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.
6,410
datasets available to search
ShareScore release 0.9.0
Dataset results
6,410 results for “results”
Result data related to "Bersalli et al. (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany"
<p>Result data related to "Bersalli et al (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany". The following files are included:</p> <ul> <li>"Energy policy 2020-21 Germany-Spain.xlsx": Policy measures supporting clean energy during the Covid-19 pandemic in Germany and Spain. Data from <a href="http://energypolicytracker.org/">EnergyPolicyTracker.org</a>, amended by the authors.</li> <li> "factors.csv": Time series of emissions, population, GDP, energy intensity, and carbon intensity. Data derived from BP and Eurostat.</li> <li>"multiplicative-contribution-factors.csv": Time series of relative growth in the factors.</li> <li>"relative-cumulative-contribution-factors.csv": Time series of cumulative relative growth in the factors.</li> <li>"periods.csv": Relative growth in the factors during the global financial and COVID19 crises and before (pre) and after (post) the global financial crisis.</li> </ul>
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>
THz TDS results of PPFe and PPFu samples
<p>Transmission spectra of the wafer covered with pre-exposed and post exposed PPF. The results are almost identical but of attenuated magnitude in comparison to transmission values obtained for a bare Si substrate.</p>
Supplementary Data for "Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results from a Community-Partnered Low-cost Sensor Deployment"
<p>These are the underlying data sets needed to build the kriging maps and calculate dissemination block cumulative hazard indices described in the paper. There are three data sets:</p> <ol> <li><strong>"Sampling location names and coordinates.csv"</strong>: locations and IDs of the low-cost sensors and the regulatory monitoring stations used in this work.<strong> [NOTE: </strong>latitudes and longitudes for the sensor deployments have been intentionally rounded to protect the location of volunteer sensor hosts.]</li> <li><strong>"Dissemination Block Populations.csv"</strong>: These are the relevant dissemination blocks in the study domain and their associated populations. This information was originally extracted from: https://censusmapper.ca/#13/49.2430/-123.1252</li> <li><strong>"Daily average concentrations by site and pollutant.csv"</strong>: This contains the PM2.5, NO2 and O3 daily averages for the entire study period across all low-cost sensor sites and regulatory monitoring stations. Refer to "Sampling location names and coordinates.csv" to parse the labels in this data set.</li> </ol> <p>There is also a sample code in Python to construct the kriging maps provided in 2 formats. <strong>[NOTE: </strong>we have intentionally excluded uploading the exact data sets imported by this code; our original data contains exact locations of sensor host volunteers and thus cannot be shared.]</p> <ol> <li><strong>"Jain et al - GeoHealth - Kriging Script.ipynb"</strong>: A Jupyter notebook script to import the data, build kriging maps, calculate CHIs, and export the data.</li> <li><strong>" Jain et al - GeoHealth - Kriging Script.pdf"</strong>: A PDF export of the Jupyter notebook so that you can read the Python scripts even if you are not a Jupyter notebooks user.</li> </ol>
Study of pig manure digestate pretreatment - Results and Figures
<p>This work evaluates the release of phosphorus contained in the digestate from the anaerobic digestion of pig manure, through an acidification process. The objective of this acidification is to increase the amount of phosphorus available in the digestate liquid fraction and, subsequently, recover this element by chemical precipitation in the form of struvite or calcium phosphate. Two digestate samples (one fresh and one old) were studied and treated by adding various amounts of sulphuric acid to the different digestate fractions (raw digestate, solid fraction and liquid fraction). For the raw digestate, phosphorus releases higher than 95% were obtained for pH 4.0. In the last part of the experiment, the influence of acid pre-treatment on the reaction yield of phosphorus precipitation, in the form of struvite or calcium phosphate, was determined. Improvements in reaction yield were obtained up to 15% for struvite and 80% for calcium phosphate, increasing also in 7.5 times the amount of phosphorus available in the digestate liquid fraction, for both cases.</p>
