Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
1,365
datasets available to search
ShareScore release 0.9.0
Dataset results
1,365 results for “Needs”
Basic Needs and Student Success Survey (Pilot 2)
<p>Food insecurity among college students is a serious problem that can impact student performance in the classroom and ultimately effect student success. The <a href="https://www.csuchico.edu/chc/">Center for Healthy Communities</a> (CHC) developed the <strong>Basic Needs Student Success Survey (BNS3)</strong> and administered it to undergraduate students participating in the <a href="https://www2.calstate.edu/attend/student-services/eop">Educational Opportunity Program (EOP)</a> at three California State Universities between November 2020 and March 2021. </p> <p>The purpose of this second cross-sectional pilot study was to revise the BNS3 tool and validate student perception of the following:</p> <ol> <li>The impact of receiving <a href="https://www.csuchico.edu/calfresh/index.shtml">CalFresh</a> assistance.</li> <li>The impact of utilization of the campus food pantry on their health, nutrition, cooking confidence, time management and academic performance.</li> </ol> <p>This entry contains </p> <ol> <li>The anonymized and cleaned data set</li> <li>A codebook (data dictionary)</li> <li>The survey tool as a Qualtrics export to Word file</li> </ol>
MULTIPLIERS_WP2_Needs analysis in open schooling and interview guidelines_UCY_20231006_v2
<p>This dataset contains data on the review of needs analysis in open schooling. The dataset is composed mainly by the following items:</p> <ul> <li>description of surveyed persons (interviews transcripts; focus groups and written survey with open ending questions)</li> <li>contents of the semi‐structured interview protocol used for conducting both interviews and focus groups. The interview protocols were produced in local languages by partners who did not conduct the interviews in English.</li> <li>summary of the transcripts of interviews with experts in the selected case‐study regions (in English). Interviewees were asked to provide their views and perceptions on OSC network building and open schooling learning projects.</li> <li>summary of the transcripts of focus groups (in English). Each focus group was held in the local language of the beneficiary organising it, recorded with audio equipment and then transcribed. Focus groups were run in Germany, Cyprus, Spain, Slovenia and Sweden.</li> </ul>
Software Engineering Education Knowledge versus Industrial Needs
<p>Dataset of the research paper: <strong>Software Engineering Education Knowledge versus Industrial Needs</strong></p> <p><em>Contribution</em>: Determine and analyze the gap between software practitioners’ education outlined in the 2014 IEEE/ACM Software Engineering Education Knowledge (SEEK) and industrial needs pointed by Wikipedia articles referenced in Stack Overflow (SO) posts.<br> <em>Background</em>: Previous work has uncovered deficiencies in the coverage of computer fundamentals, people skills, software processes, and human-computer interaction, suggesting rebalancing.<br> <em>Research Questions</em>: 1) To what extent are developers’ needs, in terms of Wikipedia articles referenced in SO posts, covered by the SEEK knowledge units? 2) How does the popularity of Wikipedia articles relate to their SEEK coverage? 3) What areas of computing knowledge can be better covered by the SEEK knowledge units? 4) Why are Wikipedia articles covered by the SEEK knowledge units cited on SO?<br> <em>Methodology</em>: Wikipedia articles were systematically collected from SO posts. The most cited were manually mapped to the SEEK knowledge units, assessed according to their degree of coverage. Articles insufficiently covered by the SEEK were classified by hand using the 2012 ACM Computing Classification System. A sample of posts referencing sufficiently covered articles was manually analyzed. A survey was conducted on software practitioners to validate the study findings.<br> <em>Findings</em>: SEEK appears to cover sufficiently computer science fundamentals, software design and mathematical concepts, but less so areas like the World Wide Web, software engineering components, and computer graphics. Developers seek advice, best practices and explanations about software topics, and code review assistance. Future SEEK models and the computing education could dive deeper in information systems, design, testing, security, and soft skills.</p> <p>The following data files are included.