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”
COVID-19: data and indicators to measure the return to work in Area Science Park after the emergency phase
<p>Data to measure the impact of SARS-CoV-2 virus on work, activities and services of Area Science Park and the return to work after the emergency epidemiological phase.</p> <p>Files available:</p> <ul> <li>Report Restart Area</li> <li>Stima_Presenze_Area_Science_Park</li> </ul> <p> </p> <p> </p>
Material for manuscript submitted to Earth and Space Science "Evaluation of a mesoscale coupled ocean-atmosphere configuration for tropical cyclone forecasting in the South West Indian Ocean basin"
<p>Configuration files for AROME Indian Ocean, NEMO and OASIS which are necessary to reproduce the results in the publication :</p> <p>Corale, L; Malardel S. , Bielli S. and M-N Bouin (2022) Evaluation of a mesoscale coupled ocean-atmosphere configuration for tropical cyclone forecasting in the South West Indian Ocean basin. <em>Earth and Space Science.</em></p>
Alligator Reef checklist.xlsx: the spreadsheet version of the checklist of Alligator Reef fishes, from Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.
<p>Alligator Reef checklist.xlsx: the spreadsheet version of the checklist of Alligator Reef fishes, from Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p>
AlligatorReefPhotos.pdf: a selection of images of various reef habitats on Alligator Reef, Florida Keys, from both the 1960s and today, for Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.
<p>AlligatorReefPhotos.pdf: a selection of images of various reef habitats from both the 1960s and today, for Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p>
Species Photos.zip Archive of fish species images for the publication of: Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.
<p>Species Photos.zip </p> <p>Archive of fish species images for the publication of:</p> <p>Starck, W.A., Estapé C.J. & Morgan Estapé, A. (2017) The fishes of Alligator Reef and environs in the Florida Keys: a half-century update. Journal of the Ocean Science Foundation, 27, 74–117.</p> <p>323 images, 318 species total,(5 species of Pomacentridae have pictures of both juvenile and adult phases)</p> <p>Carcharodon carcharias screen grab from video*<br> Centropristis ocyurus photo by C.Wangen<br> Dasyatis centroura screen grab from video by Ed. Martin<br> Diapterus sp. photo by Ed Martin. </p> <p>All other photos taken by Carlos Estapé and Allison Estapé in the study area (319 images of 314 species)</p> <p>*YouTube video - Snorkelers Spot Great White Shark Off Islamorada, https://www.youtube.com/watch?v=50l2grfaNQ4</p>
Metadata and index on social science research data
<p>The dataset contains metadata on social science research data.</p> <p>It is a snapshot of the metadata used for the creation of the search index for http://datasearch.gesis.org.</p> <p>Metadata-DC.20170713.tar.gz contains the raw XML Dublin Core metadata harvested via OAI-PMH. </p> <p>elasticsearch-2.4.4.-snapshot-20170713.tar.gz contains a corresponding elasticsearch v.2.4.4 index.</p> <p> </p>
Supplementary material 1 from: Humair F, Edwards P, Siegrist M, Kueffer C (2014) Understanding misunderstandings in invasion science: why experts don't agree on common concepts and risk assessments. NeoBiota 20: 1-30. https://doi.org/10.3897/neobiota.20.6043
Interview guideline: perception / valuation of ecosystem change related non-native, invasive plants
Dataset for Scrollytelling as as Strategy for Socio-Environmental Enagement: A Digital Citizen Science Narrative Approach
<p>Resulting Dataset on the evaluation of Scrollytelling deliverables developed by higher education students based on citizen science projects.</p>
Co-curricular Quantitative Data Analytics Training Program (CQDATP) for Undergraduate Natural Science Students
<p>While data analytics has increasingly become an essential skill for various professionals in natural science fields, college curricula often cannot be updated frequently to meet the emerging changes of the workforce’s needs. A drastic curricular change is particularly difficult at small colleges with limited availability of faculty. This study proposes a co-curricular training program that enables natural science students to master skills of applying quantitative data analytics on real datasets without requiring a significant curricular change. The training program was developed and implemented as a sequence of in-person one-hour training sessions at a small four-year college. The results show that the approach is effective in improving students’ data analytics skills. This program can be adapted by other small institutions to achieve similar goals.</p> <p> </p> <p>This dataset include the training materials and deidentified student performance and survey responses. </p>