Study of the Crystallisation Reaction Behaviour to Obtain Struvite - Agronomic Potential of Struvite and Crystallisation results
<p>The potential of N and P recovering from digestate by means of its precipitation in the form of struvite is evident. However, it is necessary to optimise the process at a larger scale, to achieve results that can be extrapolated to evaluate the technical and economic feasibility of the process at an industrial scale. In this work, batch and pilot plant tests were carried out in order to consolidate, at a sufficiently relevant scale, the results obtained at lab scale. For this purpose, the parameters that have the greatest effect on the reaction yield in a fludised bed reactor were selected (Mg and P concentration, flow rate of the fluidising agent (air) and reaction time). Digestate produced in anaerobic digestion plant from pig manure was used as raw material. According to the results obtained, for the struvite crystallisation reaction, the great operational levels for the Mg/P, N/P, air flow rate and reaction time are 1.5, 4.0, 6.0 NL·min<sup>−1</sup> and 0.5 h, respectively. Finally, a study was carried out to establish the agronomic potential of the salt (struvite) as a biofertiliser in the turf crop, obtaining a similar behaviour of the struvite used in this work to that of commercial struvite.</p>
Dataset - Survey results - Applying Model-based Requirements Engineering in AIDOaRt Collaborative Project
<p>This dataset and its associated report contain the results of an online survey on using a model-based requirements engineering approach in AIDOaRT project in 2022.</p>
Ice Throw from Wind Turbines: Experimental Data, 6DOF Model, CFD results, 3D Scans
<p>Compiled data and code from the Eisball Project (funded by the Austrian Research Promotion Agency FFG, project number 865060)</p> <p> </p> <p> </p> <p>6DOF_model_octave.zip - reference implementation of the six-degree-of-freedom model in MathML (Octave or MATLAB)</p> <p>experimental_data.csv - Experimental Data from dropping artificial ice fragments from wind turbines, recording drop distance and direction, details in experimental_data_column_description.txt</p> <p>???_forces_and_moments.csv - forces and moments tables for the use in the 6DOF model, specific per specimen type</p> <p> </p> <p>Data was first published in Nov 2021 at https://boku.ac.at/wau/risk/abgeschlossene-projekte/eisball-1 (may not persist)</p>
Quantitative results of the analysis of relevant components of the human scapholunate interosseous ligament (SLIL)
<p>This dataset corresponds to the quantification results carried out for the human scapholunate interosseous ligament (SLIL) and several control tissues analyzed in the manuscript entitled "Histological characterization of the human scapholunate ligament". The SLIL plays a fundamental role in stabilizing the wrist bones, and its disruption is a frequent cause of wrist arthrosis and disfunction. Traditionally, this structure is considered to be a variety of fibrocartilaginous tissue and consists of three regions: dorsal, membranous and palmar. Despite its functional relevance, the exact composition of the human SLIL is not well understood. In the present work, we have analyzed the human SLIL and control tissues from the human hand using an array of histological, histochemical and immunohistochemical methods to characterize each region of this structure. Results reveal that the SLIL is heterogeneous, and each region can be subdivided in two zones that are histologically different to the other zones. Analysis of collagen and elastic fibers, and several proteoglycans, glycoproteins and glycosaminoglycans confirmed that the different regions can be subdivided in two zones that have their own structure and composition. In general, all parts of the SLIL resemble the histological structure of the control articular cartilage, especially the first part of the membranous region (zone M1). Cells showing a chondrocyte-like phenotype as determined by S100 were more abundant in M1, whereas the zone containing more CD73-positive stem cells was D2. These results confirm the heterogeneity of the human SLIL and could contribute to explain why certain zones of this structure are more prone to structural damage and why other zones have specific regeneration potential. The original data obtained for the quantitative analyses of each component are shown in this dataset.</p>
