Find research datasets worth reusing

opencc-by-4.0Aug 2022View details →

A lack of open data standards for large infrastructure projects hampers social-ecological research in the Brazilian Amazon

List of papers used in literature review for "A lack of open data standards for large infrastructure projects hampers social-ecological research in the Brazilian Amazon"

Fig. 7 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 7. Ordination plot of the correspondence analysis (first two axes) based on fishermen's answers about fishing season of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

Fig. 6 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 6. Ordination plot of the correspondence analysis (first two axes) based on fishermen's answers about migratory routes of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

Fig. 4 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 4. Trophic chain based on those food items and predators most cited by fishermen in the southeastern Brazilian coast for a) reef fishes and b) pelagic fishes. Numbers are percent of interviewed fishermen who mentioned each feeding interaction. Fish sizes are not in scale. Those feeding interactions that agree with reported feeding habits of these fishes in the biological literature are marked *(Randall, 1967; Berkeley & Houde, 1978; Menezes & Figueiredo, 1980; Sazima, 1986; Pipitone & Andaloro, 1995; Barreiros & Santos, 1998; Vasconcellos & Gasalla, 2001; Silvano, 2001; Silvano & Güth, 2006; Figueiredo & Vieira, 2005; Gibran, 2007).

Fig. 3 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 3. Main habitats of fishes according to fishermen in the southeastern Brazilian coast: percentages of fishermen who mentioned each habitat category are in Appendix 1. Double-headed arrows indicate that fishes occur in both habitats in horizontal space (e.g. open ocean and reefs), up and down arrows indicate that fishes occur in both habitats in vertical space (e.g., near the bottom and at the surface). Fish sizes are not in scale.

Fig. 1 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 1. Ordination plot of the correspondence analysis (first two axes) based on fishermen answers about uses of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

Fig. 2 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 2. Ordination plots of the correspondence analysis (first two axes) based on fishermen answers about fishing methods and baits of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

Fig. 8 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 8. Ordination plot of the correspondence analysis (first two axes) based on fishermen's answers about reproductive (spawning) season of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

Fig. 5 in Fishermen's local ecological knowledge on Southeastern Brazilian coastal fishes: contributions to research, conservation, and management

Fig. 5. Ordination plot of the correspondence analysis (first two axes) based on fishermen's answers about migratory behavior of the nine studied fish species in the southeastern Brazilian coast: Absa = Abudefduf saxatilis; Boru = Bodianus rufus; Cala = Caranx latus; Epma = Epinephelus marginatus; Haau = Haemulon aurolineatum; Heba = Hemiramphus balao; Kysp = Kyphosus spp.; Mifu = Micropogonias furnieri; Sesp = Seriola spp.

