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ShareScore release 0.9.0
Dataset results
144 results for “Scientific Data”
Scientific data: Laboratory modelling of urban flooding
<p>These datasets include experimental data obtained in the hydraulic laboratory. A detailed description of the datasets is available in the article. </p>
Data Availability Statements in the 2020 and 2021 scientific publications of Tampere University
<p>For this dataset, scientific peer-reviewed articles by Tampere University researchers from the years 2020 and 2021 were extracted from the TUNICRIS. A random sample of 40 percent was taken from the listed 4,922 publications according to faculties and years. There were 2,085 analyzed articles, i.e. more than 42 percent of the total number. </p> <p>To find Data Availability Statements, articles were opened one by one and searched for mentions of research data and its availability. For each article, it was written down whether DAS existed and where in the article it was located. From the contents of DAS, information about data availability, location, openness and possible restrictions on use was written down. </p> <p>Dataset also includes information about the journals and publications taken from TUNICRIS. </p> <p>The prevalence of DAS and data openness were examined in relation to different variables. Tampere University faculty information has been removed from the dataset. </p> <p>Related slides: https://doi.org/10.5281/zenodo.7655892</p> <p>Related article (in Finnish): Toikko, T., & Kylmälä, K. (2023). Tutkimusdatan saatavuustiedot tieteellisissä artikkeleissa: Raportti Data Availability Statementien käytöstä Tampereen yliopistossa. <em>Informaatiotutkimus</em>, 42(1-2), 31–50. https://doi.org/10.23978/inf.126098</p>
Salarios de Data Scientific en el mundo 2020-2023
<p>Set de datos con gráficos en Tableau para representar los sueldos por países de los científicos de datos según nivel de experiencia. Para ver el gráfico en Tableau. <div class='tableauPlaceholder' id='viz1692988108066' style='position: relative'><noscript><a href='#'><img alt='Cuadro de mando 1 ' src='https:&#47;&#47;public.tableau.com&#47;static&#47;images&#47;Su&#47;Sueldos_Data_Science&#47;Dashboard1&#47;1_rss.png' style='border: none' /></a></noscript><object class='tableauViz' style='display:none;'><param name='host_url' value='https%3A%2F%2Fpublic.tableau.com%2F' /> <param name='embed_code_version' value='3' /> <param name='site_root' value='' /><param name='name' value='Sueldos_Data_Science&#47;Dashboard1' /><param name='tabs' value='no' /><param name='toolbar' value='yes' /><param name='static_image' value='https:&#47;&#47;public.tableau.com&#47;static&#47;images&#47;Su&#47;Sueldos_Data_Science&#47;Dashboard1&#47;1.png' /> <param name='animate_transition' value='yes' /><param name='display_static_image' value='yes' /><param name='display_spinner' value='yes' /><param name='display_overlay' value='yes' /><param name='display_count' value='yes' /><param name='language' value='es-ES' /><param name='filter' value='publish=yes' /></object></div> <script type='text/javascript'> var divElement = document.getElementById('viz1692988108066'); var vizElement = divElement.getElementsByTagName('object')[0]; if ( divElement.offsetWidth > 800 ) { vizElement.style.minWidth='420px';vizElement.style.maxWidth='650px';vizElement.style.width='100%';vizElement.style.minHeight='587px';vizElement.style.maxHeight='887px';vizElement.style.height=(divElement.offsetWidth*0.75)+'px';} else if ( divElement.offsetWidth > 500 ) { vizElement.style.minWidth='420px';vizElement.style.maxWidth='650px';vizElement.style.width='100%';vizElement.style.minHeight='587px';vizElement.style.maxHeight='887px';vizElement.style.height=(divElement.offsetWidth*0.75)+'px';} else { vizElement.style.width='100%';vizElement.style.height='727px';} var scriptElement = document.createElement('script'); scriptElement.src = 'https://public.tableau.com/javascripts/api/viz_v1.js'; vizElement.parentNode.insertBefore(scriptElement, vizElement); </script><br> https://public.tableau.com/views/Sueldos_Data_Science/Dashboard1?:language=es-ES&publish=yes&:display_count=n&:origin=viz_share_link</p>
Scientific Value Agent companion data
<p>Companion data for the Scientific Value Agent manuscript. To use, unzip all tarballs into a "results" directory in the root of <a href="https://github.com/matthewcarbone/ScientificValueAgent">https://github.com/matthewcarbone/ScientificValueAgent</a>. All notebooks should then work as-is.</p> <p>Results from 23-09-02 have also been uploaded. These contain some data used in the supplementary data of our manuscript in which we fix the regularization parameter of our procedure.</p>
MCR LTER: Coral Reef: Data for figures in Doo, et al., Ocean acidification effects on in situ coral reef metabolism, Scientific Reports, 2019
These data result from a Free Ocean CO2 Enrichment (FOCE). Data include net community calcification (NCC), net community production (NCP), and net ecosystem calcification (NEC) for the figures in Doo, Edmunds and Cparpenter, Ocean acidification effects on in situ coral reef metabolism, Scientific Reports, 2019, https://doi.org/10.1038/s41598-019-48407-7. Data for Figure 2A describe the 24-h NCC collected in the in situ SCoRe-FOCE. Data for Figures 2B and 2C describe the offset of NCC of the high CO2 treatment from ambient collected in the in situ SCoRe-FOCE. Data for Figure 3 describe the correlation of NCP to NCC collected in the in situ SCoRe-FOCE. This material is based upon work supported by the U.S. National Science Foundation under Grant No. OCE 16-37396 (and earlier awards) as well as a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2018). This work represents a contribution of the Moorea Coral Reef (MCR) LTER Site.
