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GitHub Profiles (users/organisations) and Repositories (research/non-research) of Potsdam Researchers and Research Organisations: An annotated dataset of with howfairis and software quality variables.
<p>This dataset accompanies the paper <em>"Software FAIRness, Documentation and Development Practices in Potsdam Researchers' GitHub Repositories"</em> It includes 3 CSV files that contain data related to github profiles of users/organisations, their repositories annotated as research/non-research repositories and followed by FAIRness and other software qualtiy variables. The data were collected using <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP">SWORDS-template-UP</a> (v1.0.0) methods (collect_users, collect_repositories, collect_variables) which is extended version of <a href="https://github.com/UtrechtUniversity/SWORDS-template">SWORS-template</a> adopted according our needs and detailed in the paper.</p> <p><strong>GitHub (research) user/organisation profiles. ( <em>github_profiles.csv )</em></strong></p> <table> <tbody> <tr> <td><strong>Column name</strong></td> <td><strong>Description </strong></td> </tr> <tr> <td>user_id</td> <td>GitHub username </td> </tr> <tr> <td>html_url </td> <td>URL of the GitHub profile </td> </tr> <tr> <td>type </td> <td>Type of profile (user or organization)</td> </tr> <tr> <td>organisation</td> <td>Acronym or name of the organization </td> </tr> </tbody> </table> <p><strong>GitHub repositories <em>(github_repositories.csv)</em></strong></p> <p>This file contains the repositories scraped from the GitHub profiles of research users and organizations.</p> <table> <tbody> <tr> <td><strong>Column name </strong></td> <td><strong>Description </strong></td> </tr> <tr> <td>html_url </td> <td>URL link to the repository </td> </tr> <tr> <td>description</td> <td>GitHub project description </td> </tr> <tr> <td>project</td> <td>Specifies if the project is research or non-research</td> </tr> <tr> <td>language</td> <td>Programming language used in the project </td> </tr> <tr> <td>organisation</td> <td>Acronym or name of the university, institution, or research organization</td> </tr> <tr> <td>research_group</td> <td>Acronym or name of the research group the repository belongs to</td> </tr> </tbody> </table> <p><strong>Research repositories filtered and annotated <em>(github_research_repositories_filtered_annotated.csv)</em></strong></p> <p>This file contains filtered and annotated information about research repositories.</p> <table> <tbody> <tr> <td><strong>Column Name </strong></td> <td><strong>Description </strong></td> <td><strong>Collection Method </strong></td> </tr> <tr> <td>html_url </td> <td>Repository URL </td> <td> </td> </tr> <tr> <td>howfairis_repository</td> <td>Indicates if the repository is public or private (True/False) </td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/tree/main/collect_variables#usage">howfairis_variable.py</a>) is a wrapper for <a href="https://pypi.org/project/howfairis/">howfairis</a> pypi library that checks the 5 recommendations of <a href="https://fair-software.nl">FAIR</a></td> </tr> <tr> <td>howfairis_license </td> <td>Indicates if the repository has a license (True/False)</td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/tree/main/collect_variables#usage">howfairis_variable.py</a>) is a wrapper for <a href="https://pypi.org/project/howfairis/">howfairis</a> pypi library that checks the 5 recommendations of <a href="https://fair-software.nl">FAIR</a></td> </tr> <tr> <td>howfairis_registry</td> <td>Indicates if the repository has implemented community registry (True/False)</td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/tree/main/collect_variables#usage">howfairis_variable.py</a>) is a wrapper for <a href="https://pypi.org/project/howfairis/">howfairis</a> pypi library that checks the 5 recommendations of <a href="https://fair-software.nl">FAIR</a></td> </tr> <tr> <td>howfairis_citation</td> <td>Indicates if the repository has a .cff file (True/False) </td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/tree/main/collect_variables#usage">howfairis_variable.py</a>) is a wrapper for <a href="https://pypi.org/project/howfairis/">howfairis</a> pypi library that checks the 5 recommendations of <a href="https://fair-software.nl">FAIR</a></td> </tr> <tr> <td>howfairis_checklist</td> <td>Indicates if the repository has implemented OpenSSF best practices badge (True/False)</td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/tree/main/collect_variables#usage">howfairis_variable.py</a>) is a wrapper for <a href="https://pypi.org/project/howfairis/">howfairis</a> pypi library that checks the 5 recommendations of <a href="https://fair-software.nl">FAIR</a></td> </tr> <tr> <td>fair_score</td> <td>Score based on howfairis variables (0-5) </td> <td> </td> </tr> <tr> <td>dlr_soft_class</td> <td>Name of the university, company, research institute, or research organization</td> <td>(Manual) Annotated the repository based on <a href="https://core.ac.uk/reader/211557820">DLR software engineering guideline.