openother-openFeb 2024View details →

Regression-Test History Data for Flaky Test-Research, Dataset

The dataset comprises developer test results of Maven projects with flaky tests across a range of consecutive commits from the projects' git commit histories. The Maven projects are a subset of those investigated in an <a href="https://doi.org/10.1145/3428270">OOPSLA 2020 paper</a>. The commit range for this dataset has been chosen as the flakiness-introducing commit (FIC) and iDFlakies-commit (see the OOPSLA paper for details). The commit hashes have been obtained from the <a href="https://github.com/TestingResearchIllinois/idoft/blob/main/tic-fic-data.csv">IDoFT dataset</a>. The dataset will be presented at the <a href="https://conf.researchr.org/home/icse-2024/ftw-2024">1st International Flaky Tests Workshop 2024 (FTW 2024)</a>. Please refer to <a href="https://doi.org/10.1145/3643656.3643901">our extended abstract</a> for more details about the motivation for and context of this dataset. The following table provides a summary of the data. <table> <tbody> <tr> <td>Slug (Module)</td> <td>FIC Hash</td> <td>Tests</td> <td>Commits</td> <td>Av. Commits/Test</td> <td>Flaky Tests</td> <td>Tests w/ Consistent Failures</td> <td>Total Distinct Histories</td> </tr> <tr> <td>TooTallNate/Java-WebSocket</td> <td>  822d40</td> <td>146</td> <td>  75</td> <td>  75</td> <td>24</td> <td>   1</td> <td>2.6x10^9</td> </tr> <tr> <td>apereo/java-cas-client (cas-client-core)</td> <td>  5e3655</td> <td>157</td> <td>  65</td> <td>61.7</td> <td>  3</td> <td>   2</td> <td>1.0x10^7</td> </tr> <tr> <td>eclipse-ee4j/tyrus (tests/e2e/standard-config)</td> <td>  ce3b8c</td> <td>185</td> <td>  16</td> <td>  16</td> <td>12</td> <td>   0</td> <td>   261</td> </tr> <tr> <td>feroult/yawp (yawp-testing/yawp-testing-appengine)</td> <td>  abae17</td> <td>    1</td> <td>191</td> <td>191</td> <td>  1</td> <td>   1</td> <td>       8</td> </tr> <tr> <td>fluent/fluent-logger-java</td> <td>   5fd463</td> <td>  19</td> <td>131</td> <td>105.6</td> <td>11</td> <td>   2</td> <td>8.0x10^32</td> </tr> <tr> <td>fluent/fluent-logger-java</td> <td>  87e957</td> <td>  19</td> <td>160</td> <td>122.4</td> <td>11</td> <td>   3</td> <td>2.1x10^31</td> </tr> <tr> <td>javadelight/delight-nashorn-sandbox</td> <td>  d0d651</td> <td>  81</td> <td>113</td> <td>100.6</td> <td>  2</td> <td>   5</td> <td>4.2x10^10</td> </tr> <tr> <td>javadelight/delight-nashorn-sandbox</td> <td>  d19eee</td> <td>  81</td> <td>  93</td> <td>83.5</td> <td>  1</td> <td>   5</td> <td>2.6x10^9</td> </tr> <tr> <td>sonatype-nexus-community/nexus-repository-helm</td> <td>  5517c8</td> <td>  18</td> <td>  32</td> <td>  32</td> <td>  0</td> <td>   0</td> <td>     18</td> </tr> <tr> <td>spotify/helios (helios-services)</td> <td>    23260</td> <td>190</td> <td>448</td> <td>448</td> <td>  0</td> <td> 37</td> <td>   190</td> </tr> <tr> <td>spotify/helios (helios-testing)</td> <td>  78a864</td> <td>  43</td> <td>474</td> <td>474</td> <td>  0</td> <td>   7</td> <td>     43</td> </tr> </tbody> </table>   The columns are composed of the following variables: <ul> <li>Slug (Module): The project's GitHub slug (i.e., the project's URL is https://github.com/{Slug}) and, if specified, the module for which tests have been executed.</li> <li>FIC Hash: The flakiness-introducing commit hash for a known flaky test as described in this OOPSLA 2020 paper. As different flaky tests have different FIC hashes, there may be multiple rows for the same slug/module with different FIC hashes. </li> <li>Tests: The number of distinct test class and method combinations over the entire considered commit range.</li> <li>Commits: The number of commits in the considered commit range</li> <li>Av. Commits/Test: The average number of commits per test class and method combination in the considered commit range. The number of commits may vary for each test class, as some tests may be added or removed within the considered commit range.</li> <li>Flaky Tests: The number of distinct test class and method combinations that have more than one test result (passed/skipped/error/failure + exception type, if any + assertion message, if any) across 30 repeated test suite executions on at least one commit in the considered commit range.</li> <li>Tests w/ Consistent Failures: The number of distinct test class and method combinations that have the same error or failure result (error/failure + exception type, if any + assertion message, if any) across all 30 repeated test suite executions on at least one commit in the considered commit range.</li> <li>Total Distinct Histories: The number of distinct test results (passed/skipped/error/failure + exception type, if any + assertion message, if any) for all test class and method combinations along all commits for that test in the considered commit range.</li> </ul>

opencc-by-4.0Feb 2024View details →

Overcoming confusion and stigma in habitat fragmentation research - supplementary data and R code

Data and code necessary to produce results and figures for the manuscript: Riva, Koper and Fahrig (2024). "Overcoming confusion and stigma in habitat fragmentation research". Biol Rev. Accepted conditional on minor revisions.

opencc-by-4.0Feb 2024View details →

Research Data: Facial Expression Recognition under Visual Field Restriction

This dataset contains the following files: - view_trial.xlsx: Excel spreadsheet containing data from individual trials. - view_participant.xlsx: Excel spreadsheet containing data aggregated at the participant level. - consensus.xlsx: Excel spreadsheet containing consensus data analysis. - image_id_list.txt: Text file listing the IDs of the images used in the study from The Karolinska Directed Emotional Faces (KDEF); https://kdef.se/. These files provide comprehensive data used in the research project titled "Exploring the Visual Field Restriction in the Recognition of Basic Facial Expressions: A Combined Eye Tracking and Gaze Contingency Study" conducted by M. B. Urtado, R. D. Rodrigues, and S. S. Fukusima. The dataset is intended for analysis and replication of the study's findings. Please, when using these data, we kindly request citing the following article: Urtado, M.B.; Rodrigues, R.D.; Fukusima, S.S. Visual Field Restriction in the Recognition of Basic Facial Expressions: A Combined Eye Tracking and Gaze Contingency Study. Behavioral Sciences 2024, 14, 355. <a href="https://doi.org/10.3390/bs14050355">https://doi.org/10.3390/bs14050355</a> The study was approved by the Research Ethics Committee (CEP) of the University of São Paulo (protocol code 41844720.5.0000.5407).

