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.
87
datasets available to search
ShareScore release 0.9.0
Dataset results
87 results for “data documentation”
Reference data and documentation for Skills4EOSC Deliverable D6.1 Mapping of existing professional networks
<p>This record presents the data underlying <strong>Skills4EOSC Deliverable D6.1 Mapping of existing professional networks</strong> and relevant documentation of the search string.</p>
Data and documentation from: Microclimate explains little variation in year-round decomposition across an Arctic tundra landscape
<p>The zip file contains data and code to reproduce the analysis in the submitted manuscript entitled <i>Microclimate explains little variation in year-round decomposition across an Arctic tundra landscape</i>. Please see the manuscript for further details on background, methodology, results and discussion.</p>
Fatiando a Terra data v1.0.0: A curated collection of open geophysics data for tutorials and documentation
<p>This repository holds curated sample datasets that can be used in the documentation and tutorials of the <a href="https://www.fatiando.org/">Fatiando a Terra</a> project. All datasets are cleaned and formatted versions of openly available data under permissive licenses or in the public domain.</p> <p>More information about datasets and the code for cleaning, formatting, and preprocessing the data can be found at: <a href="https://github.com/fatiando/data">https://github.com/fatiando/data</a></p> <p>See the README.md file for information on data sources and their original licenses.</p> <p><strong>NOTE:</strong> This collection uses <a href="https://semver.org/">semantic versioning</a> (i.e., MAJOR.MINOR.BUGFIX). Major releases mean that backwards incompatible changes were made to the data. Minor releases add new data without changing existing files. Bug fix releases fix errors in a previous release that makes the data unusable. Changes to the current data files will always be published as a major release unless the file(s) in the previous release was unusable/corrupted.</p>
Supplemental data from: "From lake to river: Documenting an environmental transition across the Jura/Knockfarril Hill members boundary in the Glen Torridon region of Gale crater (Mars)."
<p>This document, uploaded on the FAIR repository Zenodo, contains large data tables pertaining to the Supplementary Online Material of the above-mentioned article.</p> <p>These tables contain the complete list of individual MAHLI and ChemCam targets investigated, detailed laminae measurements and complete ChemCam compositional data.</p>
Models and Data for Simple Applications of BERT for Ad Hoc Document Retrieval
<p>This submission includes all pretrained models, test data and prediction files for the arXiv paper "<a href="https://arxiv.org/abs/1903.10972">Simple Applications of BERT for Ad Hoc Document Retrieval</a>". Please follow the instructions at the <a href="https://github.com/castorini/birch">Birch repo</a> to reproduce the results.</p>
AMSR-2 data for Pyresample quicklook documentation
<p>GCOM-W1 AMSR 2 data downloaded from Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA).</p> <p> </p> <p> </p>
The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example
<p>The TDI data and PSD/sensitivity-related files for PyCBC LISA documentation example, most of them are generated from LDC-Sangria<em> </em>dataset.</p>
Data Files and Documentation - National Coordination of Data Steward Education in Denmark
<p>This site contains the Data Files and Documentation Files from the National Coordination of Data Steward Education in Denmark Project (2019-2020). The main deliverables from the project are:</p> <p>The Main Report:</p> <p><a href="https://doi.org/10.5282/zenodo.3609516">National Coordination of Data Steward Education in Denmark</a> (<strong>Main Report</strong>)</p> <p>and</p> <p>Wildgaard, Lorna</p> <p><a href="https://doi.org/10.5281/zenodo.3628375">Reframing Data Stewardship educations in Denmark and abroad</a> (<strong>Wildgaard</strong>)</p> <p> </p> <p>List of available Data and Documentation Files below:</p> <p><strong>Wildgaard </strong>and<strong> Main Report (section 2 Review of Data Steward Education)</strong></p> <p><em>1. DS_education_1_review_thematic_analysis.nvp (NVIVO-file) </em></p> <p><em>2. DS_education_2_review_coding_scheme (Excel) </em></p> <p><em>(Created by Wildgaard, Lorna)</em></p> <p><strong>Main Report (section 3 LinkedIn analysis)</strong></p> <p>No data available due to GDPR</p> <p><strong>Main Report (section 4 Job vacancies analysis)</strong></p> <p><em>3. DS_education_3_vacancies_and_method.zip (zip-file) </em></p> <p><em>4. DS_education_4_vacancies_top10_word_frequencies_geographical_location (Excel) </em></p> <p><em>(Created by Vlachos, Evgenios)</em></p> <p>The zip-file contains a text file describing the method used in the analysis (Method) and 119 pdf files with Data Steward vacancies.