</a> There are no specific definitions on metrics how to categorise them (github repositories) into application classes. Which were needed to do a comparitive analysis. </td> </tr> <tr> <td>installation_instruction</td> <td>Presence of installation instruction (True/False) </td> <td>(Manual) Checked the presense of Installation Instruction in the readme or in the project wiki pages. </td> </tr> <tr> <td>project_information </td> <td>Presence of basic project information in README (True/False) </td> <td>(Manual) Checked if the readme have basic information about the project. </td> </tr> <tr> <td>usage_guide</td> <td>Presence of folder named test/tests in the root directory (True/False)</td> <td>(Manual) Checked the presense of Usage Guide in the readme or in the project wiki pages. For command line tools checked if they have help command which guides how to use the tool. </td> </tr> <tr> <td>test_folder</td> <td>Presence of folder named test/tests in the root directory (True/False)</td> <td> <p>(Script - <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/docs/collect_variables/scripts/soft_dev_pract/test_folder.py">test_folder.py</a>) Checks the folder names test/tests in the root directory of the repository.</p> </td> </tr> <tr> <td>requirements_explicit </td> <td>Explicit requirements for Python, R, C++ repositories (True/False)</td> <td>(Script - <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/requirement_explicit.py">requirement_explicit.py</a>) Checks the files (requirements.txt, DESCRIPTION, CMakeLists.txt) in the root directory. </td> </tr> <tr> <td>continuous_integration</td> <td>Indicates if the repository uses continuous integration (True/False)</td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/continious_integration.py">continious_integration.py</a>) Checks the presence of folder .github (github actions) same for other continious integration (travisCI, CircleCI, Jekins, azure pipeline)</td> </tr> <tr> <td>ci_tool </td> <td>Name of the continuous integration tool used</td> <td>(Script- <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/continious_integration.py">continious_integration.py</a>) Checks the presence of folder .github (github actions) same for other continious integration (travisCI, CircleCI, Jekins, azure pipeline)</td> </tr> <tr> <td>add_lint_rule </td> <td>Indicates if additional linting rules are present (True/False)</td> <td>(Script - <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/add_ci_rules.py">add_ci_rules.py</a>) - it scans the YAML files in the <br>.github/workflows directory to detect the presence of (linters) Python, R, and C++.</td> </tr> <tr> <td>add_test_rule</td> <td>Indicates if additional testing rules are present (True/False) </td> <td>(Script - <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/add_ci_rules.py">add_ci_rules.py</a>) - it scans the YAML files in the <br>.github/workflows directory to detect the presence of (testing libraries) Python, R, and C++.</td> </tr> <tr> <td>comment_at_start</td> <td>Indicates the level of comments at the start of the program (most, more, some, less)</td> <td>(Script - <a href="https://github.com/Software-Engineering-Group-UP/SWORDS-template-UP/blob/main/collect_variables/scripts/soft_dev_pract/comment_at_start.py">comment_at_start.py</a>) Checks the presence of brief comments at the start at source code files in GitHub repositories.</td> </tr> <tr> <td>language </td> <td>Programming language used in the repository </td> <td> </td> </tr> <tr> <td>type </td> <td>Specifies if the profile is a user or organization </td> <td>Github organisation or user profiles.</td> </tr> <tr> <td>organisation </td> <td>Name of the university, company, research institute, or research organization</td> <td>Oraganisation name (from where the user was found)</td> </tr> <tr> <td>research_group</td> <td>Name or acronym of the research group </td> <td> </td> </tr> </tbody> </table> <p> </p> <p>Data for publication - https://github.com/Software-Engineering-Group-UP/potsdam-research-repos</p>
The human Voice Areas: spatial organisation and inter-individual variability in temporal and extra-temporal cortices
Open the record for dataset details and reuse information.
