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.
6,025
datasets available to search
ShareScore release 0.9.0
Dataset results
6,025 results for “Science of science”
Fig. 4 in Use of stereophotography in insect science - methods and applications
Fig. 4: Light-microscopic 3D images of the terminal sections of the female accessory glands in the Mediterranean field cricket (a) and Australian field cricket (b) (image widths: 2 mm).
Fig. 2 in Use of stereophotography in insect science - methods and applications
Fig. 2: Stereoscopic macro-photographs (red-green anaglyphs) of different insects: (a) Australian field cricket; (b) hoverfly. All images have to be watched by using red-green glasses.
Fig. 1 in Use of stereophotography in insect science - methods and applications
Fig. 1: Methodds for the generation of stereo-ppairs in microsccopy (STURM 20016a, STURM 20016b): (a) procedure wwith slight rotatioon of the object by an angle α; ((b) displacementt of the focus plaane by the value d andd resulting produuction of an imagge stack.
The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document v1 Released Data Products
<p>This tarball includes software and data products associated with the DESC Science Requirements Document (SRD) v1. See the "Executive Summary and User Guide" in the enclosed PDF of the DESC SRD for instructions on how to use and cite those products. The DESC SRD is described on <a href="https://arxiv.org/abs/1809.01669">arXiv</a> as follows:</p> <p>The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. The Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment.</p>
Survey Data: Public Engagement with Science: A Survey for India Alliance Grantees
<p>Lately, the Indian research ecosystem has seen an upward trend in scientists showing interest in communicating their science and engaging with non-scientific audiences; however, the number and variety of science communication or public engagement activities undertaken formally by scientists remains low in the country. There could be many contributing factors for this trend. To explore this further, the science funding public charity in India, DBT/Wellcome Trust India Alliance (India Alliance), in a first of its kind of study by a funding agency in India, surveyed its 243 research grantees in November 2020 requesting their views on public engagement with science in India through an online survey. The survey included both quantitative as well as open-ended questions to assess the understanding of, participation in, and attitude of India Alliance Fellows/Grantees towards public engagement with research, identify the enablers, challenges, and barriers to public engagement for India Alliance Fellows/Grantees, understand the specific needs (training/capacity-building, funding, etc.) and develop recommendations for India Alliance as well as for the larger scientific ecosystem in the country. The survey showed that India Alliance grantees are largely motivated to engage with the public about science or their research but lack professional recognition and incentives, training and structural support to undertake public engagement activities.</p> <p>A shareable survey was designed using Microsoft Forms. The survey employed a mixed methods strategy and included 24 closed-ended questions (multiple choice and Likert scale) and nine qualitative questions, similar to open-ended questions. The questions were modelled on a similar survey carried out by Wellcome in 2016 to gather views of researchers on public engagement in Asia and Africa.</p> <p>The survey was shared by email with 243 Indian researchers in receipt of India Alliance fellowships or grants, out of which 137 (male – 78; female – 59) responded to the survey. Of these, 90 respondents were basic science researchers, 22 were clinical researchers, and 25 were public health researchers. A majority, i.e. 81% of the respondents indicated working as an independent researcher for more than 4 years (time post-PhD). Furthermore, 58% of the respondents were based at research institutions, 18% at higher education institutions, and 17% at central, state and private universities; these organisations geographically represent around 31 cities of India (9 respondents chose to not reveal their host institution in the survey). Periodic reminders were sent by email to the fellows to complete the survey. Three fellows who received funding from India Alliance for their public engagement projects were contacted via email after the survey for their views (in 50-150 words) on the public engagement funding programme of India Alliance. They were informed that their input is intended to be included in a report of the survey results, and they can choose to either stay anonymous or be credited. The data was collected from 27 November 2020 until 28 April 2021.</p> <p>Following the end of the survey, the data automatically mapped on Microsoft Excel was cleaned for duplication and errors. Microsoft Excel tools were used to analyse and visualise the data.</p> <p>The study did not undergo a formal ethical clearance process as the primary objective of the study was to gather insights of grantees to inform India Alliance’s public engagement support mechanisms. At the start of the survey, the objectives of the survey were clearly stated and the respondents were informed that the anonymized data of the survey may be communicated in the future. Participation in the survey was entirely voluntary.</p>