</p> <ul> <li><strong>wikipedia_articles.csv</strong>: Wikipedia articles mapped to the knowledge units of the 2014 IEEE/ACM Software Engineering Education Knowledge (SEEK) and the first and second level categories of the 2012 ACM Computing Classification System (CCS).</li> <li> <p><strong>posts_analysis.csv</strong>: Stack Overflow post data and metadata.</p> </li> <li> <p><strong>posts_aggregated_codes.csv</strong>: The aggregated codes that resulted from the manual analysis of the Stack Overflow posts by grouping individual keywords assigned to the posts.</p> </li> <li> <p><strong>survey_questionnaire.csv</strong>: The final survey questionnaire.</p> </li> <li> <p><strong>survey_responses.csv</strong>: Anonymized responses of the final survey questionnaire. (E-mail addresses have been excluded for privacy reasons.)</p> </li> </ul>
Doctoral Students' Educational Needs in Research Data Management: Quantitative Data of Perceived Importance and Current Competencies
<p>These data sets include numerically coded answers to Likert-like scale questions concerning the importance and perceived current research data management competencies of doctoral students. Interviewees were 35 doctoral students and faculty members. Interview forms are attached. The data is connected with the research article: https://doi.org/10.2218/ijdc.v16i1.684</p>
Covid-19 - Symptoms - Impact on quality of life and needs of affected people
<p>Dataset « Covid-19 - Symptoms - Impact on quality of life and needs of affected people ». The data came from an online study involving a sample of 639 participants resident in France affected by COVID-19 symptoms several days, weeks or months after infection. It was collected to provide characterization of a wide range of symptoms of COVID-19, their effects on quality of life and the needs of those affected.</p>
MainstreamBIO_Needs Analysis_Dataset2_2023.02.28_v1
<p>The dataset comprises the outcomes of 35 semi-structured interviews conducted with renowned experts in the bioeconomy domain. The primary objective of these interviews was to obtain comprehensive insights into various aspects of local bioeconomy development and its social acceptance. The experts were probed on multiple dimensions, including the prevailing framework conditions, existing needs, challenges, and market conditions related to bioeconomy practices. Furthermore, the interviews also delved into exploring nutrient recycling practices in the context of bioeconomy development. These in-depth conversations with experts were intended to gain a profound understanding of the subject matter and gather valuable information to advance research and decision-making in this field.</p>
MainstreamBIO_Needs Analysis_Dataset1_2023.02.28_v1
<p>The dataset comprises the findings of an online survey that aimed to assess awareness levels and perceptions related to the bioeconomy, biobased solutions, products, and nutrient circularity practices among a diverse group of stakeholders, including consumers.</p> <p>The results indicate notable variations both across the targeted countries and among different key-stakeholder groups. Concerning awareness and perceptions of bioeconomy development and biobased products and solutions, the primary challenges and requirements seem to revolve around economic factors, such as the lack of investments and limited access to essential finance. However, other significant determinants also play a role, including the absence of appropriate policy and regulatory frameworks governing the bioeconomy sector and issues pertaining to stakeholder engagement, particularly concerning a lack of relevant awareness.</p>
Dataset: Knowledge, information needs and behavior regarding HIV and sexually transmitted infections among migrants from sub-Saharan Africa living in Germany: Results of a participatory health research survey.
<p>Dataset for: Koschollek C, Kuehne A, Müllerschön J, Amoah S, Batemona-Abeke H, Dela Bursi T, Mayamba P, Thorlie A, Mputu Tshibadi C, Wangare Greiner V, Bremer V, Santos-Hövener C: Knowledge, information needs and behavior regarding HIV and sexually transmitted infections among migrants from sub-Saharan Africa living in Germany: Results of a participatory health research survey.</p> <p>This dataset has been described in a PLoS One paper and contains all data necessary to replicate the results presented within this paper (10.1371/journal.pone.0227178). Please cite both the paper as well as the DOI of this dataset if you make use of the data.</p>
spanichella/RP_EMSE_MCR_2019 v.1.0.1 Second release of of the replication Package for the paper "An Empirical Investigation of Relevant Changes and Automation Needs in Modern Code Review".