Datenanhang zur Umfrage zu den Angeboten für Digitale Lehre an Hochschulen im Juni 2020 durch den ZKI-Arbeitskreis Strategie & Organisation und die AMH
<p><strong>Datenanhang zur Umfrage zu den Angeboten für Digitale Lehre an Hochschulen <a href="https://doi.org/10.5281/zenodo.3911092">https://doi.org/10.5281/zenodo.3911092</a></strong></p> <p>Diese Umfrage schließt an die <a href="https://zenodo.org/deposit/3826557">Kurzumfrage aus dem April 2020</a> an, mit der die Auswirkungen der Corona-Krise auf deutsche Hochschulen und insbesondere deren IT- und Medienzentren erhoben wurden. Diese zweite Umfrage soll weitere Informationen zusammentragen, um die Mitglieder des Arbeitskreises und der AMH bei der weiteren Planung und Steuerung zu unterstützen. Die Fragengruppen haben bis zu 96 Antworten erhalten.</p> <p>Die erste Fragengruppe erfasst Angaben zur Herkunft und Rolle der Teilnehmenden. In dieser Gruppe gab es 96 Antworten. In mehreren Vorabgesprächen wurden Digitale Prüfungen als besonders klärungsbedürftiges Arbeitsfeld genannt. Deshalb fragt die zweite Fragengruppe nach den Planungen und Erfahrungen zu Digitalen Prüfungen. Hierzu gab es bis zu 50 Antworten. Die dritte Fragengruppe fragt nach den Veränderungen für die IT- und Medieneinrichtung durch die Anforderungen der Digitalen Lehre und erhielt 38 Antworten. Im vierten Teil der Umfrage wird ein Fokus auf die Top-Antworten zu den Lösungen für Digitale Lehre der Kurzumfrage aus April 2020 gelegt. Die Top-Antworten waren Zoom, BigBlueButton, Jitsi Meet und WebEx / Cisco im Bereich AV-Konferenzen, OpenCast und Panopto für Videoaufzeichnung, MS-Teams für Kollaborationsumgebungen und Rocketchat für Instant Messaging. Teilnehmende konnten Antworten für bis zu drei eingesetzten Lösungen geben. Für den Einsatz dieser Lösungen soll dabei beleuchtet werden, mit welchen Szenarien diese Lösungen eingesetzt werden, ob und wie diese Lösungen integriert wurden, ob schon jetzt Aussagen zur Nachhaltigkeit (auch personellen) getroffen werden können, wie Dienstleister eingebunden wurden, wie die technische Konfiguration aussieht und wie es um die Compliance der neuen Dienste steht. Für diese Gruppe gab es 90 Antworten. Um ein möglichstes breites und vielfältiges Spektrum an Antworten zu bekommen, waren alle Fragen optional und es war somit auch möglich, einzelne Fragengruppen leer abzusenden.Die Teilnahme an der Umfrage war vom 2.6.2020 bis zum 19.6.2020 möglich.</p>
Organisation for Economic Co-operation and Development (OECD) data for Antalya (Turkey), Antwerp (Belgium), Cork (Ireland), Thessaloniki (Greece) (source: OECD)
<p>The data have been collected via the official OECD Application Programming Interface (API)<strong> </strong>and<strong> </strong>includes the following indicators:</p> <ul> <li>EmpPlaRes - Employment at place of residence</li> <li>LfPartRa - Labour Force and Participation rate</li> <li>UnemReg - Unemployment in regions </li> <li>RegGdpTL2 - Regional Gross Domestic Product (Large regions TL2)</li> <li>GDPLT3 - Gross Domestic Product (Small regions TL3)</li> <li>RegEmIndu - Regional Employment by industry (ISIC rev 4)</li> <li>RegGVAWorker - Regional GVA per worker</li> <li>RegIncPC - Regional income per capita</li> </ul> <p>Source: https://data.oecd.org/api/</p>
National Open Access Monitor Survey: Organisational Identity: Responses Dataset
<p>This dataset contains the response data from the 'National Open Access Monitor Survey: Organisational Identity which was carried out between 9th October and 9th November 2023 under the National Open Access Monitor Project: <a href="https://zenodo.org/doi/10.5281/zenodo.8420404">https://zenodo.org/doi/10.5281/zenodo.8420404</a></p><p><strong>This survey was run to:</strong></p><ul><li>compile a complete list of Irish research performing organisations (RPO) and research funding organisations (RFO) to be represented by the National Open Access Monitor.</li><li>ensure each organisation/entity is categorised correctly as an RPO or an RFO (or both), as applicable.