in "ELN_Review_Higgins_2021.Rmd")</li> <li>"ELN_Review_Higgins_2021_Lifetimes_Interactive_Figure1.html" = an HTML file generated by the script above via the plotly package. It contains an interactive version of the ELN survey data, allowing the user to hover over the timeline and explore the data.</li> <li>"ELN_Review_Higgins_2021_Timeline.pdf" = static version of ELN timeline, used to generate figure in main manuscript.</li> <li>"ELN_Review_Higgins_2021_Releases-Per-Year.pdf" = static version of number of new ELNs per year, used to generate figure in main manuscript.</li> </ul> <p>This survey was generated from a mixture of primary and secondary sources (see references for secondary sources).</p>
Dataset for: Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manusript:<br> Perrier L, Blondal E, MacDonald H. Exploring the experiences of academic libraries with research data management: a meta-ethnographic analysis of qualitative studies. 2018; 40(3-4): 173-183. doi: 10.1016/j.lisr.2018.08.002</p> <p>Full-text available at: <a href="https://doi.org/10.1016/j.lisr.2018.08.002">https://doi.org/10.1016/j.lisr.2018.08.002</a> </p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:</p> <ol> <li>Data Dictionary: RDMMetaEthnography_DataDictionary_v1.pdf</li> <li>Data Abstraction Sheet: RDMMetaEthnography_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_ParticipantCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_Outcomes.csv</li> <li>Data Abstraction Sheet: RDMMetaEthnography_COREQ,csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Research institutions clustering based on the intensity of academic collaboration
<p>The clustering of research institutions has been conducted using the Louvain modularity algorithm. The Louvain modularity is a state-of-the-art method of identifying communities (clusters) in large networks. Modularity is a value between -1 and 1 that measures the density of edges inside communities to edges outside communities. Optimizing this value results in the best possible grouping of the nodes of a given network.</p> <p>In our exercise, the Louvain methods were applied to identify clusters of institutions within ACM and SSRN networks. In the network, nodes are constituted of institutions, and edges are represented by the intensity of research collaboration measured by number of papers co-authored by authors affiliated with the institutions.</p> <p>As an example, including the paper: <em>Fast unfolding of communities in large networks</em>, written by V. D. Blondel (Universite Catholique de Louvain), J-L. Guillaume (Universite Pierre et Marie Curie), R. Lambiotte (Imperial College London) and Etienne Lefebvre (Universite Catholique de Louvain) would impact the number of edges in our analysis in the following way:</p> <p>“Universite catholique de Louvain” ⇔ “Imperial College London” =+1</p> <p>“Universite catholique de Louvain” ⇔ “Universite Pierre et Marie Curie” =+1</p> <p>“Imperial College London” ⇔ “Universite Pierre et Marie Curie” =+1</p> <p>In our largest network we analyse 5362 institution nodes with 147 482 edges. The number of identified clusters highly depends on the resolution parameter. Resolution is a parameter for the Louvain community detection algorithm that affects the size of the recovered clusters. Smaller resolutions recover smaller, and therefore a larger number of clusters, and conversely, larger values recover clusters containing more data points. In all clusterizations, we have used a default resolution (1.0) tuned in the popular Gephi software for network analysis. Resolutions equal to one result in a moderate number of clusters, characterised by satisfactory statistical distribution. </p> <p><strong>Source:</strong></p> <p>- Association for Computing Machinery (ACM)</p> <p>Characteristics of the ACM Data Set following geographical classification</p> <p>Number of institutions: 5477</p> <p>Number of papers: 674684</p> <p>Number of countries: 122</p> <p>Years: 2011-2018</p> <p>As ACM contains publications across various areas of computer science, a more in-depth analysis requires the classification of papers into fields of interests. During the analysis, we looked at 3 wide areas:</p> <ul> <li> <p>Artificial intelligence and machine learning</p> </li> <li> <p>Technology (hardware, emerging technologies, infrastructure)</p> </li> <li> <p>Social issues</p> </li> </ul> <p>The 3 categories were set following expert analysis of the 1000 most frequent keywords in the dataset. If a term from the following list appeared among the paper’s keywords, the paper was assigned to that group, allowing a paper to assign to more than one group.</p> <p><strong>Files:</strong></p> <p>mod_ai.csv (based on keywords related to artificial intelligence)</p> <p>mod_tech.csv (based on keywords related to technologies)</p> <p>mod_soc.csv (based on keywords related to social issues)</p> <p>mod_all.csv (based on all papers)</p> <p> </p>
A census of research software in 171 academic institutional repositories.