Data from: Biocultural approaches to sustainability: a systematic review of the scientific literature
Current sustainability challenges demand approaches that acknowledge a plurality of human-nature interactions and worldviews, for which biocultural approaches are considered appropriate and timely. This systematic review analyses the application of biocultural approaches to sustainability in scientific journal articles published between 1990 and 2018 through a mixed methods approach combining qualitative content analysis and quantitative multivariate methods. The study identifies seven distinct biocultural lenses, i.e. different ways of understanding and applying biocultural approaches, which to different degrees consider the key aspects of sustainability science - inter and transdisciplinarity, social justice and normativity. The review suggests that biocultural approaches in sustainability science need to move from describing how nature and culture are co-produced to co-producing knowledge for sustainability solutions, and in so doing, better account for questions of power, gender and transformations, which has been largely neglected thus far.
Visibilidade e engajamento público na web 2.0: estudo altmétrico dos artigos publicados na Scientific Data
<p>A Web 2.0 tem causado impactos na comunicação científica. O uso das mídias sociais tem sido utilizado de maneira crescente para compartilhar produtos científicos, havendo diferentes dinâmicas de visibilidade e engajamento público. Nesse contexto, surge a Altmetria - área dos estudos métricos da informação que busca medir o impacto e circulação social da produção científica na web social. A pesquisa busca compreender aspectos da visibilidade e engajamento na Web 2.0 utilizando-se de métodos e técnicas altmétricas. Busca-se compreender dinâmicas relacionadas à tipos de atenção por mídia, indicadores de atenção, identificação de autoria do primeiro post, relação entre citação, leitor e menção. Os dados analisados referem-se a artigos científicos da revista <em>Scientific Data</em>, extraídos por meio da plataforma Altmetric, publicados entre 2014 a 2019. Constatou-se que o Twitter foi a mídia mais utilizada para a divulgação dos artigos; que o público em geral, seguido das revistas, são os principais responsáveis pela primeira menção dos artigos da revista analisada; que após publicados, a menção dos artigos nas mídias sociais é muito rápida; e, que não existe uma nítida relação de causa e efeito entre indicadores de citação, menção e número de leitores. Foram vislumbrados aspectos relevantes sobre o entendimento da visibilidade e engajamento público da produção acadêmica nas mídias sociais, auxiliando na compreensão das dinâmicas e características relacionadas aos indicadores altmétricos.</p>
Additional materials used in the paper "Towards Continuous Scientific Data Analysis and Hypothesis Evolution" on the Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
<p>This bundle contains a web page describing the materials used in the evaluation of the paper, along with references to the software and datasets, provenance metadata and workflows used. All the scripts and descriptions are included as well.</p>
Raw data of the experiments in "Examining the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific Applications" (REPPAR workshop at IPDPS 2017)
<p>Raw data of the experiments in "Examining the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific Applications" (REPPAR workshop at IPDPS 2017)</p>
Raw data of the experiments in "Towards the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific Applications" (ISPDC 2017)
<p>Raw data of the experiments in "Towards the Reproducibility of Using Dynamic Loop Scheduling Techniques in Scientific Applications" (ISPDC 2017)</p>
Data for figures and tables in: "Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument"
<p>Supplementary material to DESI's publication 'Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument' to comply with the data management plan.</p>
Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects. Dataset
<p>Tables containing the information about the projects funded by the Spanish AEI and publications acknowledging funding from Funder Registry. Both datasets where used in our publication: <em>Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects</em>.</p>
The Earth Surface System Scientific Data Thesaurus
<p>The Earth Surface System Scientific Data Thesaurus</p>
Scientific Data Item Recommendation Benchmark Corpus