</li><li>identify if an organisation/entity is publicly funded.</li><li>identify formally affiliated organisations/entities where <strong>all </strong>research outputs of one organisation/entity should also be included in the research outputs of another organisation/entity.</li><li>capture the persistent identifiers for RPOs, RFOs and publishers, to enable identification of relevant research outputs for the National Open Access Monitor.</li></ul><p><strong>To note: </strong></p><ul><li>Respondents' email addresses have been redacted.</li><li>Responses have been pseudonymised to the level of stakeholder-group e.g. Contributor A, Research Funding Organisation A, where requested by the participant in the participant consent form: <a href="https://doi.org/10.5281/zenodo.7589770">https://doi.org/10.5281/zenodo.7589770</a>.</li><li>Respondents were notified of the limits of pseudonymisation for this survey. Due to the nature and purpose of this survey on Organisational Identity, the identity of the organisation/entity could not be pseudonymised. Participants were advised only to participate if they were happy to do so under these conditions.</li><li>Survey responses were deleted by request of certain respondents. These responses are not included in these files.</li><li>Survey respondents were enabled to update their submissions. These changes are captured in the <i>NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.</i></li></ul><p><strong>There are four files within in this dataset:</strong></p><p>- <i>Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.README - </i>this PDF details the changes made to the raw data, as specified in the bullet points above and a description of the files within the dataset.</p><p>- <i>Results.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.101123</i> - this is the original raw data, in csv format, as downloaded from the Online Surveys platform and subsequently pseudonymised and redacted.</p><p>- <i>NationalOpenAccessMonitorSurvey.OrganisationalIdentity.MasterChangeFile.101123 </i>- this is a change file, in csv format, which documents the changes which participants requested to be made to their submissions after they were received.</p><p>- R<i>esults.NationalOpenAccessMonitorSurvey.OrganisationalIdentity.Pseudonymised.Updated.101123 - </i>this is the original raw data, pseudonymised and redacted, with the requested changes implemented.</p><p><strong>Notes for data use:</strong></p><ul><li>The "affiliated organisations/entities" section of the survey was insufficiently described in the survey text. One-to-one follow-up and support was provided to clarify to respondents that questions 12 and 13 of the survey intended to identify where <strong>all </strong>research outputs of one organisation/entity should appear on that organisation's/entities' own RPO or RFO dashboard within the National Open Access Monitor, and <strong>also </strong>on the dashboard of another organisation/entity. </li><li>Survey respondents were notified in the introduction section to the "affiliated organisations/entities" section that "<strong>only where all entities agree there is a formal relationship in place</strong> that should be reflected in the Monitor will the link be implemented". Therefore, for the National Open Access Monitor project, only where both parties have asserted that <strong>all </strong>research outputs of one organisation/entity should also appear on the dashboard of another organisation/entity, will it be considered validated and implemented. </li><li>The geographic scope of the National Open Access Monitor Project is the Republic of Ireland. Where respondent's RPO or RFO organisations/entities are based outside the Republic of Ireland, or where respondents stated affiliations with overseas organisations/entities, they will not be actioned or implemented. To note: the survey invited responses from international <i>publishers</i> to enable filtering functionality by publisher within the National Open Access Monitor, these responses are <i>not </i>out