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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>
Italian TikTok users online behaviour patterns and social attitudes (survey)
<p>Survey of 500 young TikTok users (18-35) in Italy covering online behaviour patterns and social attitudes</p>
Donor-acceptor complex formation by social self-sorting of polycyclic aromatic hydrocarbons and perylene bisimides
<p>Additional data to report <a href="https://doi.org/10.1039/D3CC03704E">https://doi.org/10.1039/D3CC03704E</a></p> <p>Self-assembly versus complexation with polycyclic aromatic hydrocarbon (PAH) guest molecules is studied for a series of perylene bisimides (PBIs). Bulky imide substituents at the PBI guide their self-assembly into dimer aggregates with null-type exciton coupling. Host-guest titration experiments with perylene and triphenylene PAHs afford 1:1 and 1:2 complexes whose properties are studied by single crystal X-ray analysis and UV/Vis and fluorescence spectroscopy.</p>
Cognition in Social Engineering Empirical Research: a Systematic Literature Review
<p># Description of contents</p> <p>This repository contains the codebook, dataset and analysis scripts in R used for the following publication: Pavlo Burda, Luca Allodi, Nicola Zannone. "Cognition in Social Engineering Empirical Research: a Systematic Literature Review". ACM Transactions on Computer-Human Interaction (TOCHI).<br> The repository consists of the following files:</p> <p>## dataset_and_codebook.xlsx contains the dataset, the codebook and a detailed description of contents.</p> <p>## scripts/ contains the R scripts used for the analysis</p> <p>## readme.txt contains this readme</p> <p><br> # Dataset and codebook</p> <p>The dataset_and_codebook.xlsx contains the following sheets:</p> <p>## Codebook<br> Contains a detailed description of the dataset (tables, columns, fields, etc.).<br> The codebook describes the concepts and variables that are present in the dataset. This includes explanations on meaning, numerical values, classification schemes and labels.</p> <p>## Hypotheses table <br> Contains the hypotheses for all analyzed papers and is used in the results of the paper. <br> Each row is a hypothesis of an included paper, cells contain one or more values (e.g., value1,value2,...) with or without sub values (e.g., value1,value2(sub-value1, ...)). Any content that is in square brackets [] is ignored in the analysis. Empty cells mean that there is no applicable value for that column.</p> <p>## Papers table<br> Contains the analyzed papers and is used in the results of the paper. It is also used in the overview table (Table 6) in Appendix C.<br> Each row is an included paper, cells contain up to two values (e.g., value1, value2) or the word 'multiple' in case of more than two values. Empty cells mean that there is no applicable value for that column.</p> <p>## Values table <br> Contains the description of cell values of 'Hypotheses' and 'Papers' and sub-values (specific variables in a study) that belong to a value. <br> It has a hierarchical structure from left to right where each field on the right column falls under the first non-empty field on the immediate left-top.</p> <p><br> # Reproducing results with scripts/ (generate figures)<br> To run the R scripts included in the 'scripts' directory it is sufficient to follow the instructions in and run the 'RUN_ALL_SCRIPTS.R' in 'scripts' directory.<br> The scripts use the TSV (Tab Separated Values) format of the dataset, which is the exact copy of the 'Papers' and 'Hypotheses' tables in the 'dataset_and_codebook.xlsx' file.<br> The resulting figures are stored in the 'scripts/results' directory.</p>
Physical, Social, and Biological Attributes for Improved Understanding and Prediction of Wildfires: FPA FOD-Attributes Dataset
<p><strong>Wildfires are increasingly impacting social and environmental systems in the United States. The ability to mitigate the undesirable effects of wildfires increases with the understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis-Fire Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the contiguous United States (CONUS). FPA FOD v6 contains information on the location, jurisdiction, discovery time, cause, and final size of >2.2 million wildfires from 1992-2020 in CONUS. For each wildfire, we added physical (e.g., weather, climate, topography, infrastructure), biological (e.g., land cover, normalized difference vegetation index), social (e.g., population density, social vulnerability index), and administrative (e.g., national and regional preparedness level, jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models.</strong></p>