</p> <p><strong>Main Report (section 5 Questionnaire)</strong></p> <p><em>5. DS_education_5_questionnaire_questions </em></p> <p><em>6. DS_education_6_questionnaire_survey_report </em></p> <p><em>(Created by Vlachos, Evgenios & Knudsen, Christian B.)</em></p> <p><strong>Main Report (section 6 Interviews)</strong></p> <p>7. <em>DS_education_7_interviews_summaries_interview_1-4</em> </p> <p><em>(Created by Hüser, Falco)</em></p>
Data Documentation WeatherAggReOpt
<p>This data documentation describes a data set of the German, France and Polish electricity system compiled within the research project “WeatherAggReOpt” (Developing Aggregation and Reduction Methods for Implementing Disaggregated Renewable Infeed Profiles in Energy System Models). The project is a collaboration between the Chair for Management Science and Energy Economics at the University of Duisburg-Essen and the Fraunhofer Institute for Solar Energy Systems (ISE). With a project period of three years WeatherAggReOpt (03ET4042A) is funded by the Federal Ministry for Economic Affairs and Energy (BMWi).</p>
Data set 3 photographic documentation BRAD research project
<p>Photographic documentation collected during the BRAD research project. For the personal data protection reasons, the published pictures do not represent recognizable people. The pictures present the places where part of the fieldwork was done (London, Croydon in the UK, Poznań in Poland). A separate folder contains images related to EUSS application.</p>
The STRINGS queries to identify documents related to the SDGs (+ country-SDG data)
<div>This page contains three documents related to the work the STRINGS team has developed on mapping research related to the Sustainable Development Goals (SDGs): <br>1. A document explaining the methodology used to create search queries for identifying documents related to SDGs 1-16. <br>2. An Excel file containing the search queries themselves. <br>3. An additional Excel file containing country-SDG level data used in the paper "Countries’ research priorities in relation to the Sustainable Development Goals".<br><br>The procedure for creating SDG queries was developed for the STRINGS project. For both the project and the paper, the procedure to identify SDG-related publications does not rely exclusively on search queries. We apply each SDG query to research areas obtained from a publication-level clustering algorithm, based on direct backward and forward citations. This enables us to select research areas related to SDGs and include all the publications contributing to that area. This approach has several advantages, including the ability to include publications that do not use SDG-related language in their abstract or title but still contribute to SDG-related research. <br><br>For further insights, the platform, data, and thresholds used to understand which research areas are associated with an SDG are openly available <a href="https://public.tableau.com/profile/ed.noyons#!/vizhome/UKStringsSDGtocommunities/Dashboard1">here</a>.<br><br>In the <a href="https://strings.org.uk/">STRINGS report</a>, you can explore applications to map and characterize publications and patents related to the SDGs. <br><br>Additionally, the paper "Countries’ research priorities in relation to the Sustainable Development Goals" provides a country-level analysis of the alignment between research priorities and SDG challenges. </div>
PSM-AP Comparative document analysis data: Priorities and challenges in the policy and digital strategies of ten PSM