of scope. </li></ul><p>-----------------------</p><p>The context for the survey is detailed in the National Open Access Monitor Project Plan: <a href="https://doi.org/10.5281/zenodo.7331431">https://doi.org/10.5281/zenodo.7331431</a>, the National Open Access Monitor Advisory Group Meeting Minutes, 18th September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8405472">https://zenodo.org/doi/10.5281/zenodo.8405472</a> and the Developing the National Open Access Monitor, Ireland: Stakeholder Webinar, 22nd September 2023: <a href="https://zenodo.org/doi/10.5281/zenodo.8370578">https://zenodo.org/doi/10.5281/zenodo.8370578.</a></p><p>This project is managed by <a href="http://www.irel.ie/">IReL </a>and has received funding from Ireland's National Open Research Forum under the NORF Open Research Fund. <a href="https://norf.ie/funding/">https://norf.ie/funding/ </a><a href="https://norf.ie/orf-projects-announcement/">https://norf.ie/orf-projects-announcement/</a></p>
Figure - Network Organisation
<p>Figure "Network Organisation" created for the MIDA Project application document in 2018. </p>
Rohdaten zu den Ergebnissen der ZKI Top Trends-Umfrage des ZKI-Arbeitskreises Strategie und Organisation für das Jahr 2022
<p>Der Arbeitskreis Strategie und Organisation des ZKI-Vereins führt eine jährliche Umfrage zu den wichtigsten Themen und Trends von IT-Einrichtungen aus Hochschulen und Forschungseinrichtungen durch. Die Umfrageergebnisse sollen dabei helfen, wichtige Entwicklungen, Themen und Best Practices im Blick zu behalten und bei den umfangreichen Themenfeldern der Digitalisierung und der rasanten Erneuerung von Technologien Schritt zu halten bzw. auch Inspiration für die weitere Ausgestaltung an der eigenen Einrichtung zu gewinnen.</p> <p>Die Kernumfrage adressiert die wichtigsten Themen und Veränderungen im Umfragejahr in standardisierter Form. Darüber hinaus werden in jedem Jahr individuelle Schwerpunkte abgefragt, die viele Einrichtungen beschäftigen. Im Jahr 2022 waren die Schwerpunktfragen über die Kernumfrage hinaus:</p> <ul> <li>Hat die <strong>Nutzung von externen Cloud-Angeboten</strong> während der Pandemie eher zugenommen oder eher abgenommen?</li> <li>In welchem <strong>Umfang</strong> setzen Sie <strong>Cloud-Technologien</strong> ein?</li> <li>Welche <strong>Maßnahmen</strong> haben Sie im Bereich <strong>"Digitale Souveränität"</strong> getroffen?</li> <li>Welche <strong>spezifischen Aspekte</strong> sehen Sie für Hochschulen und Forschungseinrichtungen im Bereich <strong>Digitaler Souveränität</strong>?</li> <li>Welche <strong>Auswirkungen</strong> sehen Sie durch Corona für die <strong>Arbeitsplatzgestaltung</strong>?</li> <li>Welche <strong>Tools und Mechanismen</strong> haben Ihnen dabei geholfen, <strong>Zusammenarbeit</strong> und Team-Geist <strong>trotz weniger Präsenz</strong> zu erhalten?</li> <li>Welchen <strong>Prozentsatz</strong> an <strong>Home-Office</strong> sehen Sie zukünftig <strong>für die IT-Einrichtung</strong> Ihrer Hochschule?</li> <li>Wie sehen Sie die <strong>Rolle der IT</strong> an Ihrer Hochschule <strong>nach Corona</strong>?</li> </ul> <p>Weiterhin wird nach den Modellen zur IT-Governance gefragt.</p>
Forschungsdaten und Fragebogen zur "Umfrage zum Bedarf und Nutzung von Organisations-IDs an Hochschulen und außeruniversitären Forschungseinrichtungen in Deutschland"
<p>*English description below*</p> <p>Um mehr über den Status quo der Nutzung und Verbreitung von Organisations-IDs in Deutschland zu erfahren, wurde im Rahmen des DFG-geförderten Projekts ORCID DE im Zeitraum vom 13.07.2020 bis zum 04.12.2020 eine „Umfrage zum Bedarf und Nutzung von Organisations-IDs an Hochschulen und außeruniversitären Forschungseinrichtungen in Deutschland“ unter 548 wissenschaftlichen Einrichtungen in Deutschland durchgeführt. An der bislang größten Befragung zu Organisations-IDs in Deutschland beteiligten sich 183 Einrichtungen. Bestandteil der Studie waren unter anderem Fragen zur Kenntnis, Verbreitung und Nutzung von Organisations-IDs