User Study Data for Paper "A case study in designing trustworthy interactions: implications for socially assistive robotics"
<p>Experimental data collected for the user study described in Frontiers paper "A case study in designing trustworthy interactions: implications for socially assistive robotics" by Mengyu Zhong et al. Citation: <i>Zhong, Mengyu, et al. "A case study in designing trustworthy interactions: implications for socially assistive robotics." Frontiers in Computer Science 5.1152532 (2023). </i></p>
ES12 - Social Housing - Candeleda (Spain)
<p>Data files for building: ES12 - Social Housing - Candeleda (Spain)</p><p>Languages: Spanish, English</p><p>These files are part of the public benchmark repository created as a part of the crossCert EU project. </p><p>This repository contains curated building data, certificate results and, where available, measured performance results. The repository is publicly available so that it can be used as a testbench for new Energy Performance Certificate (EPC) procedures.</p><p>The files are organised in the following folders (note that not all files are always provided):</p><ol><li>Main data and Results, with:<ol><li>Neutral data inventory.</li><li>Neutral results report.</li><li>Original EPC certificate.</li></ol></li><li>Energy Consumption Data, with:<ol><li>Files, where available, with energy consumption data for the building, which can be used for validation of models and EPC results.</li></ol></li><li>Drawings<ol><li>Building drawings which can be used as an aid for generating the EPC, or for creating dynamic energy consumption models.</li></ol></li><li>Other Data<ol><li>Any other data that can be useful for the purposes of creating or validating an EPC or an energy consumption dynamic model for the building.</li></ol></li><li>Dynamic Model<ol><li>Data to run a dynamic model of the building, if available.</li></ol></li></ol><p>The files have been redacted to exclude confidential information. </p>
ES11 - Social housing - Simancas (Spain)
<p>Data files for building: ES11 - Social housing - Simancas (Spain)</p><p>Languages: Spanish, English</p><p>These files are part of the public benchmark repository created as a part of the crossCert EU project. </p><p>This repository contains curated building data, certificate results and, where available, measured performance results. The repository is publicly available so that it can be used as a testbench for new Energy Performance Certificate (EPC) procedures.</p><p>The files are organised in the following folders (note that not all files are always provided):</p><ol><li>Main data and Results, with:<ol><li>Neutral data inventory.</li><li>Neutral results report.</li><li>Original EPC certificate.</li></ol></li><li>Energy Consumption Data, with:<ol><li>Files, where available, with energy consumption data for the building, which can be used for validation of models and EPC results.</li></ol></li><li>Drawings<ol><li>Building drawings which can be used as an aid for generating the EPC, or for creating dynamic energy consumption models.</li></ol></li><li>Other Data<ol><li>Any other data that can be useful for the purposes of creating or validating an EPC or an energy consumption dynamic model for the building.</li></ol></li><li>Dynamic Model<ol><li>Data to run a dynamic model of the building, if available.</li></ol></li></ol><p>The files have been redacted to exclude confidential information. </p>
Spatial and Social Behavior of Acanthurus triostegus on Moorea (French Polynesia) and Palmyra Atoll (USA), 2017-2018
These data describe the schooling behavior of coral reef fish on Moorea (French Polynesia) and Palmyra Atoll (USA) in 2017 and 2018. Data are grouped into two sets of observations: 1) surveys measuring the abundance of reef fish and the proportion of those fish occurring in schools, and 2) behavioral observations including time spent grazing and GPS tracks of schooling and solitary Acanthurus triostegus.
Adirondack Public Good Events Database: Natural Resource, Environmental, Economic and Recreation Policy and Common Pool Resources for a Social-Ecological System in Adirondack Park, New York, USA, 1760-2020.
