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1,719 results for “Making”
Social Decision-Making Risky Choice Task Dataset
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Memory and decision making dataset
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ShareTrait: a data portal for making trait data interoperable and reusable
<p><strong>Scope</strong></p> <p>This dataset provides the SQL version of the ShareTrait database, corresponding to <strong>ShareTrait version 1.2.0</strong>. It represents the structured database equivalent of the previously published dataset, <strong>ShareTrait: a data portal for making trait data interoperable and reusable</strong>, version 1.0.0 (Zenodo, July 12, 2023, <a href="https://doi.org/10.5281/zenodo.8138904" target="_new" rel="noopener">DOI: 10.5281/zenodo.8138904</a>). This version includes the database file, an SQL query, and the resulting output file generated from the SQL query. </p> <p><strong>Dataset content</strong></p> <p>The repository provides:</p> <ul> <li><strong>ShareTrait-database-v1.2.0.db</strong> : the database file.</li> <li><strong>master-query-all.sql</strong> : SQL query used for reconstructing the dataset.</li> <li><strong>master-query-output.csv</strong> : SQL query output file .</li> <li><strong>ShareTrait-dataset-database-mapping.csv</strong> : mapping of attribute fields from the SQL query output to the corresponding attributes in <a href="/records/8138904/files/ShareTrait_MetaData_v1.0.0.csv?download=1">ShareTrait_MetaData_v1.0.0.csv</a>, with relevant column name = "Column_name", version 1.0.0 (<a href="https://doi.org/10.5281/zenodo.8138904" target="_new" rel="noopener">DOI: 10.5281/zenodo.8138904</a>)</li> </ul> <p><strong>Access and usage</strong></p> <p>Files and documentation are available on GitHub: <a href="https://github.com/ShareTraitProject" target="_new" rel="noopener">ShareTrait Project</a>. Users can execute the SQL query by using either SQLiteStudio or SQLite3. Detailed instructions are provided in this repository <strong>README</strong>.</p> <p><strong>Citation</strong></p> <p>When using this dataset, please provide the following citation:</p> <p>Leiva, F., Ellers, J., Berg, M. P., Cuxart-Erruz, R., Barneche, D., Blackburn, T., Castañeda, L. E., Chown, S., Gaitán-Espitia, J. D., Gebauer Mery, P. H., Gomez Isaza, D., Hardy, I., Hermaniuk, A., Hirst, A., Jorissen, S., Keasar, T., Koene, J. M., Le Lann, C., Martorelli, I., Molinet C., Niklitschek E.J., Oliveira B., Olivier B., Orizaola G., Pilakouta N., Shameer K.S., Shokri M., Stoks R., Tougeron K., Tuni C., van de Pol I.L.E., van Dis N.E., Visser B., Vogels J., White C.R., Wu N., and Verberk W. (2025). ShareTrait: a data portal for making trait data interoperable and reusable (version 1.2.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.14826294" target="_new" rel="noopener">https://doi.org/10.5281/zenodo.14826294</a></p> <p>For further information, please contact: <a rel="noopener">i.martorelli@vu.nl</a></p>
A living catalogue of artificial intelligence datasets and benchmarks for medical decision making
<p>We provide a comprehensive curated catalogue of <strong>artificial intelligence datasets</strong> and <strong>benchmarks for medical decision making</strong>. At the time of first release (April 2021), the dataset contains more than 400 biomedical and clinical datasets of which 252 are publicly available or available upon request.</p> <p>The dataset was compiled based on a systematic literature review covering both biomedical and computer science literature and grey literature data sources. All datasets were manually systematized and annotated for meta-information, such as:</p> <ul> <li>Availability and licensing information</li> <li>Type of source data</li> <li>Links to source publications, main references or dataset repositories</li> </ul> <p>Benchmark dataset were additionally annotated for the following information:</p> <ul> <li>Associated task</li> <li>Performance metrics commonly used for evaluation</li> <li>Clinical relevance</li> <li>The availability of data splits</li> </ul> <p>In addition to the versioned TSV file on Zenodo, the dataset can also be explored live via <a href="https://docs.google.com/spreadsheets/d/1QjUxxnZ3tuyW5dj6nkt_o5yJcWUZec4ttfJxO8Zlty4/edit?usp=sharing">this Google Spreadsheet</a>. The dataset is intended as a living, extendable resource. Edit suggestions and additions are encouraged and can be submitted via the comment function of the Google sheet.</p> <p> </p> <p><strong>File descriptions</strong></p> <p><em>annotated-datasets.tsv</em> -- contains the annotated datasets</p> <p><em>arXiv-literature-export.tsv</em> -- contains the original literature record export from arXiv</p> <p><em>pubmed-literature-export.tsv</em> -- contains the original literature record export from PubMed</p> <p><em>README.md</em> -- contains a detailed description of all annotation fields</p>
Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs
<p>Datasets describing the fungal species diversity, microbial density and acidity of French sourdoughs, phenotypic variation of Kazachstania bulderi and Kazachstania humilis strains as well as the diversity of bread-making practices of 40 bakers and farmers-bakers.The data were collected, analyzed, and reported within the following publication :</p> <p>Elisa Michel, Estelle Masson, Sandrine Bubbendorf, Léocadie Lapicque, Thibault Nidelet, Diego Segond, Stéphane Guézenec, Thérèse Marlin, Hugo deVillers, Olivier Rué, Bernard Onno, Judith Legrand, Delphine Sicard and the participating bakers: <strong>Artisanal and farmer bread making practices differently shape fungal species community composition in French sourdoughs</strong>. PCI Evol. Biol.</p> <p> </p>
A list of newly (re)appearing alien species in Belgium in support of decision making
<h2><strong>Context</strong></h2> <p>Invasive alien species are an important driver of biodiversity loss. Policy responses are developed to address this threat and need to be based on the best available data, including information from alien species registries and occurrence data. The Tracking Invasive Alien Species (<a href="http://trias-project.be" target="_blank" rel="noopener">TrIAS</a>) project implemented a workflow based on FAIR principles to identify new species in Belgium. These are species that have been newly observed on the territory or that were newly added to a species registry or checklist. The workflow is built on the Global Biodiversity Information Facility (GBIF) and uses the Belgian Global Register of Introduced and Invasive Species (<a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">GRIIS Belgium</a>) as a baseline for comparison. </p> <h2><strong>Description</strong></h2> <p>This dataset contains the outputs of the <a href="https://trias-project.github.io/indicators/06_occurrence_indicators_appearing_taxa.html" target="_blank" rel="noopener">pipeline</a> that generates a list of new alien species occurring in Belgium. This pipeline retrieves alien taxa from openly published species checklists or occurrence datasets on GBIF and compares this list with the <a href="https://doi.org/10.15468/xoidmd" target="_blank" rel="noopener">Global Register of Introduced and Invasive Species - Belgium</a> (GRIIS Belgium) which is published by the IUCN Invasive Species Specialist Group (ISSG). This register is based on the <a href="https://github.com/trias-project/unified-checklist" target="_blank" rel="noopener">unified checklist of alien species in Belgium</a> which was created by TrIAS in support of research and policy using an open and reproducible workflow. Appearing/reappearing species are defined as follows:</p> <ul> <li>Appearing: an alien species which newly occurs on the Belgian territory in the three years before the year of the GBIF download used for creating the <a href="../records/10527772" target="_blank" rel="noopener">occurrence cube for non-native taxa in Belgium</a>. We will refer to this 3 years period as <em>evaluation period</em>.</li> <li>Re-appearing: an alien species reappearing on the Belgian territory after a latency of 4 years or more. For example, we consider a taxon reappearing in 2022 if observations occur in 2022 and 2018 or before.