Mirror of data from NOAA U.S. Climate Reference Network for Research Computing in Earth Science
<p>This is a mirror of data from the NOAA U.S. Climate Reference Network (https://www.ncei.noaa.gov/products/land-based-station/us-climate-reference-network).</p> <p>It was created because outbound FTP access is not allowed from some cloud-based JupyterHub setups.</p>
Swiss Institutions and Online Ressources for the Historical Sciences
<p><strong>Datensätze aus der Datenbank infoclio.ch.</strong></p> <p>Die Datenbank des Fachportals für die Geschichtswissenschaften der Schweiz (infoclio.ch) enthält 1677 Datensätze zu schweizerischen Institutionen und 1326 Datensätze zu Online Ressourcen, die für die Geschichtswissenschaften von Bedeutung sind. Es sind lediglich Institutionen aus der Schweiz erfasst: historische Departemente, wichtige Bibliotheken, Archive sowie Forschungseinrichtungen und historische Gesellschaften. Unter den Bereich Online Ressourcen fallen online zugängliche Ressourcen wie Bibliothekskataloge, Inventare von Archiven, Quelleneditionen, Bibliografien, diverse Datenbanken etc.</p> <p>Die Datensätze enthalten einen Link zur Institution oder Online Ressource und einen kurzen Beschreibungstext. Bei den Institutionen ist zusätzlich die Adresse verzeichnet.</p> <p>Die Datensätze enthalten als Metadaten folgende Taxonomien: Formaler Schlüssel, Region, Epoche, Thema und Schlagworte. Die vollständigen Taxonomien sind in vier Sprachen in einer separaten Datei verfügbar.</p> <p><br> <strong>Verknüpfungen zwischen den Datensätzen:</strong></p> <p>Viele der Online Ressourcen gehören zu einer Institution. Die entsprechende Verknüpfung lässt sich in den Datensätzen der Online-Ressourcen mit der unter <institution-reference-nid> verzeichnete Nummer herstellen.</p> <p>Alle Datensätze sind mindestens in einer deutschen und einer französischen Version vorhanden. Einige Datensätze sind zusätzlich in einer englischen und/oder einer italienischen Version verfügbar. Die Verknüpfung zwischen den Übersetzungen kann über <translated-from-nid> hergestellt werden.</p> <p>Die Datensätze wurde 2008/2009 erstellt und 2017/2018 letztmals aktualisiert.</p> <p>########################</p> <p><strong>Jeu de données de la base de données infoclio.ch</strong></p> <p>La base de données du portail professionnel suisse pour les sciences historiques en Suisse infoclio.ch contient 1677 fiches sur les institutions et 1326 fiches sur les ressources en ligne qui présentent un intérêt pour les sciences historiques. Parmi les institutions sont recensés principalement les départements d’histoire des universités, les bibliothèques, les archives, les centres de recherche et les sociétés d’histoire de la Suisse. Parmi les ressources numériques sont recensées des ressources utilisables en ligne comme des catalogues de bibliothèques, des inventaires d’archives, des bases de données, des éditions de sources, des bibliographies, etc. </p> <p>Les fiches contiennent un lien web vers l’institution ou la ressource en ligne et une courte description. Pour les institutions, l’adresse est également mentionnée.</p> <p>Les fiches comprennent comme métadonnées les taxonomie suivantes: type de ressource, région, époque, thème et mot-clés. Les taxonomies complètes en quatre langues sont disponibles dans un fichier séparé.</p> <p><strong>Liens internes entre les fiches</strong></p> <p>De nombreuses ressources en ligne sont liées à des institutions. Dans les fiches des ressources en ligne, le lien correspondant peut être rétabli avec le numéro mentionné sous <institution-reference-nid>.</p> <p>Toutes les fiches sont disponible au minimum en Allemand et en Français. Certaines fiches sont également disponibles en Anglais et/ou en Italien. Les liens entre les traductions peuvent être rétablis avec le numéro mentionné sous <translated-from-nid>.</p> <p>Les données ont été créées en 2008/2009 et actualisées pour la dernière fois en 2017/2018.</p>
ICITS'23 - Understanding the Success Factors of Research Software: Interviews with Brazilian Computer Science Academic Researchers
<p>Artifacts used for data collection and analysis of the article accepted for publication in ICITS'23.</p> <p>Mourão, E., Trevisan, D., Viterbo, J. (2022).Understanding the Success Factors of Research Software: Interviews with Brazilian Computer Science Academic Researchers. In: ICITS'23 - 6th International Conference on Information Technology & Systems. Advances in Intelligent Systems and Computing, Springer, Cham.</p>
Open Chat Series: How-to-Advocacy "Why advocate for open scholarly communication in the social sciences and humanities?"