<p>The document consists of a list of 61 key policy and strategy documents analysed as part of the comparative work conducted in WP1 of the project Public Service Media in the Age of Platforms (PSM-AP). It also contains a series of selected quotes supporting the three key areas prioritised by the policies and PSM digital strategies: People (reaching audiences), Personalisation (developing the video-on-demand portal), and Prominence (of PSM services and content). The data was collected and analysed in 2023, from documents concerning 10 PSM organisations in seven media markets: Belgium-Flanders (VRT), Belgium-Wallonia Brussels (RTBF), Canada (CBC/Radio-Canada), Denmark (DR, TV 2) Italy (RAI), Poland (TVP), and the UK (BBC, Channel 4, ITV). All quotes were translated to English by the authors.</p>
State of biodiversity documentation in the Philippines: Metadata gaps, taxonomic biases, and spatial biases in the DNA barcode data of animal and plant taxa in the context of species occurrence data
<p>These files can be categorized into three groups: (1) raw datasets obtained from public databases (i.e., GBIF, BOLD, and GenBank), (2) manually edited files needed for parsing and analysis, and (3) supplementary files for spatial analysis. All are used in the examination of gaps and biases present in Philippine biodiversity data, which can direct research on the taxa and spatial regions that need more sampling.</p>
Data Cleaning, Translation & Split of the Dataset for the Automatic Classification of Documents for the Classification System for the Berliner Handreichungen zur Bibliotheks- und Informationswissenschaft
<ul> <li>Cleaned_Dataset.csv – The combined CSV files of all scraped documents from DABI, e-LiS, o-bib and Springer.</li> <li>Data_Cleaning.ipynb – The Jupyter Notebook with python code for the analysis and cleaning of the original dataset.</li> <li>ger_train.csv – The German training set as CSV file.</li> <li>ger_validation.csv – The German validation set as CSV file.</li> <li>en_test.csv – The English test set as CSV file.</li> <li>en_train.csv – The English training set as CSV file.</li> <li>en_validation.csv – The English validation set as CSV file.</li> <li>splitting.py – The python code for splitting a dataset into train, test and validation set.</li> <li>DataSetTrans_de.csv – The final German dataset as a CSV file.</li> <li>DataSetTrans_en.csv – The final English dataset as a CSV file.</li> <li>translation.py – The python code for translating the cleaned dataset.</li> </ul>
musiXplora: Documentation - Data Retrieval
<h1>musiXplora: Structured Data Access</h1> <p>This documentation provides an overview of structured musiXplora data, that are now persistently accessible on Zenodo utilizing its DOI system. MusiXplora is a linked knowledge base for musicological and organological data developed and maintained by the <strong>Research Center <em>DIGITAL ORGANOLOGY</em></strong> at <strong>Leipzig University</strong>.</p> <p>Currently, the German versions are available only, but it is planned to extend this data after suitable translations were found.</p> <p>Code snippets will are provided for Python, JavaScript, and Bash (cURL), in order to assist with accessing the latest available data and retrieve the desired information efficiently.</p> <p>Rate Limits for Zenodo are listed <a href="https://developers.zenodo.org/#rate-limiting">here</a>.</p> <p>Available musiXplora-IDs with the corresponding latest DOIs are listed here: <a href="https://doi.org/10.5281/zenodo.11581620">musiXplora-Zenodo-Dictionary</a>.</p> <p>For further questions or requests, please refer to: redaktion@musixplora.de</p> <p>Version of Documentation: 0.0.1 (11 June, 2024)</p>
Survey on data access conditions for sensitive data - Raw Data and Documentation
<p>This Upload concerns the survey entitled “Survey on data access conditions for sensitive data” which was performed by The Dutch Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) and DANS, the Dutch national centre of expertise and repository for research data. The survey was launched in April 2024 and open until July 1st 2024. </p> <p>The goal of the survey was to gather additional information about access conditions and restrictions used by researchers using the DANS and ODISSEI services. The results of the survey can guide us to identify common conditions that should be included in a standardisation effort. Moreover, the results will improve the available guidance that DANS and ODISSEI can provide for their local research community. A comprehensive analysis of the survey and resulting recommendations will be published separately at a later point in time. </p> <p>This upload contains:</p> <ul> <li>a PDF with documentation of the survey, specifically the description and question text.</li> <li>an ODS spreadsheet with the raw data from the survey which was filled in by 46 participants. Please note that the survey was anonymous, no personal data of the respondents was collected. </li> </ul> <p>The survey was executed using EUSurvey (v1.5.3.1). EU Survey is open source and built by DG DIGIT and funded under the ISA, ISA2 and Digital Europe Programme (DIGITAL). EUSurvey is published under the EUPL licence and the source code is available from GitHub: https://github.com/EUSurvey.</p>