<p> A dataset of metadata for 171 UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table>
A dataset of metadata for UK academic institutional repositories, including a census of research software contained.
<p>A dataset of metadata for UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table> <p> </p>
Dataset for: Research data management in academic institutions: a scoping review
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manuscript: <br> Perrier L, Blondal E, Ayala AP, Dearborn D, Kenny T, Lightfoot D, Reka R, Thuna M, Trimble L, MacDonald H. Research data management in academic institutions: A scoping review. PLOS One. 2017 May 23;12(5):e0178261. doi: 10.1371/journal.pone.0178261.</p> <p>Full-text available at: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178261 ">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178261 </a></p> <p><strong>Data and Documentation Files</strong> </p> <p>Five files make up the dataset: </p> <ol> <li>Data Dictionary: RDMScopingReview_DataDictionary.pdf</li> <li>Data Abstraction Sheet: RDMScopingReview_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_Setting.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_DataCollectionTools.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_Outcomes.csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> ● The Islamic University of Gaza (IUG) ● Al-Quds Open University (QOU) ● Birzeit University (BZU) ● Palestine Technical University-Kadoori (KAD)
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data with Pie Charts
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> <p>● The Islamic University of Gaza (IUG)</p> <p>● Al-Quds Open University (QOU)</p> <p>● Birzeit University (BZU)</p> <p>● Palestine Technical University-Kadoori (KAD)</p> <p>[Data visualised as pie charts]</p> <p> </p>
ICITS'23 - Understanding the Success Factors of Research Software: Interviews with Brazilian Computer Science Academic Researchers
<p>Artifacts used for data collection and analysis of the article accepted for publication in ICITS'23.</p> <p>Mourão, E., Trevisan, D., Viterbo, J. (2022).Understanding the Success Factors of Research Software: Interviews with Brazilian Computer Science Academic Researchers. In: ICITS'23 - 6th International Conference on Information Technology & Systems. Advances in Intelligent Systems and Computing, Springer, Cham.</p>
Publication packages for academic research
<p>Infographic summarizing what to include in a publication package, based on the <a href="https://doi.org/10.5281/zenodo.7583831">Guideline for the archiving of academic research for Faculties of Behavioural and Social Sciences in the Netherlands (March 2022)</a></p> <p> </p>
Research Scholars Workshop: Academic vs. Industry Research
<p>In this workshop, we will explore the differences between research in an academic setting versus industry, including how work is planned, executed, and disseminated. We will hear from expert researchers in both settings. </p>
Research Data Services (RDS) in Spanish Academic Libraries
<p>Files in csv format to analyze Research Data Services implemented in Spanish university libraries (2022).</p>
Academic Social Media: The Marketplace of Ideas | Researching Islam | iBrary
<p>This video introduces the module “Academic Social Media: The Marketplace of Ideas” from the course Researching Islam, taught by Prof. Shafique N. Virani. You can download the complete online course, including this module, for free from <a href="https://www.youtube.com/redirect?event=video_description&redir_token=QUFFLUhqbHVJYVg2TmtrVjZmcWloZ3hMWDFFVmZ3MmJvZ3xBQ3Jtc0tsaE9fWnJ5STY3aFoteXVtMTAxVUItQV96ZzN0cklRMFUxRnJiTEtsdzJEamQtSW5teUpfT0JCRTVobVNPOUI1UllfaXF1NFNJODVVN3B4dkUtNW1LeWlkRFdsc0xCVmJpLVJOQXlIZndsV3Y3TW1zUQ&q=https%3A%2F%2Fwww.ecampusontario.ca%2F&v=lCfJPE-ZGV8">https://www.ecampusontario.ca/</a>.</p>
Antimicrobial Resistance Microbiological Dataset (ARMD-UTSW): A deidentified collection of electronic health records, from a quaternary, academic medical center, for antimicrobial resistance research
Open the record for dataset details and reuse information.