an wissenschaftlichen Einrichtungen. Darüber hinaus wurden Anforderungen an Organisations-IDs bzw. ihre Metadaten (z. B. Relationen und Granularität) erfragt. Die vorliegende quantitative Befragung wurde als Online-Umfrage durchgeführt. Technisch wurde die Befragung mit der Software LimeSurvey auf einem Server der Universität Bielefeld umgesetzt. </p> <p>Die vorliegende CSV-Datei enthält die aus Lime-Survey exportierten, prozessierten und anonymisierten Antworten der 183 teilnehmenden Einrichtungen auf die 22 gestellten Fragen. Der Fragebogen wurde besseren Nachvollziehbarkeit der Dokumentation sowie zur Reproduzierbarkeit ebenfalls als PDF-Datei bereitgestellt. Sowohl die Forschungsdaten als auch der Fragebogen sind auf Deutsch.</p> <p>In order to learn more about the status quo of the use and dissemination of organizational identifiers in Germany, a "Survey on the Need for and Use of Organizational Identifiers at Universities and Non-University Research Institutions in Germany" was conducted among 548 research institutions in Germany in the period from July 13, 2020 to December 4, 2020 as part of the DFG-funded ORCID DE project. This survey constitutes the largest survey on organizational identifiers in Germany to date; it counts 183 participating institutions. Among other things, the survey included questions on the knowledge, distribution, and use of organizational identifiers at research institutions.</p> <p>Technically, the survey was implemented with the software LimeSurvey on a server at Bielefeld University. </p> <p>This CSV file contains the processed and anonymised answers of the 183 participating institutions to the 22 questions exported from LimeSurvey. The questionnaire was also made available as a PDF file for better traceability of the documentation and for reproducibility. Both the research data and the questionnaire are in German.</p>
Data for: From pattern to process? Dual travelling waves, with contrasting propagation speeds, best describe a self-organised spatio-temporal pattern in population growth of a cyclic rodent
<p>Centroid data used for the analysis in Roos et al. Eco Lett.</p> <p>Transects, up to 99 m in length (dependent on the field's length), were surveyed in linear stable landscape features (field, track or ditch margins) to estimate vole abundance from November 2011 until September 2017. Each transect was divided into 3 m sections (33 in total) and the presence or absence of one or more signs of vole activity (i.e., latrines by burrows, fresh vegetation clippings, and recent burrow excavations) in each section was noted. The proportion of sections with signs of vole presence per transect was then used as the abundance index. The number of surveys carried out at any time varied adaptively with the perceived risk of an outbreak (according to changes in estimated abundance in previous monitoring surveys).</p> <p>The response variable typically used in all models is proportional growth rate (r_{t,i}, where is the abundance index for site at time (Royama 1992; Berryman 2002). A benefit of using r_{t,i}, rather than ln(N_{t,i}), is that any multiplicative effects of site quality are cancelled out, provided they are constant over time. To calculate r_{t,i}, vole abundance indices are required at the same location in successive time periods (i.e., N_{t,i} and N_{t+1,i}). Given that exact transect locations were rarely reused in successive months, and all transect measurements took place throughout the year rather than discrete seasons, the data had to be aggregated to consistent locations and times to allow growth rate to be calculated. As such, transects were temporally aggregated into a respective yearly quarter (e.g., January to March 2014). Transects were spatially aggregated by sequentially selecting an unassigned transect as a reference point for the ith centroid and assigning all unassigned transects within a 5 km radius to the ith centroid, and repeating until all transects had been allocated (see Figure 2 for a summary of the number of transects assigned to each centroid, centroid locations, and time series of growth rate of each centroid). Once complete, the mean Julian day, X and Y UTM (Universal Transverse Mercator) and the mean index was calculated for all transects assigned to each centroid for each time period. Where a centroid had successive values of N_{t,i} and N_{t+1,i} available, the corresponding proportional growth rate was calculated.