C. elegans data sample for Pergola documentation
<p>C. elegans data sample for Pergola documentation (<a href="http://cbcrg.github.io/pergola/quick_start.html">http://cbcrg.github.io/pergola/quick_start.html</a>). The sample data set consists in two folders: One named "worm_speeds" containing a CSV file for each of the tracked worms. From the several measures that can be found in the individual files, in this example we will use mid-body speed. The "mapping" folder contains the "worm_speed2pergola.txt", which sets the mappings between the information represented in the worm_speed files and the pergola ontology.</p>
Mouse data sample for Pergola documentation - Shiny visualization
<p>Data sample of feeding and drinking behavior recorded during three weeks of C57BL6/J male mice. The data correspond to 2 groups (9 control mice and 8 high-fat diet mice). Each animal was tracked individually on Phecomp cages for 9 weeks. During the first experimental week all animals were given <em>ad libitum</em> access to a standard chow (habituation phase). After this first week, control mice continued with the same diet regime while high-fat mice were exclusively given <em>ad libitum</em> access to a high-fat chow. Data was used originally in this publication <a href="http://onlinelibrary.wiley.com/doi/10.1111/adb.12595/abstract">10.1111/adb.12595.</a> The recordings were processed using Pergola to BED and BedGraph file formats.</p> <p>The data set consist in:</p> <p>- a exp_info.txt file setting mouse membership to the control or the HF mice.</p> <p>- a files folder containing BED and BedGraph files of mouse feeding behavior.</p>
Research data, sources and documents for thesis on Exploring Complexity Metrics for Artifact-Centric Business Process Models
<p>Research data, sources and documents for thesis on Exploring Complexity Metrics for Artifact-Centric Business Process Models This repository contains the supplemental material for the <a href="https://pqdtopen.proquest.com/pubnum/10759956.html">thesis "Exploring Complexity Metrics for Artifact-Centric Business Process Models" by Marin, Mike A., Ph.D., University of South Africa (South Africa), 2017.</a></p>
Survey Data Set Part 1 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering
<p>In 2017, we conducted an online survey to explore software professionals' attitudes towards videos as a documentation option for communication in requirements engineering. The survey covered the following topics:</p> <ul> <li>Demographics</li> <li>Attitude towards videos as a medium in RE including its strengths, weaknesses, opportunities, and threats</li> <li>Current production and use of videos in RE, respectively the obstacles that prevent the production and use of videos</li> </ul> <p>64 out of 106 software professionals from industry and academia completed the survey. The survey was implemented in LimeSurvey and distributed across several communication channels such as LinkedIn, ResearchGate, and a mailing list of a German RE professionals group.</p> <p>This dataset includes the following files:</p> <ul> <li>"Raw and analyzed data.xlsx" contains the raw and analyzed survey responses which are anonymized <ul> <li>This data includes <em>demographics </em>and <em>attitude</em>.</li> <li>The data on <em>video production and use</em> are included in: <a href="https://zenodo.org/record/4064741">Survey Data Set Part 2 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering</a>.</li> </ul> </li> <li>"Survey - Offline version.docx" contains the questions and possible answers of the survey</li> <li>"Survey - Offline version.pdf" contains the questions and possible answers of the survey</li> </ul> <p>This survey was designed, conducted, and analyzed by Oliver Karras (<a href="https://twitter.com/KarrasOliver">@KarrasOliver</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.