opencc-by-4.0Jan 2024View details →

Data and code from: Unoccupied aerial systems adoption in agricultural research

<div> </div> This repository contains data and code supporting the findings of the study on the adoption of Unoccupied Aerial Systems (UAS) in agricultural research as reported by Lachowiec et al (2024) in The Plant Phenome Journal. We collected data through an online survey as well as through in person interviews. <div> <h2>Description of Repository Contents</h2> </div> <div> <h3>Data</h3> </div> Data are in the <code>/data</code> directory: <ul> <li><code>Ag_Drones_Codebook_14Jun2023.pdf</code>: Codebook providing detailed descriptions of survey questions and coding schemes. This contains detailed descriptions of the content of the two CSV files listed below.</li> <li><code>Results_Ag_Drones_2021_Survey.csv</code>: This is raw survey data collected from agricultural researchers regarding their use of UAS technology.</li> <li><code>countries_code.csv</code>: Country codes used in the survey data for respondent location.</li> <li><code>interviews/</code>: A directory containing interview transcripts and summary provided as both Microsoft Word and plain text (Markdown) formats, specifically: <ul> <li>Notes from nine one on one interviews named <code><interviewee last name>)UAS_Interview.[md|docx]</code></li> <li>A summary document, <code>Feldman_AG2PI_InterviewSummary_2022-08-10.docx</code>.</li> </ul> </li> </ul> <div> <h3>Code</h3> </div> Code used to process data and generate the manuscript's analysis and figures. <ul> <li><code>data_code.R</code>: R Script for preprocessing and cleaning the survey data.</li> <li><code>dataAnalysis.R</code>: R script for statistical analysis and visualization of survey results.</li> </ul> <div> <h2>Citing this work</h2> </div> This repository contains data and code to support the manuscript: <blockquote> Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Unoccupied aerial systems adoption in agricultural research. Zenodo. The Plant Phenome Journal Volume(Issue), pages 00. doi:DOI </blockquote> If you use the data or code from this repository, please also cite: <blockquote> Lachowiec, J., Feldman, M.J., Matias, F.I., LeBauer, D., Gregory, A. (2024). Data and code from: Unoccupied aerial systems adoption in agricultural research. Zenodo. doi:10.5281/zenodo.10573428 </blockquote> And consider contributing cleaned data and code to this repository. <div> <h2>Acknowlegements and Support</h2> </div> Acknowledgments We thank all survey respondents for their participation. We acknowledge the Montana State University HELPS lab for aiding in the development and implementation of the survey. Funding This research was supported by the intramural research program of the U.S. Department of Agriculture, National Institute of Food and Agriculture, Agricultural Genome to Phenome Initiative (2020-70412-32615 and 2021-70412-35233). The findings and conclusions in this preliminary presentation have not been formally disseminated by the U. S. Department of Agriculture and should not be construed to represent any agency determination or policy.

Open dataset of 20 interviews with senior service designers and managers for the Empathy Business research project

The aim of the Empathy Business research project (2023-2024) led by the University of Lapland focused on how to digitalize services and business prototyping through creativity. The research named challenges as well as design methods for developing digital tools for meeting the future needs of service design and business development. In total, 20 interviews among senior service designers and managers located in Europe, Latin America and Asia were conducted during spring 2023. The interviews provide perspectives related to the future of service design as a practise, the skills required and further issues of relevance for professionals in the field. Based on affinity diagramming eight main clusters were named: Sustainability, Business compatibility, New tools, Designer’s skills, Art-based methods, People in the centre, Online workshops, and Physical workshops. This data set includes an anonymized list of the interviewees, affinity diagram post-it notes of the interviews, short descriptions of the main clusters and an internet link to the online affinity diagram on Miro board. The materials provided initial insights for developing Proof-of-Concepts for digitized interfaces, such as suitable plugins, 3D-based photorealistic solutions, or an application with the potential to be used in service design and service prototyping contexts as well as in other development processes within and across organizations.

DailySense: a Daily Self-reports and Physiological Signals Sensing Dataset for Subjective Health Research in the Wild