<p>Replication Package for the paper "An Empirical Investigation of Relevant Changes and Automation Needs in Modern Code Review"</p> <p>Structure</p> <pre><code>project_raw_data/ gerrit_review_comments.csv gerrit_review_changes.csv survey_raw_data/ google_forms_survey.pdf google_forms_survey.csv RQ1_taxonomy_mcr/ RQ1_inception_phase/ initial_taxonomy.pdf intermediate_taxonomy.pdf RQ1_definition_phase/ Q1.2_evaluation_survey.csv cram_classified.csv cram.pdf RQ2_automation_needs/ Q2.1-Q2.5_evaluation_survey.xlsx Q2.6-Q2.7_evaluation_survey.xlsx Q2.1-Q2.7_question_index.csv Now "RQ3_automated_support/" contain the results concerning RQ2.1 in the paper. content explained in the README.md file located in "RQ3_automated_support/README.md" </code></pre> <p>Contents of the Replication Package</p> <p><strong>project-raw-data/</strong> contains the data used for the creation of our taxonomies, it includes information about the ten open-source projects.</p> <ul> <li><code>gerrit_review_comments.csv</code> - information about all in-line review comments used for this paper</li> <li><code>gerrit_review_changes.csv</code> - information about all patches analyzed that contain the in-line comments</li> </ul> <p><strong>survey_raw_data/</strong> contains information about the survey conducted for the paper.</p> <ul> <li><code>google_forms_survey.pdf</code> - the distributed <em>Google Forms</em> of our survey</li> <li><code>google_forms_survey.csv</code> - all survey answers obtained from 52 survey participants</li> </ul> <p><strong>RQ1_taxonomy_mcr/</strong> contains information and data about the elicited taxonomies in our paper (RQ1).</p> <ul> <li><strong>RQ1_inception_phase/</strong> <ul> <li><code>initial_taxonomy.pdf</code> - initial taxonomy obtained in the inception phase of our paper</li> <li><code>intermediate_taxonomy.pdf</code> - intermediate taxonomy after integrating and merging the initial taxonomy with the one by Beller <em>et al</em> [1]</li> </ul> </li> <li><strong>RQ1_definition_phase/</strong> <ul> <li><code>Q1.2_evaluation_survey.csv</code> - relevant survey feedback with additional taxonomy categories integrated into <em>CRAM</em></li> <li><code>cram_classified.csv</code> - classified review comments (<code>gerrit_review_comments.csv</code>) into <em>CRAM</em></li> <li><code>cram.pdf</code> - <em>CRAM</em> taxonomy</li> <li><code>cram_classified_with_frequency_information2020.xls</code> - it contain the information used to compute the frequency of CRAM changes, derived by the analysis of the 211 commits</li> </ul> </li> </ul> <p><strong>RQ2_automation_needs/</strong> contains the encoded evaluation of the survey question Q2.1-2.7 for RQ2</p> <ul> <li><code>Q2.1-Q2.5_evaluation_survey.xlsx</code> - the encoded evaluation of the survey questions Q2.1-Q2.5 (used for the <em>Automation Needs</em> Section in the paper) and contains the following sheets: <ul> <li><strong>all Findings</strong>: Very detailed findings matrix distilled from all answers concerning possible automated solutions or general possibilities to achieve automation in MCR. Every feedback was analyzed and decomposed into single findings. These findings are grouped, into categories of our Taxonomy of Code Changes in MCR (CRAM). Red represent in the feedback-text where the corresponding category was distilled from.</li> <li><strong>unique Findings</strong>: As one participant could mention the same categories/solutions in multiple feedbacks, the following matrix is cleaned of any duplication of participant answers. Multiple feedbacks containing the same information by one participant were removed, leaving only distinct occurances.</li> <li><strong>aggregated by Solution</strong>: Aggregated feeback clustered into abstracted solutions and the number of times participants mentioned the solution.</li> <li><strong>aggregated by Taxonomy</strong>: Aggregated feeback grouped by low-level categoried in CRAM.</li> </ul> </li> <li><code>Q2.6-Q2.7_evaluation_survey.xlsx</code> - the encoded evaluation of the survey questions Q2.6-Q2.7 (used for the <em>Automation Needs</em> Section in the paper) and contains the following sheets: <ul> <li><strong>all Findings</strong>: Very detailed findings matrix distilled from all answers concerning possible techniques, approaches and data to achieve automation in MCR. Every feedback was analyzed and decomposed into single findings. These findings are grouped, into categories of our Taxonomy of Code Changes in MCR (CRAM). Red represent in the feedback-text where the corresponding category was distilled from.