Data from: Postdoctoral T32 training is correlated with obtaining an academic primarily research faculty position
Open the record for dataset details and reuse information.
Antimicrobial Resistance Microbiological Dataset (ARMD-ECUH): A deidentified collection of electronic health records from a rural academic health system for antimicrobial resistance research
Open the record for dataset details and reuse information.
Research Data Services in Academic Libraries: A Survey of North American Academic Libraries in 2019
<p>To determine the extent to which research data services (RDS) are supported in academic libraries and how that has changed over a decade, in 2019 a research team led by Carol Tenopir at the University of Tennessee Center for Information and Communication Studies, in collaboration with ACRL-Choice, surveyed academic library directors in the United States and Canada. This survey allowed us to compare results with a similar survey conducted in 2012. The goal of both studies was to discover the types of data services offered, the staffing deployed or anticipated for such services, the training necessary to support RDS, and RDS plans for the future.</p> <p>The associated white paper can be accessed at <a href="http://www.choice360.org/librarianship/whitepaper">http://www.choice360.org/librarianship/whitepaper</a> and downloaded at <a href="https://www.research.net/r/CHOICERDSWP">https://www.research.net/r/CHOICERDSWP</a></p>
Using Artificial Intelligence in Research: Academic Staff of Ukrainian HEIs
<p>The survey was conducted by the researchers of the Institute of Higher Education of NAES of Ukraine (https://ihed.org.ua/). Empirical data was collected from March 21 to April 3, 2023. The Register of Education Institutions of the Unified State Electronic Database on Education (https://registry.edbo.gov.ua/) was the source for the targeted sample.</p>
Academic Research at UNTRM: Bibliometric Analysis in Economic and Administrative Sciences
<p><span>Bibliometric analysis is crucial to assess research trends in disciplines such as economics and administrative sciences. This study aims to detail trends and developments in these areas at the Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), highlighting emerging themes and influential actors. A systematic bibliometric methodology was used to understand the scientific focus of the publications of the thesis students of the Faculty of Economics and Administrative Sciences of the UNTRM. Scopus documents were thoroughly reviewed, using specific inclusion and exclusion criteria. The research followed a qualitative descriptive approach with non-experimental and longitudinal design. A total of 379 faculty theses were analyzed through December 31, 2023, using keywords such as "bibliometric analysis," "economic sciences," "management," "digital transformation," "business sustainability," and "energy efficiency." The initial search identified 786 papers, which were refined for quality assurance. Bibliometric analysis was performed with VOSviewer and Bibliometrix R, facilitating the creation of scientific maps and exploration of citation patterns. Results showed that the most researched topics include digital transformation, sustainability, energy efficiency and business innovation. Influential authors and institutions within UNTRM were identified and major research trends were mapped, highlighting emerging areas and gaps in the current literature. These findings are significant for future research as they provide a basis for exploring new directions in economics and management sciences. This bibliometric analysis not only maps research streams and scholarly collaborations at UNTRM, but also promotes a deeper understanding of the dynamics in these key areas of study.</span></p>
Investigating the Adoption of Research Software: A Survey with Brazilian Academic Researchers
<p>Artifacts used for data collection and analysis.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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OpenNeuro
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