</p> <p>A constant of 3.03 was added to N_{t,i} to avoid zero entries (3.03 was the lowest non-zero value of <em>N</em> observed). The final dataset consisted of 3,751 observations.</p>
CSI-COP Dataset of Organisations to Approach in Citizen Science Projects
<p>This dataset complements CSI-COP project deliverable D2.3 report: '<strong>Framework for Engaging Citizen Scientists</strong>'.</p> <p>The D2.3 deliverable was produced in 2020 by partners in CSI-COP work package 2 led by <strong>Professor Olga Stepankova </strong>of Czech Technical University, Prague (<strong>CTU</strong>).</p> <p>The Stepankova et al. (2020) report is available on this Zenodo platform here:</p> <p><a href="https://zenodo.org/record/4066515#.Yrx9DezMLb0">https://zenodo.org/record/4066515#.Yrx9DezMLb0</a></p>
Insights into the Cyst Organisation and Selected Morpho-Physiological Aspects of Encystment in Thulinius ruffoi
<p>This dataset is related with studies on morpho-physiological aspects of encystment in Thulinius ruffoi (Parachela, Isohypsibioidea: Doryphoribiidae). Data gathered to elucidate the adaptations of these microinvertebrates to environmental changes. Encystment is an adaptive response in tardigrades triggered by environmental cues and potentially by internal factors. The dataset provides insights into cellular organization, morphology, and anatomy during cyst formation in selected tardigrade species. This dataset is supplemented by two others available at <a target="_new" rel="noopener">10.5281/zenodo.10008352</a> and <a target="_new" rel="noopener">10.5281/zenodo.11213808</a>.</p>
Report on a Survey among Organisers of Citizen Science Projects - Dataset and Report
<p>In this publication you will find the report on a survey among organisers of citizen science projects developed by Michael Strähle & Christine Urban (alphabetical order), Wissenschaftsladen Wien - Science Shop Vienna. You will also find, the datasets which contain the responses obtained from the very short questionnaire "VSQ" and the responses used for the report.</p>
Les Data Lakes comme Approche d'Organisation de l'Information
<p>Dans cette présentation, nous faisons le tour des méthodes d'organisation et de stockage de l'information depuis la bibliothèque (antiquité) au tout récent <em>Data Lake</em>. </p>
D2.1: Artefact, Contributor, and Organisation Relationship Data Schema - Appendix A
<p>Comparison of metadata schema for ORCID, DataCite, Dublin Core, CASRAI, MODS and DDI regarding contributors, organizations and artefacts.</p>
Dataset and figures: Antibiotic underdosing and disposal in NHS organisations across Great Britain
<p>This record contains the data collated and figures generated as part of the production of the "Antibiotic underdosing and disposal in NHS organisations across Great Britain: Research Report and Policy Brief" published by the Office of Baroness Bennett of Manor Castle.</p>
Temporal cluster-based organisation of sleep spindles underlies motor memory consolidation
<p><span>Sleep benefits motor memory consolidation, which is mediated by sleep spindle activity and associated memory reactivations during non-rapid eye movement (NREM) sleep. However, the particular role of NREM2 and NREM3 sleep spindles and the mechanisms triggering this memory consolidation process remai<span>n unclear. Here, sim</span>ultaneous electroencephalographic and functional magnetic resonance imaging (EEG-fMRI) recordings were collected during night-time sleep following the learning of a motor sequence task. Adopting a time-based clustering approach, we provide evidence that spindles iteratively occur