</li> </ul> <h2><strong>Files</strong></h2> <ul> <li><code>appearing_taxa.tsv</code></li> <li><code>reappearing_taxa.tsv</code></li> </ul> <h2><strong>Field values</strong></h2> <p>Field values of <code>appearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of appearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species occurs for the first time in protected areas of NATURA2000 in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species occurs for the first time in Belgium during the evaluation period(<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <p>Field values of <code>reappearing_taxa.csv</code>: </p> <ul> <li><code>taxonKey</code>: GBIF taxonKey</li> <li><code>canonicalName</code>: scientific species name</li> <li><code>year</code>: year of reappearance</li> <li><code>ncells_prot_areas</code>: number of 1x1km grid cells in protected areas</li> <li><code>ncells_BE</code>: number of 1x1km grid cells in Belgium</li> <li><code>in_prot_areas</code>: species reappears in protected areas of NATURA2000 in Belgium (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>in_BE</code>: species reappears in Belgium during the evaluation period (<code>TRUE</code>/<code>FALSE</code>)</li> <li><code>n_latent_years</code>: latency, in year, i.e. the number of years since last occurrence in Belgium</li> <li><code>class</code></li> <li><code>kingdom</code></li> <li><code>classKey</code></li> <li><code>kingdomKey</code></li> </ul> <h2><strong>Potential uses of the dataset</strong></h2> <p>The list of newly (re)appearing alien species in Belgium can be used for various purposes:</p> <ul> <li>to update the Belgian GRIIS checklist</li> <li>to flag the occurrence of new, regulated species on the territory (early warning)</li> <li>to develop a rapid response </li> <li>to select species for quick impact assessment</li> <li>to select species for risk assessment</li> <li>to draft alert lists</li> <li>for horizon scanning alien species</li> <li>to select species for risk assessment</li> <li>to identify new introduction patways</li> <li>...</li> </ul>
Bibliographic Data from the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review
<p>This database contains all the bibliographic information about the 8673 records found after applying the Search Strategy used for the Digital Twin Anomaly Detection Decision-Making for Bridge Management Systematic Review. Such strategy consisted on using seven initial keywords and similar terms of interest (namely: bridge and bridges, etc.): </p> <ul> <li>Bridge.</li> <li>Digital twin.</li> <li>Bridge information modelling.</li> <li>Finite elements.</li> <li>Bridge health monitoring.</li> <li>Anomaly detection algorithm.</li> <li>Cultural heritage.</li> </ul> <p>Six initial queries were done combining the first keyword with the rest of them:</p> <ul> <li>bridge* AND "digital twin*"</li> <li>bridge* AND (BrIM OR "bridge information model*")</li> <li>bridge* AND (FEM OR FEA OR "finite element method*" OR "finite element analy*")</li> <li>bridge* AND ("bridge health monitoring" OR "structural health monitoring")</li> <li>bridge* AND (ADA OR "anomaly detection algorithm*")</li> <li>bridge* AND ("cultural heritage" OR "monument* bridge*" OR "old bridge*" OR "ancient bridge*" OR "historic* bridge*")</li> </ul> <p>As a first screening step, the combination of these 6 initial searches was done to obtain relevant works containing at least three of the main keywords of interest:</p> <ul> <li>#1 AND #2</li> <li>#1 AND #3</li> <li>#1 AND #4</li> <li>#1 AND #5</li> <li>#1 AND #6</li> <li>#2 AND #3</li> <li>#2 AND #4</li> <li>#2 AND #5</li> <li>#2 AND #6</li> <li>#3 AND #4</li> <li>#3 AND #5</li> <li>#3 AND #6</li> <li>#4 AND #5</li> <li>#4 AND #6</li> <li>#5 AND #6</li> </ul> <p>All records found in Scopus where downloaded both in .ris and .csv format and are included in this database. The search was conducted on 10/12/2022.</p> <p>Note: Searches 10, 14, 17 and 21 did not return any records.</p>
Datasets and R source code of manuscript "Parasites make hosts more profitable but less available to predators"
<p>Data about experimentations of DIV-1 (virus) infection on Daphnia magna.</p> <p>Linked article: Parasites make hosts more profitable but less available to predators</p>
Artificial Intelligence for EU Decision-Making: Effects on Citizens Perceptions of Input, Throughput and Output Legitimacy