I assembled this dataset from various published sources to evaluate how the social-ecological system (SES) in Adirondack Park, New York changed through time and the interplay of public goods (Common Pool Resources, CPRs), public land rules and private land rights, and related concepts over 260 years (1760-2020). The database was the basis for a doctoral dissertation titled "Blue Lining: Assessing the Resilience of Adirondack Park, New York Using Polycentricity and Panarchy Frameworks." The goal of the dissertation was to assess patterns and changes in institutional rules, actors and arrangements before and after establishment of the public Adirondack Forest Preserve in 1885 and Adirondack Park in 1892 as those actors and rules were modified and as both internal and external events influenced the SES as it moved through different phases of the adaptive cycle through space and time (see panarchy). Using the database, I identified which organizations and events contributed to natural resource and CPR policy. The dissertation can be downloaded here: https://experts.esf.edu/esploro/outputs/99917370604826.
Twice weekly monitoring of a Microtus ochrogaster population and social behavior in alfalfa in eastern Illinois, 1982-1987.
These data were obtained as part of a field study on social behavior of the prairie vole, Microtus ochrogaster in alfalfa. The study was conducted in two adjacent 1-ha alfalfa (Medicago sativa) fields within the University of Illinois Biological Research Area (Phillips Tract). Social groups were monitored over a 63-month period, from March 1982 through July 1984 in field 1 and from October 1983 to May 1987 in field 2, by locating underground and surface nests and subsequent trapping, twice weekly. 4-5 live traps were set around the entrances to underground nests and runways leading to a surface nest of social groups. Each month the study sites were also trapped at a 10-m grid interval as a part of an ongoing 25-year trapping study (Getz, L.L. 2024. Environmental Data Initiative. https://doi.org/10.6073/pasta/2dae8f08578ce31e7817c92a0f6acc87).
Phoenix Area Social Survey (PASS): 2011
The Phoenix Area Social Survey (PASS) parallels the Ecological Survey of Central Arizona (formerly, Survey 200) as a long-term monitoring program of the CAP LTER. Every five years, the PASS research team surveys households in selected neighborhoods in the metropolitan Phoenix area to better understand perceptions, values, and behaviors on several key environmental issues, including water conservation, urban growth, air pollution, land conservation, biodiversity and urban climate change, as well as perceptions about their neighborhoods. The survey was piloted in 2001-2002 in eight neighborhoods in Phoenix with 302 respondents and grew to 40 neighborhoods and 800 households in 2005. The PASS research team added five new neighborhoods to the survey design in 2011 to incorporate areas co-located with other CAP research endeavors and to expand the sample of low-income neighborhoods and included additional questions relevant to the housing crisis and recession and access to healthy food in the city.
Point-count bird censusing: bird abundance and diversity in CAP LTER Phoenix Area Social Survey neighborhoods throughout the greater Phoenix metropolitan area, 2006-2016
The Phoenix Area Social Survey (PASS) parallels the Ecological Survey of Central Arizona (formerly, Survey 200) as a long-term monitoring program of the CAP LTER. Every five years, the PASS research team surveys households in selected neighborhoods in the metropolitan Phoenix area to better understand perceptions, values, and behaviors of several key environmental issues, including water conservation, urban growth, air pollution, land conservation, biodiversity and urban climate change, as well as perceptions about their neighborhoods. The survey was piloted in 2001-2002 in eight neighborhoods in Phoenix with 302 respondents, and grew to over 40 neighborhoods and 800 households in 2005. Bird survey locations were established in each of the PASS neighborhoods, colocated as much as possible with the corresponding ESCA survey location in the neighborhood. Bird surveys were conducted biannualy (spring, winter) approximately the year of and the year after each PASS. In a given season, each bird survey location is visited independently by three birders who count all birds seen or heard within a 15-minute window.