Description: This is a daily self-reports and physiological signals sensing dataset for subjective health research in the wild (DailySense). This is a dataset from a consecutive 14-day experiment in real-life settings composed of smartphone-based subjective psychological evaluation and physiological sensing. A Total of 36 healthy Japanese adult remote workers (mean±SD, 35.8±7.5; range, 27–58 years; 21 male and 15 female participants) participated in the experiment through two terms (1st term [1], 18 participants from a Japanese company without rewards; 2nd term, 18 participants from a participant's pool with rewards). The study protocol was approved by the internal review board of Research & Development Group, Hitachi, Ltd., and was conducted in accordance with the Declaration of Helsinki. All participants provided informed consent prior to enrollment in this study. The permission to share the raw data with participants' anonymization was included in this approval and explicitly obtained in that informed consent. This dataset contains the following data:  - pre- and post-term data of     - responses to self-reporting questionnaires (i.e., the Japanese versions of NEO-FFI, STAI, CES-D, CFS, PSQI, WHO-QOL, and SF-36v2©).     - demographics     - survey regarding this experiment - mid-term data of     - responses to emotional self-reports (i.e., Affective Slider and I-PANAS-SF) and their behavior in ESM 6 times/day at maximum     - responses to subjective health (i.e., degree of fatigue, stress, anxiety, depression, and sleeplessness), wake-up/in-bed times, and work style 1time/day     - continuously monitored physiological data (i.e., EDA, PPG, Acc) and event tags obtained by a wristband sensor (E4 wristband, Empatica Inc.) during their waking hours     - response profile data estimated using the proposed method     - log data of an experience sampling support system (exkuma, Japan Experience Sampling Method Association) Details of data are mentioned in an xlsx file of the root directory. Due to the limitation of questionnaires, descriptions of original instructions of items in each questionnaire are omitted. The details of the experiment are described in [1][2]. Note that, in [1], participant #29 was excluded due to insufficient physiological data quality. In addition, in [2], participant #47 was excluded since he did not complete a personality questionnaire, but #29 was included since he completed responses to all the questionnaires.   License: This dataset is made available by Hitachi, Ltd. under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.   References: If you use this dataset, please cite the following papers: [1] Shunsuke Minusa, Chihiro Yoshimura, and Hiroyuki Mizuno "Emodiversity evaluation of remote workers through health monitoring based on intra-day emotion sampling," Front. Public Heal., vol. 11, no. August, pp. 1–12, 2023, doi: <a href="https://doi.org/10.3389/fpubh.2023.1196539" target="_blank" rel="noopener">10.3389/fpubh.2023.1196539</a> [2] Shunsuke Minusa, Tadayuki Matsumura, Kanako Esaki, Yang Shao, Chihiro Yoshimura, and Hiroyuki Mizuno, "Response Style Characterization for Repeated Measures Using the Visual Analogue Scale," arXiv preprint <a href="https://arxiv.org/abs/2403.10136" target="_blank" rel="noopener">arXiv:2403.10136</a>, 2024.   Contact: If there is any problem, please contact us: <ul> <li>Shunsuke Minusa, <a href="mailto:shunsuke.minusa.hd@hitachi.com" target="_blank" rel="noopener">shunsuke.minusa.hd@hitachi.com</a></li> </ul>

opencc-by-4.0Dec 2023View details →

(Processed data) How do Spanish educational researchers use X's platform to promote the dissemination of scientific knowledge: a descriptive study: a descriptive study

Processed data used in the article 'How do Spanish educational researchers use X's platform to promote the dissemination of scientific knowledge: a descriptive study', from the project Comscienciaeduspain (FCT-20-15761), executed with the collaboration of the Spanish Foundation for Science and Technology – Ministry of Science and Innovation.

Accelerating Digital Skills for Music Researchers - Processing Text-Based Corpora for Musical Discourse Analysis - Episode 2

Dataset containing three subgenre-specific .xlsx files for the exercises in Episode 2 of the <a href="https://acceleratingdigitalskills.github.io/Processing-Text-Based-Corpora/">Processing Text-Based Corpora for Musical Discourse Analysis</a> lesson of the <a href="https://acceleratingdigitalskills.org/">Accelerating Digital Skills for Music Researchers</a> project. The original data was collected from <a href="https://boomkat.com/">Boomkat.com</a> with permission.

opencc-by-4.0Apr 2024View details →

Extended Data for "A Scoping Review of Infertility Research conducted in the Republic of Ireland"

This dataset contains the following files: ·         Extended Data 1: Changes to Methodology from Protocol ·         Extended Data 2: List of Included Documents (n=105); List of Potentially Relevant Studies that were not Located (n=8) ·         Extended Data 3: Data Extraction Table ·         Extended Data 4: Completed PRISMA ScR Checklist These files comprise extended data for the paper: Earley, A., O’Dea, A., Madden, C., O’Connor, P., Byrne, D., Murphy, AW., & Lydon, S (2024). A Scoping Review of Infertility Research conducted in the Republic Of Ireland. Under review.

Research Data for Comparative Evaluation of RT-PCR and Antigen-based Rapid Diagnostic Tests (Ag-RDTs) for SARS-CoV-2 Detection: Performance, Variant Specificity, and Clinical Implications

This dataset represents laboratory findings for the comparative evaluation of the diagnostic performance of Ag-RDTs (Flourescence Immunoassay and Lateral Flow Immunoassay) with RT-PCR