</li> <li><strong>unique Findings</strong>: As one participant could mention the same categories/solutions in multiple feedbacks, the following matrix is cleaned of any duplication of participant answers. Multiple feedbacks containing the same information by one participant were removed, leaving only distinct occurances.</li> <li><strong>aggregated by low-level taxonomy</strong>: Aggregated mentionings of approaches/data by developers in the survey grouped by low-level taxonomy category.</li> <li><strong>aggregated by high-level taxonomy</strong>: Aggregated mentionings of approaches/data by developers in the survey grouped by high-level taxonomy category.</li> </ul> </li> <li><code>Q2.1-Q2.7_question_index.csv</code> - table of IDs given to each participant-question pair for Q2.1-Q2.7 in order to trace back the feeback.</li> <li><code>cram_survey-with_criticality_and_feasibility2020.xls</code> and <code>cram_survey-with_relevance_and_completeness_information2020.xls</code>: they contain we results of the survey, involving 14 additional participants (12 developers and 2 researchers), not involved in the aforementioned survey, and performed to qualitatively assess the relevance and completeness of the identified MCR change types as well as assess how critical and feasible to implement are some of the identified techniques to support MCR activities.</li> </ul> <p><strong>RQ2_1_automated_support/</strong> (or <strong>RQ3_automated_support/</strong> )- content explained in the README.md file located in "RP_EMSE_MCR_2019/tree/master/EMSE_MCR_2019/RQ3_automated_support/README.md"</p> <p>References</p> <p>[1] Moritz Beller, Alberto Bacchelli, Andy Zaidman, and Elmar Juergens. 2014. Modern code reviews in open-source projects: which problems do they fix?. In Proceedings of the 11th Working Conference on Mining Software Repositories (MSR 2014). ACM, New York, NY, USA, 202-211. DOI: <a href="http://dx.doi.org/10.1145/2597073.2597082">http://dx.doi.org/10.1145/2597073.2597082</a></p>
Information Needs in Contemporary Code Review - Appendix
<p>Contemporary code review is a widespread practice used by software engineers to maintain high software quality and share project knowledge. However, conducting proper code review takes time and developers often have limited time for review. In this paper, we aim at investigating the information that reviewers need to conduct a proper code review, to better understand this process and how research and tool support can make developers become more effective and efficient reviewers. Previous work has provided evidence that a successful code review process is one in which reviewers and authors actively participate and collaborate. In these cases, the threads of discussions that are saved by code review tools are a precious source of information that can be later exploited for research and practice. In this paper, we focus on this source of information as a way to gather reliable data on the aforementioned reviewers’ needs. We manually analyze 900 code review comments from three large open-source projects and organize them in categories by means of a card sort. Our results highlight the presence of seven high-level information needs, such as knowing the uses of methods and variables declared/modified in the code under review. Based on these results we suggest ways in which future code review tools can better support collaboration and the reviewing task. Appendix material.</p>
Projected freshwater needs of the energy sector in the European Union and the UK
<p>This dataset contains the projections of future freshwater demands of the energy sector (primary energy supply and transformation in power plants and oil refineries) in the EU and the United Kingdom for the period 2015-2050, in 5-year steps. The projections are estimated by the combination of water withdrawal and consumption factors for different energy technologies under six energy scenarios, at national and NUTS2 level, as described in the JRC technical report: Hidalgo Gonzalez, I., Medarac, H. and Magagna, D., Projected freshwater needs of the energy sector in the European Union and the UK, EUR 30266 EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-19829-1 (online), doi:10.2760/796885 (online), JRC121030.</p>