ScintiPi3 data sets for "First observations of severe scintillation over low-to-mid latitudes driven by quiet-time extreme equatorial plasma bubbles: conjugate measurements enabled by citizen science initiatives"
<p>ScintPi 3.0 data sets for "First observations of severe scintillation over low-to-mid latitudes driven by quiet-time extreme equatorial plasma bubbles: conjugate measurements enabled by citizen science initiatives" by Sousasantos et al. (2024).</p>
Benefits of Ontologies in Earth System Science
<p>The exponential growth of data due to technological developments along with an increased recognition of research data as relevant research output during the last decades substantiates fundamental challenges in terms of interoperability, reproducibility and reuse of scientific information. Being cross-disciplinary at its core, research in Earth System Science comprises divergent domains such as Paleontology, Marine Science, Atmospheric Sciences and Molecular Biology in addition to different types of data such as observation and simulation data. Within the various disciplines, distinct methods and terms for indexing, cataloguing, describing and finding scientific data have been developed, resulting in several controlled Vocabularies, Taxonomies and Thesauri. However, given the semantic heterogeneity across scientific domains, effective utilisation and (re)use of data is impeded while the importance of enhanced and improved interoperability across research areas will increase even further, considering the global impact of Climate Change to literally all aspects of everyday life. There is thus a clear need to harmonise practices around the development and usage of semantics in representing and describing information and knowledge. For a beneficial usage of semantic artefacts, sustainability is the key: any kind of terminology service must be maintained to guarantee that terms and relations are offered in a persistent way. But if they are, Vocabularies, Taxonomies, Thesauri and Ontologies can serve as a driving force for improved visibility and findability of research output within and across different research areas. Why Ontologies matter, what they are, and how they can be used will be depicted on our Poster in an easy-to-understand way.</p> <p> </p>
2023 Results of Complex Academic Integrity and Open Science Surveys of OPTIMA Project
<p>We publish the list of questions and results (datasets) of the complex survey conducted at the National level in Ukraine and within the Ukrainian partner universities of the <a href="https://lpnu.ua/en/optima">OPTIMA project</a> from Dec 04 – Dec 31, 2023. Identical surveys were conducted in <a href="https://doi.org/10.5281/zenodo.8067080">2021</a> and <a href="https://doi.org/10.5281/zenodo.8067262">2022</a>.</p> <p>The survey aims to study the attitude of Ukrainian students and the academic community toward the values of academic integrity and open scientific practices, as well as to identify typical examples of dishonest behavior in Ukrainian higher education institutions. Participation in the survey was voluntary and anonymous, and its results (collected data and their analysis) will be published in open access. Ethical approval for the survey was waived by the Ethics Committee of the Lviv Polytechnic National University Academic Board. This waiver of approval was provided due to non-sensitive data obtained from the survey respondents. </p> <p><strong>Number of participants in the complex survey in 2023:</strong></p> <ul> <li>National Survey - 4560</li> <li>Lviv Polytechnic National University - 530</li> <li>Sumy State University - 327</li> <li>Vasyl Stus Donetsk National University - 231</li> <li>Lutsk National Technical University - 146</li> </ul>
Open Source Software in Data Science
<p>This upload includes an anonymized data set of a survey first launched in 2022. The survey has been revised since. The data set. however, contains answers of the first launch.</p>
Data coverage, biases, and trends in a global citizen-science resource for monitoring avian diversity