Results of the expert opinion survey on environmental modeling with InVEST, Mapbiomas, and Open Street Maps
<p>This is the repository for the results of the 'expert opinion survey on environmental modeling with InVEST, Mapbiomas, and Open Street Maps'.</p> <p>Note: check the most recent version in the sidebar</p> <table> <tbody> <tr> <td>Current version</td> <td>v.0.2</td> </tr> <tr> <td>Date</td> <td>2024/01/10</td> </tr> <tr> <td>Respondants</td> <td>30</td> </tr> </tbody> </table> <p><strong>Available files:</strong></p> <table> <tbody> <tr> <td>File</td> <td>Type</td> <td>Description</td> </tr> <tr> <td><a href="../api/files/a241155a-1fb9-4b1d-b2b4-3e5cca19ff4a/responses_v01_public.csv">responses_v01_public.csv</a></td> <td>CSV table</td> <td>Survey raw results (anonymous)</td> </tr> <tr> <td><a href="../api/files/a241155a-1fb9-4b1d-b2b4-3e5cca19ff4a/responses_v01_stats.csv">responses_v01_stats.csv</a></td> <td>CSV table</td> <td>Questions statistics</td> </tr> <tr> <td><a href="../api/files/a241155a-1fb9-4b1d-b2b4-3e5cca19ff4a/responses_v01_mean_sd.jpg">responses_v01_mean_sd.jpg</a></td> <td>JPEG Image</td> <td>Illustration of Stats (mean and standard deviation)</td> </tr> <tr> <td><a href="../api/files/a241155a-1fb9-4b1d-b2b4-3e5cca19ff4a/responses_v01_bands.jpg">responses_v01_bands.jpg</a></td> <td>JPEG Image</td> <td>Illustration of Stats (uncertainty bands)</td> </tr> </tbody> </table> <p>The column descriptions in the statistical table are as follows:</p> <p>Prefixes:</p> <ul> <li>HABITAT: habitat suitability score</li> <li>WEIGHT: Threat weight</li> <li>MAX_DIST: Maximum distance of negative influence (impact)</li> </ul> <p>Suffixes:</p> <ul> <li>mean: Average</li> <li>std: Standard deviation</li> <li>min: Minimum value</li> <li>p05: 5th percentile</li> <li>p25: 25th percentile</li> <li>p50: 50th percentile (median)</li> <li>p75: 75th percentile</li> <li>p95: 95th percentile</li> <li>max: Maximum value</li> </ul> <p>These prefixes and suffixes describe various statistical measures used to analyze the environmental modeling data.</p>
Simulation results for study on pulsed electron lenses for space charge mitigation
<p>Simulation results for beam loss in the FAIR SIS100 synchrotron for a comprehensive study on pulsed electron lenses for space charge mitigation. The affiliated manuscript "Pulsed electron lenses for space charge mitigation" describing the study parameters is published on arxiv.org (https://arxiv.org/abs/2310.02365) and submitted for journal publication.</p> <p>For the "ffsc" files, each file contains the tabulated beam survival rate of 1000 simulated particles for a given bare tune. A file typically gathers results from scanning the betatron tune quadrant 18.5 <= Qx,y <= 19.0 in tune steps of 0.01.</p> <p>Explanation of file names:</p> <p>- "ffsc": using the fixed frozen Gaussian field map model for space charge (as established in https://doi.org/10.1103/PhysRevAccelBeams.25.054402 );</p> <p>- "nel": number of pulsed electron lenses placed symmetrically in the straight sections of the SIS100 ring;</p> <p>- "alpha": linear compensation degree, alpha=1.0 corresponds to a total electron lens tune implied tune shift equal to the linear rms-equivalent KV space charge tune shift;</p> <p>- "N": intensity in percent units of the FAIR design intensity for Uranium-28+ beams, i.e. N=100 corresponds to the FAIR design intensity;</p> <p>- "2D" or "3D": the 3D results correspond to the full simulation model with (nonlinear) synchrotron motion, the 2D results assume a fixed longitudinal phase-space distribution and only simulate the transverse dynamics (thus, periodic resonance crossing is suppressed by construction).</p>