<p>The uploaded dataset was used for the statistical analysis of the pre-print "Artificial Intelligence for EU Decision-Making: Effects on Citizens’ Perceptions of Input, Throughput and Output Legitimacy" (Permanent identifier: <a href="https://arxiv.org/abs/2003.11320">arXiv:2003.11320</a>)</p> <p>A lack of political legitimacy undermines the ability of the European Union (EU) to resolve major crises and threatens the stability of the system as a whole. By integrating digital data into political processes, the EU seeks to base decision-making increasingly on sound empirical evidence. In particular, artificial intelligence (AI) systems have the potential to increase political legitimacy by identifying pressing societal issues, forecasting potential policy outcomes, informing the policy process, and evaluating policy effectiveness. This paper investigates how citizens’ perceptions of EU input, throughput, and output legitimacy are influenced by three distinct decision-making arrangements: (1) independent human decision-making (HDM); (2) independent algorithmic decision-making (ADM) by AI-based systems; and (3) hybrid decision-making by EU politicians and AI-based systems together. The results of a pre-registered online experiment (n = 572) suggest that existing EU decision-making arrangements are still perceived as the most democratic (input legitimacy). However, regarding the decision-making process itself (throughput legitimacy) and its policy outcomes (output legitimacy), no difference was observed between the status quo and hybrid decision-making involving both ADM and democratically elected EU institutions. Where ADM systems are the sole decision-maker, respondents tend to perceive these as illegitimate. The paper discusses the implications of these findings for (a) EU legitimacy and (b) data-driven policy-making.</p>
Dynamic meta-analysis: a method of using global evidence for local decision making (supplementary materials)
<p>Dynamic meta-analysis: a method of using global evidence for local decision making (supplementary materials)</p>
Evaluating demand forecasting models using multi-criteria decision-making approach
<p>The datasets added include the raw data, ANP weights calculations and TOPSIS ranking calculations for the demonstration case in the article titled: Evaluating demand forecasting models using multi-criteria decision-making approach.</p> <p>The files include a data explanation text file.</p>
Supplementary Information for "Nucleoside Phosphorylases Make N7-Xanthosine, a "Non native" Regioisomer of Xanthosine"
<p>This is the external Supplementary Information for our publication "Nucleoside Phosphorylases Make N7-Xanthosine, a "Non native" Regioisomer of Xanthosine".</p> <p>The .pdf file contains the Supplementary Information: author contributions, accessibility statement, experimental procedures, and supplementary items, among others.</p> <p>The .zip file contains the raw data and metadata for all items (supplementary and main text) as well as the calculation results. This includes UV, HPLC, NMR, HRMS, and DFT results. The full set of raw HPLC chromatograms is - unfortunately - only available to us in a proprietary file format but we are happy to share these data upon request. This revised version contains additional UV data on experiments excluding oxidation of xanthine to uric acid as well as additional NMR data on purified N7-xanthosine and reference data for N9-xanthosine and xanthine in D2O.</p> <p>To some extent, this work builds on and borrows from our previous publications on spectral unmixing (https://doi.org/10.3390/mps2030060, https://doi.org/10.1002/cbic.202000204), continuous reaction monitoring (https://doi.org/10.1021/acs.analchem.1c05356), and thermodynamic reaction control (https://doi.org/10.1002/adsc.201901230, https://doi.org/10.5281/zenodo.3568858, https://doi.org/10.1002/cphc.202000901, https://doi.org/10.1021/acscatal.1c02589).</p>
Dataset: High emission rates and strong temperature response make boreal wetlands a large source of isoprene and terpenes
<p>Dataset used in the article "High emission rates and strong temperature response make boreal wetlands a large source of isoprene and terpenes"</p> <p>The tab-delimited file contains direct surface-atmosphere Volatile Organic Compound fluxes, measured by Eddy Covariance with a Vocus- proton transfer reaction mass spectrometer (Vocus-PTR) at a subarctic fen during 2021. It also contains PAR (Photosynthetic Active Radiation), temperature and flux quality criteria.</p>
PhysiCell Studio: a graphical tool to make agent-based modeling more accessible. Supplemental material.