Data and code for the manuscript: "Varying richness need not imply non-random species co-occurrence: implications for specifying null models"
<p>Data and R code for the manuscript "Varying richness need not imply non-random species co-occurrence: implications for specifying null models".</p>
H2M survey data on commercialisation training needs of Health Researchers
<p>Health-2-Market was a 3-year long Coordination and Support Action, funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration (Grant Agreement No 305532). H2M aimed at providing training and individual support to Health / Life Sciences researchers in the process of translating their research results into successful new business ideas.</p> <p>With a view to properly adapting the training offer of the project to the needs of Health / Life Sciences researchers in terms of entrepreneurship and business skill development a Training Needs Analysis (TNA) was conducted. In this context, H2M launched an online survey targeted at Health / Life Sciences researchers who have been involved in EU health projects. In particular, the objectives of the survey were:</p> <ul> <li>To formulate a descriptive understanding of various aspects of commercialisation and training needs of the main target group of the project;</li> <li>To divide this target group into homogeneous sub-groups (clusters) along a number of key characteristics such as demographics, commercialisation attitudes and needs;</li> <li>To understand preferences and importance of different aspects and needs through the analysis of: <ul> <li>Knowledge areas that can influence commercialisation behaviour;</li> <li>Training modalities that have an effect on the intention to participate and /or on the perception of the usefulness of a commercialisation training;</li> <li>Variations identified over different sub-groups.</li> </ul> </li> </ul> <p>The survey was dispatched to a database composed of 7,991 unique contacts of participants in previous health projects, accessed through the Directorate General for Health and Food Safety of the European Commission. The initial aim of at least 50 complete responses was overwhelmingly surpassed: 637 respondents completed the survey in full.</p> <p>The “H2M survey data on commercialisation training needs of Health Researchers” dataset contains the raw, anonymised data that were collected from these respondents, along with the questionnaire items that were utilised.</p>
Multiple dimensions of phylogenetic diversity are needed to explain the complex aboveground-belowground diversity relationships
<p>The complex relationship between aboveground and belowground diversity and whether they act as surrogates for one another remains unresolved. Increasing evidence suggests that investigating phylogenetic diversity could provide valuable insights into the interplay between plants and soil microbes, but the proliferation of phylogenetic diversity metrics has hindered comparative studies and the identification of general patterns. To overcome this challenge, we implemented a multi-dimensional framework that classifies phylogenetic diversity metrics into three dimensions: richness, divergence, and regularity, each of which captures different ecological aspects of species differences. Then we applied this framework to investigate the relationship between above and belowground diversity in a subtropical forest in Eastern China. We found that phylogenetic diversity of plant and soil microbes, including bacteria and fungi, were more strongly correlated at the richness and regularity dimension compared with divergence dimension. Further analyses revealed that these observed correlation patterns can be attributed to the influence of soil total phosphorus content, which is the limiting factor of plant and microbial phylogenetic diversity at richness and regularity dimensions. Together, our study demonstrated the necessity of using a multi-dimensional approach to advance our understanding of the complex relationships between plant and soil microbial biodiversity.</p>