<p>On the 21.10.2022 Alíz Horváth, researcher, expert in East Asian studies, creator of “Humanista” podcast - and member of OPERAS's Special Interest Group "Advocacy" moderated an Open Chat with our guest speaker Per Pippin Aspaas, Head of Library Research and Publishing Support at the UiT in Tromsø, discussing the question "Why advocate for scholarly communication in the social sciences and humanities?"</p>
Products and Models for "Early Release Science of the Exoplanet WASP-39b with JWST NIRSpec G395H"
<p>Associated Publication: <a href="https://www.nature.com/articles/s41586-022-05591-3">https://www.nature.com/articles/s41586-022-05591-3</a></p> <p>Overview:<br> Measuring the abundances of carbon and oxygen in exoplanet atmospheres is considered a crucial avenue for unlocking the formation and evolution of exoplanetary systems. Access to an exoplanet’s chemical inventory requires high-precision observations, often inferred from individual molecular detections with low-resolution space-based and high-resolution ground-based facilities. Here we report the medium-resolution (R≈600) transmission spectrum of an exoplanet atmosphere between 3–5 𝛍m covering multiple absorption features for the Saturn-mass exoplanet WASP-39b, obtained with JWST NIRSpec G395H. Our observations achieve 1.46x photon precision, providing an average transit depth uncertainty of 221 ppm per spectroscopic bin, and present minimal impacts from systematic effects. We detect significant absorption from CO<sub>2</sub> (28.5<span class="math-tex">\(\sigma\)</span>) and H<sub>2</sub>O (21.5<span class="math-tex">\(\sigma\)</span>), and identify SO<sub>2</sub> as the source of absorption at 4.1 𝛍m (4.8<span class="math-tex">\(\sigma\)</span>). Best-fit atmospheric models range between 3 and 10x solar metallicity, with sub-solar to solar C/O ratios. These results, including the detection of SO<sub>2</sub>, underscore the importance of characterising the chemistry in exoplanet atmospheres, and showcase NIRSpec G395H as an excellent mode for time series observations over this critical wavelength range.<strong> </strong></p> <p> </p> <p> </p>
[Dataset] Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects - Graph Files
<p><strong>Explanation/Overview:</strong></p> <p>Corresponding graph files of the extracted Zooniverse networks described in D3.3 (can be found here), which are the result of our research that culminated into the publication "Does Volunteer Engagement Pay Off? An Analysis of User Participation in Online Citizen Science Projects", a conference paper for the conference CollabTech 2022: <a href="https://link.springer.com/book/10.1007/978-3-031-20218-6">Collaboration Technologies and Social Computing</a> and published as part of the <a href="https://link.springer.com/bookseries/558">Lecture Notes in Computer Science</a> book series (LNCS,volume 13632) <a href="https://link.springer.com/chapter/10.1007/978-3-031-20218-6_5">here</a>. Usernames have been anonymised.</p> <p>The graph files are in <code>.gexf</code> (graph exchange XML format) and <code>.gml</code> (graph modeling language) formats which can be used by common graph/network-analysis and visualisation tools such as Gephi.</p> <p><strong>Purpose:</strong></p> <p>The purpose of this dataset is to provide the basis for possible further examinations of the network structure, involving additional (not yet analysed) features such as the content of the comments etc.</p> <p><strong>Relatedness:</strong></p> <p>The data of the different projects was derived from the forums of 7 Zooniverse projects based on similar discussion board features. The projects are: 'Galaxy Zoo', 'Gravity Spy', 'Seabirdwatch', 'Snapshot Wisconsin', 'Wildwatch Kenya', 'Galaxy Nurseries', 'Penguin Watch'.</p> <p><strong>Content:</strong></p> <p>The dataset contains distinct graph files for each of the analysed projects. For each graph file, there are <em>nodes </em>and <em>edges</em> and their associated attributes (i.e., each edge can have an attribute). For the edges, apart from source and target, we have as attributes:</p> <ul> <li><code>weight</code></li> <li><code>project_title</code></li> <li><code>body </code>(i.e., text)</li> <li><code>created_at</code></li> <li><code>userRoles</code></li> <li><code>discussion_title</code></li> <li><code>discussion_id</code></li> <li><code>user_id</code></li> <li><code>board_title</code></li> <li><code>relation</code></li> <li><code>target_role</code></li> </ul> <p>For the nodes, the attributes are:</p> <ul> <li><code>user_id</code></li> <li><code>userRoles</code></li> <li><code>degree_reply </code>(i.e., degree for the reply relation)</li> <li><code>in_degree_reply</code></li> <li><code>out_degree_reply</code></li> <li><code>degree_comment</code></li> <li><code>in_degree_comment</code></li> <li><code>out_degree_comment</code></li> <li><code>degree_total</code></li> <li><code>in_degree_total</code></li> <li><code>out_degree_total</code></li> <li><code>target_role</code></li> </ul> <p><strong>Grouping:</strong></p> <p>Each graph file represents all the comments for the respective project across its lifespan irrespective of any time slices. Edges represent the comments and users represent the nodes. While the different boards are still contained within the data, all boards occur in the data.</p> <p> </p>
[Dataset] Is it a match? Motivations on citizen science volunteers and recruitment arguments in project descriptions