Results of the test for the sampling period described in D7.3: Madrid pilot report
<p>This datasets provides further information about section 9.4 Monitorisation and results of D7.3. This public deliverable describes Madrid pilot project report. CARTIF share this dataset with the results of the test carried out during the sampling period regarding particulate matter and nitrogen oxides.</p>
HeatResilientCity II - work package 2.2: Influence of regional and urban climate on indoor overheating - Results of building performance simulation
<p>This repository contains the <strong>results of the building performance simulations</strong> carried out in the working package 2.2 Influence of regional and urban climate on indoor overheating of the project <a href="http://heatresilientcity.de/">HeatResilientCity II</a>. The buildings under consideration are a multi-residential so-called ‘Gründerzeithaus’ (GZH) and a large-panel construction (LPC) building. The results were extracted for two rooms on the top floor/attic of each building and follow a consistent name convention. Each file contains hourly resolved values for the outdoor air temperature, the indoor air temperature, the indoor operative temperature and the relative humidity indoors and outdoors. Further information can be found in the README of this repository. The simulations were performed for five <strong>different</strong> <strong>regions</strong> in Germany (Dresden, Hamburg, Köln, Stuttgart and Potsdam) for <strong>average present</strong> and <strong>future</strong> <strong>summers</strong> based on meteorological measurement data and under consideration of <strong>urban</strong> <strong>climate</strong>.</p> <p>In addition to the ‘plain’ simulation results, some <strong>heat-indicator variables</strong> were calculated and listed in the files <em>Calculated_Variables.txt</em>. The calculated quantities include temperature-weighted exceedance hours (TWEH) for the limits of 25, 26 and 27 °C (defined in DIN 4108-2:2013 as ‘Übertemperaturgradstunden’) and the maximum operative temperature calculated for the period from April to September.</p> <p>The used <strong>input data</strong> and <strong>building models</strong> can be found in the related repository.</p>
Results of semantic queries for "carbon cycling" for datasets in the DataONE catalog
DataONE (https://www.dataone.org) is a federation of institutions involved with the earth and environmental sciences that share data through common cyberinfrastructure. In 2016, the DataONE project carried out a quantification of the utility of semantic query, by measuring the precision and recall of relevant datasets available through that catalog. Precision is defined as the proportion of relevant data in the retrieved results, and recall is the proportion of relevant data retrieved, compared to all relevant data present in the repository (see Methods). This dataset contains the queries and results of that study. Four data tables are included. First, a table of the 10 queries, which were formatted in several ways, including natural language and text strings (for plain text searches of various parts of metadata), and URIs for measurements in the EcoSystem Ontology (ECSO). A second table contains 994 relevant datasets in the DataONE catalog, with a column for each of the ten queries and boolean value indicating whether the dataset is a match for that query. Two query results tables are included, for the raw and summarized results of the query tests. A fifth entity contains the zipped code (R language) used to perform the queries in the DataONE system. When run against approximately 1000 datasets (in October, 2016), results for the ten queries ranged from 0-50% (precision) and 0-100% (recall), indicating that traditional searches may sometimes be adequate to return all relevant data in a corpus, but results can be erratic and inconsistent, with potentially large returns of irrelevant data in the result set. When querying through semantic classes, precision and recall were much higher and more consistent (90-100% and 75-100%, respectively).