<p><strong>Aim:</strong> Understanding and addressing the global biodiversity crisis requires ecological information compiled continuously from across the globe. Data from citizen science initiatives are useful for quantifying species' ecological niches and geographical distributions but can be difficult to apply towards biodiversity monitoring. The presence of fixed geographical locations reduces the opportunistic nature of citizen science data, allowing for more reliable and nuanced trend estimation. The eBird citizen-science programs contains predefined locations whose bird assemblages are sampled across years ('hotspots'). For hotspots to function as a biodiversity monitoring resource, issues related to data coverage, biases, and trends need to be addressed.</p> <p><strong>Location:</strong> Global.</p> <p><strong>Methods:</strong> We estimated the survey completeness of species richness at 300,500 eBird hotspots during the years 2002 to 2022. We documented sampling biases at eBird hotspot and non-hotspot locations during 2022 based on protection status, temperature, precipitation, and landcover.</p> <p><strong>Results:</strong> A total of 10,410 bird species (<em>ca</em>. 96.9% of total) were recorded at hotspots. The number hotspots and the quantity of data and unique participants and quality of species richness estimates has increased worldwide with the Nearctic containing the strongest and most consistent trends. Compared to non-hotspots, hotspots over sampled areas with higher protection status. Hotspots and non-hotspots over sampled warmer and wetter locations in the Antarctic, Nearctic, and Palearctic, and cooler locations in the Afrotropics, Australasia, and the Neotropics. Hotspots and especially non-hotspots over sampled urban areas. Hotspots and non-hotspots under sampled shrublands in Australasia. Hotspots and especially non-hotspots under sampled forests in the Afrotropics, Indomalaya, Neotropics, and Oceania.</p> <p><strong>Main conclusions:</strong> Hotspots have captured a large component of the world's avian diversity but have done so inconsistently across space and time. Data quantity and quality are increasing in many regions, but the presence of sampling biases and spatial uncertainty needs to be addressed when applying the data.</p>
Dataset: Problem-centred interviews results for Matching Data Life Cycle and Research Processes in Engineering Sciences
<p>The authors would like to thank the Federal Government and the Heads of Government of the Länder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.</p>
Рис. 14. Орест Александрович Скарлато. 1983 г. Архив Зоологического института РАН. in Orest A. Scarlato - scientist and organizer of science: on the 100th anniversary of his birth (1920-1994)
Рис. 14. Орест Александрович Скарлато. 1983 г. Архив Зоологического института РАН.
Scientific production of the University of Informatics Sciences in the period 2004-2020 in Scopus
<p><span>The data were part of the research to analyze the behavior of the scientific production of the University of Informatics Sciences of Cuba indexed in the Scopus database in the period 2004 to 2020, through a descriptive, longitudinal bibliometric study, the scientific production was analyzed. , research areas, and scientific collaboration in 366 records found.</span></p>
MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature
<p>Using the MaTableGPT tool, which extracts table data from material literature based on GPT, performance data of catalysts were extracted from 11,077 documents on OER catalysts. GPT-3.5 fine-tuning was conducted using 126 tables, achieving an accuracy of 96.8%. The data consists of DOI, catalyst, performance, and property(reaction_type, value, current_density, electrolyte, overpotential, potential, substrate, versus, condition). For more details, please refer to the DOI.</p>
Combined data file for Jokinen et al. "Terrestrial organic matter input drives sedimentary trace metal sequestration in a human-impacted boreal estuary", Science of the Total Environment 717, 2020
<p>The datafile contains all the new raw data presented in the figures in the publication.</p>
Video delle lezioni - Open Science come e perché / Corso Universitario Aggiornamento Professionale per Data Steward, Università di Torino marzo 2024
<p>Video delle lezioni su Open Science, FAIR data management, politiche europee per CUAP data steward Università di Torino</p> <p>Contenuto;</p> <ol> <li>[DA AGGIUNGERE]</li> </ol>
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.