<p>Defining a multicellular model can be challenging. There may be hundreds of parameters that specify the attributes and behaviors of objects. In the best case, the model will be defined using some format specification, i.e., a markup language, that will provide easy model sharing (and a minimal step toward reproducibility). PhysiCell is an open source, physics-based multicellular simulation framework with an active and growing user community. It uses XML to define a model and, traditionally, users needed to manually edit the XML to modify the model. PhysiCell Studio is a tool to make this task easier. It provides a graphical user interface that allows editing the XML model definition, including the creation and deletion of fundamental objects: cell types and substrates in the microenvironment. It also lets users build their model by defining initial conditions and biological rules, run simulations, and view results interactively. PhysiCell Studio has evolved over multiple workshops and academic courses in recent years which has led to many improvements. There is both a desktop and cloud version. Its design and development has benefited from an active undergraduate and graduate research program. Like PhysiCell, the Studio is open source software and contributions from the community are encouraged. This dataset provides Supplemental material for the PhysiCell Studio publication.</p>
Making Archaeology FAIR[ER]
<p>In April 2018, at the Society for American Archaeology’s 83rd Annual Meeting in Washington, D.C., Sarah Whitcher Kansa, Julian Richards and Willeke Wendrich hosted a forum entitled ‘Making Archaeology Fair’ (see abstract below). The forum responded to a recently published <a href="https://www.nature.com/articles/sdata201618">article by Wilkinson et al.</a> outlining FAIR data principles, centred on avenues for making scientific data findable, accessible, interoperable and reusable. In preparation for this forum, I produced this illustrated graphic. </p>
IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 2nd Web-Delphi process to HTA stakeholders, organized in a single panel
<p>IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 2<sup>nd</sup> Web-Delphi process to HTA stakeholders, organized in a single panel (all stakeholder groups in a single panel, 2 rounds), about the views of stakeholders regarding “This aspect should be considered in the evaluation of new medicines on a common basis” (2019)</p> <p>For details on the Web-Delphi process, see: IMPACT HTA, Work Package 7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2, Deliverable 7.2 (Multi-criteria evaluation framework), Advancing knowledge and MCDA tools to assist HTA agencies in evaluating medicines on a common basis (2021) Oliveira, M.D. (IST), Panos Kanavos (LSE), Bana e Costa, C. (IST)</p>
IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 1st Web-Delphi process to HTA stakeholders, organized into 6 separate parallel panels
<p>IMPACT HTA, WP7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2 (Multi-criteria evaluation framework), Results of the 1<sup>st</sup> Web-Delphi process to HTA stakeholders, organized into 6 separate parallel panels (one panel per stakeholder group, 2 rounds), about the views of stakeholders regarding “This aspect should be considered in the evaluation of new medicines on a common basis” (2019)</p> <p>For details on the Web-Delphi process, see: IMPACT HTA, Work Package 7 (Methodological tools using multi-criteria value methods for HTA decision-making), Task 2, Deliverable 7.2 (Multi-criteria evaluation framework), Advancing knowledge and MCDA tools to assist HTA agencies in evaluating medicines on a common basis (2021) Oliveira, M.D. (IST), Panos Kanavos (LSE), Bana e Costa, C. (IST)</p>
Visualisation Techniques for Decision-making in Agriculture
<p>This dataset is the result of a systematic review conducted to survey visualisation techniques for decision-making in agriculture.</p>
Literature search for publication: A meta-analysis on the role older adults with cancer favour in treatment decision making
<p>Dataset belonging to 10.5281/zenodo.7308287 including data of literature search regardign outcome preference scale in geriatric oncology</p>
Making Social Science Research Transparent [Webinar recording]
<p>High-quality data have the potential to be reused in many ways. Archiving and publishing your data properly is at the core of making your data FAIR and will enable both your future self as well as others to get the most out of your data. Recently, more and more scientific journals are implementing open data policies, leading to researchers' dilemmas about where, when and how to publish the data. Consequently, the way that social science research is conducted and disseminated is gradually changing. A crucial element of that change is research transparency. Introduction to the topic took place in the first part of the event.</p> <p>In the second part, panellists presented in-depth the processes, policies and tools implemented for facilitating transparent research in the social sciences. They discussed the processes that need to be in place for an open research cycle, the role of data archives and repositories in sharing research data and materials, tools for reproducing research findings in practice, collaborations between archives and social science journals, and implementing Transparency and Openness Promotion Guidelines in different social science disciplines.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=B-phrIMETGk"> the CESSDA Training YouTube channel</a>.</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.