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465
datasets available to search
ShareScore release 0.9.0
Dataset results
465 results for “academics”
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>
Psychological Well-being, Food Insecurity, Academic Performance, and Other Risk Factors in a Sample of College Students in Jordan during Covid-19
<p>This research investigated the occurrence of psychological well-being perception and its relationship with food insecurity, academic performance, and other correlates in a sample of university students in Amman, Jordan during Covid-19. A cross-sectional study was conducted in two phases. Phase-1 translated and validated an Arabic version of the Psychological General Wellbeing Index-Short version (PGWB-S) in 122 students from the University of Jordan. In Phase-2, 414 students completed demographic questionnaire, Arabic Versions of the PGWB-S, Ryff Psychological Wellbeing Scale, and Individual Food Insecurity Experience Scale.</p> <p>Ethical considerations: This manuscript has been read and approved by all authors. The authors confirm that there are no other persons, who satisfied the criteria for authorship, but are not listed. The order of authors listed in the manuscript has been approved by all of them. They also understand that the Corresponding Author is the sole contact for the Editorial process, and holds the responsibility for communicating with the other author about progress, submissions of revisions and final approval of proofs. Moreover, the authors declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere. Furthermore, all data used in the study is confidential and the lead author has full access to the data reported in the manuscript. We confirm that there are no known conflicts of interest associated with this publication, which did not receive any financial support. Finally, the reporting of this work is compliant with The Code of Ethics of the World Medical Association (Declaration of Helsinki). In addition to that, the protocol of this research is approved by the Institutional Review Board at the University of Jordan, Amman, Jordan (ref no.: 2021-89).</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>
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>
URLs with query strings for software in UK Academic Institutional Repositories.
<p>A set of exact URLs containing the query strings to search for software within UK Academic IRs.</p>
Co-Creation Methods Inventory: Sourced from Academic and Grey Literature
<p><strong>Introducing the Co-Creation Methods Inventory.</strong> Discover an open-access dataset containing a vast collection of co-creation methods. This resource is the culmination of meticulous research and ongoing analysis, drawing from diverse co-creation projects and references. Within this dataset, you will find <strong>765 </strong>co-creation methods sourced from the Health CASCADE Co-Creation Database and grey literature sources. Each method is accompanied by a description and a reference.</p> <p>This initial dataset is meticulously curated to support and enhance your co-creation processes. Whether you are engaged in co-creation, co-design, co-production, or participatory research, these methods offer valuable insights and approaches. This dataset is a precursor to the forthcoming academic articles by Agnello DM et al., scheduled for publication in 2024.</p> <p>For any inquiries or further information about the dataset, please feel free to reach out to Danielle Marie Agnello at <a href="mailto:danielle.agnello@gcu.ac.uk">danielle.agnello@gcu.ac.uk</a>. Additionally, join the conversation and stay updated on her work by following her on Twitter: <a href="https://twitter.com/DannyAgnello_GH">https://twitter.com/DannyAgnello_GH</a>. <br><br>To delve deeper into the <em>Health CASCADE Co-Creation Database</em>, follow this link: <a href="https://doi.org/10.2196/45059">https://doi.org/10.2196/45059</a>. For additional support in utilizing these co-creation methods, explore our <em>Draft Evidence-based Co-Creation Guideline: PRODUCES+ </em>at<em> </em><a href="https://doi.org/10.5281/zenodo.7343029">https://doi.org/10.5281/zenodo.7343029</a><em>.</em> Finally, if you're interested in understanding more about how these methods align with co-creation characteristics, please take a look at this pre-print manuscript about the Co-Creation Rainbow framework: <a href="../records/10391410">https://zenodo.org/records/10391410</a>. </p> <p>Unlock the potential of co-creation methods and embark on a collaborative research journey with confidence, creativity and innovation!</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.
Data for: A path forward: creating an academic culture of justice, equity, diversity and inclusion
Open the record for dataset details and reuse information.
Finite Element model data for Academic Rotor bladed-disc system
Open the record for dataset details and reuse information.
In-hospital patient safety events, healthcare costs and utilization: an analysis of data from the incident reporting system in an academic medical center
<p>Raw Datasets for the study 'In-hospital patient safety events, healthcare costs and utilization: an analysis of data from the incident reporting system in an academic medical center'.</p>
Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic
<p>This data set contains supplementary material for the paper 'Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic' by Martijn Visser, Nees Jan van Eck, and Ludo Waltman. The data set provides the statistics presented in the figures in the paper.</p>
Data from: Are replication rates the same across academic fields? community forecasts from the DARPA SCORE program
The DARPA program "Systematizing Confidence in Open Research and Evidence" (SCORE) aims to generate confidence scores for a large number of research claims from empirical studies in the social and behavioral sciences. The confidence scores will provide a quantitative assessment of how likely a claim will hold up in an independent replication. To create the scores we follow earlier approaches and use prediction markets and surveys to forecast replication outcomes. Based on an initial set of forecasts for the overall replication rate in SCORE and its dependence on the academic discipline and the time of publication, we show that participants expect replication rates to increase over time. Moreover, they expect replication rates to differ between fields, with the highest replication rate in economics (average survey response 58%), and the lowest in Psychology and in Education (average survey response of 42% for both fields). These results reveal insights into the academic community's views of the replication crisis, including for research fields for which no large-scale replication studies have been undertaken yet.
Data from: Use of web-based species occurrence information systems by academics and government professionals
<p>Web-based information systems designed to increase access to species occurrence data for use in research and natural resource decision-making have become more prevalent over the past few decades. The effectiveness of these systems depends on their usability and extent of use by their intended audiences. We conducted an online survey of academics and government professionals in the United States to compare their species occurrence data needs and their perceptions and use of web-based species occurrence information systems. Our results indicate that although views and perceptions held by academics and government professionals about the importance, usefulness, and ease of use of these information systems tend to be similar, there were differences in their use of species occurrence data and web-based species occurrence information systems. The baseline information obtained in this study will help inform future directions for improvements in species occurrence information systems.</p>
Datasets for Effective Distributed Representations for Academic Expert Search
<p>Dataset for the "Effective Distributed Representations for Academic Expert Search" paper published at the <a href="https://ornlcda.github.io/SDProc/ ">SDP 2020 workshop</a> of the EMNLP conference.</p> <p>Two .zip archives are provided:</p> <p>1)<em><strong> papers_and_authors_source_csvs.zip : </strong></em>Contains <em>papers.csv </em>and <em>authors.csv</em>, which are CSV files with the source metadata for all the ~130k papers and ~68k authors used in the final version of the system.</p> <p>2) <em><strong>faiss_indexes.zip : </strong></em>Contains all the pre-populated FAISS indexes with all the embedding variations we used in our research.</p>
Token-based data sets for the analysis of the academic language of literary studies and linguistics
<p>These are the token-based data sets used for my PhD thesis ("Potentiale syntaktischer Annotationen für die datengeleitete Sprachbeschreibung am Beispiel der Wissenschaftssprachen der Germanistik", publication in progress).</p> <p>For python scripts and further data see https://github.com/melandresen/dissertation.</p> <p>Due to copyright law, the annotated texts of the corpus could only be published without the token layer. The files provided here include the token-based frequency data that have been derived from the origial texts and can be used as input to the analysis scripts in the GitHub-Repository.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.