Social and Heat Vulnerability Indices in Phoenix, Arizona
Vulnerability indices and maps are commonly employed by researchers and practitioners to assess hazard risk by combining variables that are theoretically or empirically associated with hazard outcomes and spatially visualizing those combined variables. For this dataset, we followed established methods to produce two vulnerability indices for 358 census tracts in the City of Phoenix, Arizona for the year 2016: the all-hazards Social Vulnerability Index (SoVI) and a specific hazards Heat Vulnerability Index (HVI). For SoVI, we compiled 27 social variables from the 2012-2016 American Community Survey (ACS); for HVI, we compiled seven social variables from the 2012-2016 ACS, one variable regarding residential air conditioning prevalence from the Maricopa County Assessor’s Office, and two variables related to vegetation density from Landsat 8 remote sensing imagery. Lastly, we conducted principal components analysis on each of the indices respective variables and then summed the resulting component scores for each census tract to produce the index values which we then spatially joined to the Phoenix census tracts.
Institutional Dimensions of Restoring Everglades Water Quality - Social Capital Analysis (FCE), Florida Everglades Agricultural Area from September 2014 to July 2015
These data were compiled through the Institutional Dimensions of Restoring Everglades Water Quality research project. One of the manuscripts generated by this project focused on the social capital dynamics in the Everglades Agricultural Area. These data represent different social capital aspects reflected by the responses of interview subjects. The purpose of analyzing social capital was to explore why and how farmers cooperated given that the state law, the Everglades Forever Act, which required the adoption of best management practices, relied on shared compliance for farmers to improve water quality. The study sought to undrestand how different aspects of social capital (broadly pro-social norms of reciprocity and trust) either encouraged or discouraged farmers to adopt BMPs effectively.
Coastal SEES Collaborative Research: Coastal Sustainability: A cross-site comparison of salt marsh persistence in response to sea-level rise and feedbacks from social adaptations
Coastal ecosystems are often valued for decision-making purposes based on monetized market and non-market values of goods and services, and associated economic impacts. Examples include values of fishery landings, price changes for waterfront homes, and tourism revenues. Monetized quantities such as these do not provide a comprehensive characterization of the values provided by these ecosystems. Human reliance on the goods and services provided by ecosystems and the global decline in the health of many of these ecosystems suggests the need for ecosystem valuation to help inform decision-making and conservation policy. However, traditionally employed economic valuation methods are rarely able to capture the full scope of the benefits ecosystems provide, including benefits provided by "cultural" ecosystem services. Qualitative methods such as focus groups can provide insight on these values not available through quantitative methods alone. This research explores public perceptions of salt marsh value through the use of semi-structured focus groups in marsh-adjacent communities in Massachusetts, Virginia, and Georgia. The data include de-identified focus group transcripts from three 90-minute focus groups held in each state. Initial questions were drawn from the same semi-structured question list in each focus group, with exploratory follow-up questions based on participant responses. Results of text analysis suggest that in case study communities, outdoor experiences in salt marshes inspire serenity in Massachusetts, influence shore identities in Virginia, and promote stewardship cultivation in Georgia. Perceived threats to these benefits, such as the threat of residential development, industrial pollution, and increasing flood risk, together constitute the context for various community responses related to marsh protection. Results supplement information from extant economic valuations and show the importance of utilizing diverse methods to elicit information on soci
Brain activity during reciprocal social interaction investigated using conversational robots as control condition
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Agreeableness personality trait and social information encoding
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Figure 8. E in Phylogenetic analysis of species of the neotropical social wasp Epipona Latreille, 1802 (Hymenoptera, Vespidae, Polistinae, Epiponini)
Figure 8. E. niger, propodeum, dorsal view. Scale bar = 1.0 mm. Figure 9. E. guerini, propodeum, dorsal view. Scale bar = 1.0 mm. Figure 10. E. niger, head, dorsal view. Scale bar = 1.0 mm. Figure 11. E. guerini, head, dorsal view. Scale bar = 1.0 mm. Figure 12. E. tatua, Tergum II, dorsal view. Scale bar = 1.0 mm. Figure 13. E. media, Tergum II, dorsal view. Scale bar = 1.0 mm.
ScienceDex guides
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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.