<p>Open-source generalized benchmark corpus to evaluate scientific data item (e.g. dataset or paper) recommendation methods.</p>
Analysis of shared research data in Spanish scientific papers about COVID-19: a first approach
<p><strong>Introduction:</strong> During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. <strong>Objective: </strong>To study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. <strong>Methodology:</strong> Qualitative and descriptive study applying nine attributes: (1) availability, (2) accessibility, (3) format, (4) licensing, (5) linkage, (6) funding, (7) editorial policy, (8) content and (9) statistics. <strong>Results:</strong> We analyzed 1340 papers, 1173 (87.5%) did not have research data. 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data and 5.2% share their data as supplementary material. <strong>Conclusions:</strong> There is a small percentage that shares their research data, however it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.</p>
Raw Bibliobmetric Data for the article "The Scientific Landscape of Phytoremediation of Tailings: A Bibliometric and Scientometric Analysis"
<p>Bibliometric data for CiteSpace related to the scientific article "The Scientific Landscape of Phytoremediation of Tailings: A Bibliometric and Scientometric Analysis".</p>
Data for the paper "PETScML: Second-Order Solvers for Training Regression Problems in Scientific Machine Learning"
Open the record for dataset details and reuse information.
Scientific production data on the COVID-19 pandemic in Brazilian favelas and urban communities (2020-2022)
<p>Spreadsheet of data created for the dissertation ‘The COVID-19 pandemic in Brazilian favelas and urban communities: a bibliometric analysis’, PPGICS/ICICT, Fiocruz, to respond to the bibliometric analysis elaborated in the research, Brazil, Rio de Janeiro, May 2024. </p>
Metagenomics education in a modular CURE format positively affects students' scientific discovery perception and data analytical skills
<p>The targeted metagenomics study performed by Pollock et al. <em>(Pollock 2018)</em> was part of the Global Coral Microbiome Project <em>(Vega Thurber Lab 2014)</em>. Since the original publication of Pollock et al. <em>(Pollock 2018) </em>was written for a highly specialized academic public, we provided Bsc. students with a short introduction of the paper and guided them through the metadata table stored in the <em>gcmp16S_map_r25.txt </em>file under the <em>GCMP Australia sequence data, OTU tables, and metadata</em> folder (<a href="https://doi.org/10.6084/m9.figshare.c.3855466.v2">https://doi.org/10.6084/m9.figshare.c.3855466.v2</a>).</p> <p>In order to process the fastq-files and obtain OTU tables, a custom-made pipeline on a Galaxy instance <em>(Galaxy Community)</em> was used. This pipeline contained data analytical tools obtained from the Naturalis Biodiversity Center GitHub environment (<a href="https://github.com/naturalis">https://github.com/naturalis</a>). In order to align with the newest Galaxy best practices, we updated the tools and links to the original as well as the updated GitHub and toolshed versions are included in the references list.</p> <p>The names of the original raw fastq-files contain many dots which can hamper file-type recognition during downstream analyses in Galaxy. Therefore, prior to distributing the fastq-files to the students, these names were renamed using the ManageZIP tool <em>(The BLFS Development Team 1999-2023)</em>. Dots were replaced with underscores, with an exception made for the last 2 file type extension dots. For example, the file name <em>E1.2.Tur.pelt.1.20140814.M_S71_L001_R1_001.fastq.gz</em> was changed into <em>E1_2_Tur_pelt_1_20140814_M_S71_L001_R1_001_1.fastq.gz</em>. Similarly, the filenames in the metadata table were adjusted accordingly. The total collection of renamed file names is available through this zenodo repository as wel as the accompanying metadata file.</p>
Coral growth data from Dongsha Atoll - published in DeCarlo et al. (2017) in Scientific Reports
<p>Coral growth data (annual extension, density, and calcification) for massive <em>Porites</em> corals from the eastern reef flat and lagoon of Dongsha Atoll, South China Sea. The data are derived from computed tomography (CT) scans of coral skeletons. Please cite the following paper when using these data:</p> <p>DeCarlo, T. M. <em>et al</em>. Mass coral mortality under local amplification of 2 °C ocean warming. <em>Sci. Rep</em> <strong>7</strong>, 44586 (2017).</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.