within clustered and temporally organised patterns during both NREM2 and NREM3 sleep. However, the clustering of spindles in trains is related to motor memory consolidation during NREM2 sleep only</span><span>. Altogether</span><span>,</span><span> our findings suggest t</span><span>hat</span><span> spindles' clustering and </span><span>rhythmic occurrence </span><span>during NREM2 sleep may serve as an intrinsic rhythmic sleep mechanism for the timed reactivation and subsequent consolidation of motor memories, through synchronised oscillatory activity within a subcortical-cortical network involved during learning</span>.</p>
Image repository for "Towards advancing Translators' Guidance for Organisations Tackling Innovation Challenges in Manufacturing within an Industry 5.0 context"
<p>The files on this trusted repository are provided by the authors of the manuscript with the title “Towards advancing Translators’ Guidance for Organisations Tackling Innovation Challenges in Manufacturing within an Industry 5.0 context” that was received by the MDPI journal Sustainability (ISSN 2071-1050) on 29 January 2024, got the manuscript ID sustainability-2872279, and is intended to become part of the special issue “Sustainable Materials, Manufacturing and Design” accessible under the link <a href="https://www.mdpi.com/journal/sustainability/special_issues/Sus_materials_manufacturing_design">https://www.mdpi.com/journal/sustainability/special_issues/Sus_materials_manufacturing_design</a>.</p> <p>The authors Paul-Ludwig Michael Noeske, Alexandra Simperler, Welchy Leite Cavalcanti, Vinicius Carrillo Beber, Brendon Weager, Tasmin Alliott, Peter Schiffels, and Gerhard Goldbeck aim at facilitating common access to the files representing high-resolution microscopy images (corresponding to the light microscopy (LM) and scanning electron microscopy (SEM) images shown in Figure 9 and Figure 12 in the manuscript or complementing them) given in .jpg and .tif format, respectively. Moreover, this repository comprises a .csv file containing the data points underlying the values presented in Table A1 of this manuscript and their description. The authors indicate here that following the sixth step of the translation process in materials modelling the translator may provide these data in this presentation that is adapted to the process-centric perspective required by representatives of an enterprise manufacturing prepregs and to their background knowledge disclosed to the translator beforehand.“</p>
Data supporting the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" by Milsom et al.
<p>Model and experimental data from the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" to be published in Atmospheric Chemistry and Physics. </p>
A comparison of the World Health Organisation's HEAT model results using a non-linear physical activity dose response function with results from the existing tool
<p>Datasets relating to the Wellcome Open Research publication of the same name.</p>
RDA Data Stewardship Organisational Models Survey 2021 Output Dataset
<p>Data Stewardship comes in many forms and contexts, with the common goal of supporting data management. Yet that diversity can make it hard for the RDM community to further professionalise our work and services.</p> <p><br> The RDA Professionalising Data Stewardship Interest Group (PDS-IG) Models Task Group sought input from the research data community to help model different approaches to research data stewardship through an online survey in October to November 2021. An offline copy of the survey is available as a linked resource from this record.<br> <br> This dataset consists of a cleaned, anonymised responses from 136 respondents, though not all questions were answered by all respondents. The output are available in a CSV formatted file containing the full response set along with output from a thematic textual analysis undertaken on responses to a number of open-text questions in the survey.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.