Baltimore Ecosystem Study: Stewardship Mapping And Assessment Project (STEW-MAP) survey results 2011 and 2019
Addressing the challenges of sustainable and equitable city management in the 21st century requires innovative solutions and integration from a range of dedicated actors. In order to form and fortify partnerships of multi-sectoral collaboration, expand effective governance, and build collective resiliency it is important to understand the network of existing stewardship organizations. The term ‘stewardship’ encompasses a spectrum of local agents dedicated to the evolving process of community care and restoration. Groups involved in stewardship across Baltimore are catalysts of change through a variety of conservation, management, monitoring, transformation, education, and advocacy activities for the local environment – many with common goals of joint resource management, distributive justice, and community power sharing. The “environment” here is intentionally broadly defined as land, air, water, energy and more. The Stewardship Mapping and Assessment Project (STEW-MAP) is a method of data collection and visualization that tracks the characteristics of organizations and their financial and informational flows across sectors and geographic boundaries. The survey includes questions about three facets of environmental stewardship groups: 1) organizational characteristics, 2) collaboration networks, and 3) stewardship “turfs” where each organization works. The data have been analyzed alongside landcover and demographic data and used in multi-city studies incorporating similar datasets across major urban areas of the U.S. Additional information about the growing network of cities conducting stewmap can be found here: https://www.nrs.fs.usda.gov/STEW-MAP/ Romolini, Michele; Grove, J. Morgan; Locke, Dexter H. 2013. Assessing and comparing relationships between urban environmental stewardship networks and land cover in Baltimore and Seattle. Landscape and Urban Planning. 120: 190-207. https://www.fs.usda.gov/research/treesearch/44985 Johnson, M., D. H. Locke, E. Svendsen, L
Log Decomposition Dynamics in Interior Alaska 5a - Preliminary Results (treatment down) - Absolute
The entire dataset (all 7 files) contains detailed information on a time series study of log decomposition in interior Alaska. The species studied include white and black spruce, aspen, birch, balsam poplar and aspen starting as green trees. In addition white and black spruce in recently burned sites are included. The study was designed to produce a time series of log decomposition measurements over the next 100 years. The information to be measured on the logs includes weight and density changes over specified time periods, changes in nutrient concentrations, and hemicellulose, cellouse, and lignin concentrations, and changes in the quantity of nutrients and hemicellulose, cellouse and lignin. (This file contains preliminary absolute results for treatment=down part of the study.)
Log Decomposition Dynamics in Interior Alaska 5b - Preliminary Results (treatment down) - Retained
The entire dataset (all 7 files) contains detailed information on a time series study of log decomposition in interior Alaska. The species studied include white and black spruce, aspen, birch, balsam poplar and aspen starting as green trees. In addition white and black spruce in recently burned sites are included. The study was designed to produce a time series of log decomposition measurements over the next 100 years. The information to be measured on the logs includes weight and density changes over specified time periods, changes in nutrient concentrations, and hemicellulose, cellouse, and lignin concentrations, and changes in the quantity of nutrients and hemicellulose, cellouse and lignin. (This file contains preliminary retention results for the treatment=down part of the study.)
Modeling CH4 and CO2 cycling using porewater stable isotopes in a thermokarst bog in Interior Alaska: Results from three conceptual reaction networks
Quantifying rates of microbial carbon transformation in peatlands is essential for gaining mechanistic understanding of the factors that influence methane emissions from these systems, and for predicting how emissions will respond to climate change and other disturbances. In this study, we used porewater stable isotopes collected from both the edge and center of a thermokarst bog in Interior Alaska to estimate in situ microbial reaction rates. We expected that near the edge of the thaw feature, actively thawing permafrost and greater abundance of sedges would increase carbon, oxygen and nutrient availability, enabling faster microbial rates relative to the center of the thaw feature. (full abstract available in supplemental file 610_NeumannPorewaterExtendedMetadataText.pdf)
Litter Trap Results at the Tanana River Exclosures: 2001 - Present
This study examines the effects browsing by mammals has on the function of the Alaskan taiga ecosystem. The primary emphasis is the effects that browsing in winter by snowshoe hares (Lepus americanus) and moose (Alces alces) have on vegetation composition, leaf litter biomass, and growth of deciduous shrubs on the floodplain of the Tannana River. Nine 50m X 20m exclosures were originally established in the willow stage and alder stage of succession in 1988 which have been used to evaluate the effect of browsing on vegetation dynamics, element cycling, soil chemistry. Additionally, the effect on vegetation type on the diversity and abundance of neotropical birds as well as ground-dwelling invertebrates populations on the the Tannana floodplain has been examined. This is an ongoing study.
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.