<p>This dataset contains the necessary details to reproduce the experiments of the paper:</p> <p><em>Kai Nils, W., Gutiérrez Páez,N.F., Sabel, O. and Hämäläinen, R. (2022) “Is It a Match? Motivations on Citizen Science Volunteers and Recruitment Arguments in Project Descriptions.” In Proceedings of the ECSA2022 conference: Citizen Science for Planetary Health, 69–70. <a href="https://2022.ecsa-conference.eu/files/ecsa/Bilder/ECSA2022_Conference_Proceedings.pdf">https://2022.ecsa-conference.eu/files/ecsa/Bilder/ECSA2022_Conference_Proceedings.pdf</a></em></p> <p>Data has been collected by quantitative triangulation. 1076 participants in citizen science projects answered a survey about the 12 motivational factors for participating. They had access to the survey by social media posts or email invitations sent to people in charge of projects. Data regarding motivational arguments in recruitment come from quantitative content analysis of 367 project descriptions of the website Zooniverse. The content analysis of the project descriptions was done manually by two coders independently. Then, both coders analysed their codings and reached consensus.</p>
Citizen Science Initiatives in Greece
<p>This dataset contains original mapping data developed in the process of the Greek Citizen Science landscape review. In total, 20 Greek Citizen Science projects were analysed according to a common framework. During the mapping process, we weren’t always able to find information on things that interested us e.g. project impact, stakeholder engagement, the size of the volunteering force. But just because we couldn’t find something does not mean the results or activities did not happen. It goes without saying that absence of evidence is not evidence of absence. Failure to find some information on our part can be explained by the fact that we worked primarily with internet sources, so we had to make do with whatever publicly available information we could find within reasonable time.</p>
Benefits and limitations of environmental magnetism for completing citizen science on air quality: a case study in a street canyon.
<p>Inside a street canyon in Montpellier (France) a total of 72 deposimeters were deployed in 29 households for a period of 3 months to measure local air quality. This street canyon was chosen because dwellers were already mobilized against the street traffic, and because they were in conflict on this issue with policy makers. The project aimed to include all the stakeholders through co-construction. The closure of the street during the metrological campaign and the absence of agreement curbed their involvement and motivation. However, the feedbacks from the citizen partners promote the fact that this study supported their claims and brought them a deeper understanding on the micro-scale air quality monitoring. Indeed, it is increasingly difficult for citizens, who seemed specifically interested in what is happening right outside their front door, to understand this measure with the emergence of ever more low-cost sensors. For that reason, we examined the citizen’s degree of confidence in magnetic monitoring of air quality and how can this technique be useful in their claims. The results show that magnetism can be a measurement technique favorable to citizen participation because it provides a large amount of data at the micro-scale of the street level, while the data from the certified associations for monitoring air quality requires a spatial interpolation to map variations on a neighborhood scale. In this study, we proposed a magnetic air quality index to standardize and democratize the magnetic monitoring of air quality to facilitate the dialogue with all stakeholders.</p>
Text-fig. 1. Iosif Vasilievich Kiselev in the later years of life. The figure from the archive of the Institute of Geography, National Academy of Sciences of Ukraine. in New Material Of The Puffer Fish Archaeotetraodon Winterbottomi Tyler Et Bannikov, 1994 (Tetraodontidae) From The Oligocene Of The Eastern Paratethys
Text-fig. 1. Iosif Vasilievich Kiselev in the later years of life. The figure from the archive of the Institute of Geography, National Academy of Sciences of Ukraine.
U.S. Science Journalists' Knowledge and Opinion of Open Access Articles as Sources
<p>Survey data of U.S. science journalists and their knowledge and opinions of OA research as news sources.</p>
Web Of Science (WOS-5736)
<p>Web Of Science (WOS-5736) is a collection of academic articles/journals. 5,736 documents classified in 11 classes.</p> <p>The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_<k>.pkl: pandas DataFrame with k-cross validation partition.</p>
Web Of Science (WOS-11967)
<p>Web Of Science (WOS-11967) is a collection of academic articles/journals. WOS-11967, with 11,967 documents partitioned across 33 categories;</p> <p>The files:<br> texts.txt: Document set (text). One per line.<br> score.txt: Document class whose index is associated with texts.txt<br> split_<k>.pkl: pandas DataFrame with k-cross validation partition.</p>
Dataset test: Master Data Science (LEB Oro)
<p>Archivo de prueba para la asignatura de ciclo de vida de los datos. El dataset contiene las estadísticas principales de los equipos de la LEB Oro (2022/2023) de las primeras 20 jornadas.</p>
Data for "A snapshot of the long term evolution of a distributed tectonic plate boundary" submitted to Science Advances
<p>This compressed folder contains data presented in Figures of the following paper: "<strong>A snapshot of the long term evolution of a distributed tectonic plate boundary</strong>" by M. Dalaison, R. Jolivet, L. Le Pourhiet; submitted to <em>Science Advances</em> in February 2023</p> <p>Please open the README.txt file for details about the folder's content</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.