Supplementary Material - "Explanations in Everyday Software Systems: Towards a Taxonomy for Explainability Needs" (RE'24)
<p>This artifact contains the questionnaire, coding guidelines and resulting coded data set for the research paper "Explanations in Everyday Software Systems: Towards a Taxonomy for Explainability Needs" submitted to and accepted at the 32nd IEEE International Requirements Engineering 2024 conference. This artifact does not contain any automated analyses or tools.</p>
"How much OWL do you need to know to make sense of building ontologies?" supplementary material
<p>This records contains the ontologies analized in the “How much OWL do you need to know to make sense of building ontologies?” paper presented at “LDAC2024 - Linked Data in Architecture and Construction” workshop. It also includes the resulting estructures and patterns identified as well as a library of graphical pattersn generated with the Chowlk notation (https://chowlk.linkeddata.es/).</p>
MS2Query pre-trained datasets needed for library matching
<p>The models, embeddings, sqlite file with metadata and classifiers identifiers needed for running MS2Query (https://github.com/iomega/ms2query)</p>
Replication Package of: "From Anecdote to Evidence: The Relationship Between Personality and Need for Cognition"
<p>Several anecdotes suggests that software engineers enjoy engaging in solving puzzles and other cognitive efforts. This tendency to engage in and enjoy effortful thinking is referred to as a person's 'need for cognition.' An open question is, however, whether developers differ from the general population in their scores of need for cognition. To address this question, we conducted a large-scale sample study of 483 software engineers. Personality plays a significant role in people's behavior and is stable over time, and is therefore considered a defining characteristic of individuals. We analyzed the data using multiple Bayesian linear regression analyses. The results indicate that ca. 33% of variation in developers' need for cognition can be explained by personality traits. Given the importance of human factors for software developer performance in general, and problem solving skills in particular, answering this question has substantial implications, such as recruitment & retention, working behaviour, and teaming.</p>
Data for Horowitz et al. (2022). The Energy System Transformation Needed to Achieve the U.S. Long-Term Strategy
<p>Data repository for Horowitz, et al. 2022, "The Energy System Transformation Needed to Achieve the U.S. Long-Term Strategy"</p> <p>All data shown in the paper is included here. Data includes results from:</p> <p>1. U.S. LTS GCAM scenarios (labeled "GCAM")<br> 2. U.S. LTS NEMS scenarios (labeled "NEMS")<br> 3. Princeton's Net-Zero America scenarios (labeled "NZA")<sup>a</sup><br> 4. Williams et al. (2020) scenarios (labeled "Williams")<sup>b</sup></p> <p><br> Results are included in the following files:</p> <p>1. waterfall.csv - Figure 1. Emissions decomposition by scenario. GCAM only.<br> 2. clean_fuels.csv - Figure 2. Clean fuel (bioliquids, biogas, and blue/green hydrogen) consumption. All models.<br> 3. coal.csv - Figure 2. Primary energy consumption of coal without CCS. All models.<br> 4. ZEV_stock.csv - Figure 2. Zero-emission vehicle percentage of light-duty vehicle stock. All models.<br> 5. ghg_by_type.csv - Figure 3. Greenhouse gas emissions by gas/source. GCAM only.</p> <p> </p> <p>Reference:</p> <p>a) Larson, E., Greig, C., Jenkins, J.,Mayfield, E., Pascale, A., Zhang, C., Drossman, J., Williams, R., Pacala, S., Socolow, R., et al. (2021). Net-zero America: Potential pathways, infrastructure, and impacts. (Princeton University).</p> <p>b) Williams, J. H., Jones, R. A., Haley, B., Kwok, G., Hargreaves, J., Farbes, J., & Torn, M. S. (2021). Carbon-Neutral Pathways for the United States. AGU Advances, 2, e2020AV000284. <a href="https://doi.org/https://doi.org/10.1029/2020AV000284">https://doi.org/https://doi.org/10.1029/2020AV000284</a>.</p>
Supplementary data to the Baseline Methodological User Needs Analysis
<p>Supplementary data to the Baseline Methodological User Needs Analysis</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.