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.
1,069
datasets available to search
ShareScore release 0.7.1
Dataset results
1,069 results for “Data Management”
Quantitative assessment of research data management practice
<p>This survey aims to investigate research data management practices in academic institutions. The survey comprises questions common to all institutions as well as institution-specific ones. Common questions were drafted in the frame of a collaboration between several RDM services: Tu Delft (team effort), EPFL (team effort), University of Cambridge (notably Marta Busse) and University of Illinois (notably Heidi Imker). The first survey was run by TU Delft and EPFL only end of 2017. In total, 1263 responses where collected (680 from TU Delft, 235 from EPFL and 348 from the University of Cambridge) and are published here. The results of each institution are provided in Microsoft Excel 2007 (XLSX) format. Consolidated results are provided in CSV format</p> <p>The first lines of the CSV file contains the question asked to researchers. Each further line contains the response of a researcher; answers to institution-specific questions are set to N/A for researchers of the other institutions. Column delimiters are commas(,), quote chars are double-quotes (") and subfield separators are semi-columns (;). The text encoding is UTF-8.</p> <p>More information about this survey as well as the exact survey questions and a detailed description how the survey might be re-used by other institutions is available on the project page on the Open Science Framework: htts://osf.io/mz3fx/ For any questions contact datastewards@tudelft.nl or researchdata@epfl.ch</p>
Data set for risk management in the allocation of vehicles to tasks in transport companies using a heuristic algorithm
<p>The purpose of this dataset is to enable the replication of the research results presented in the article: Izdebski, M. (2023). Risk management in the allocation of vehicles to tasks in transport companies using a heuristic algorithm. Archives of Transport, 67(3), 139-153. https://doi.org/10.5604/01.3001.0053.7463 - published online: 2023-09-30, which discusses the allocation problem of vehicles to tasks, taking into account risk issues.</p> <p>Dataset contains:</p> <ul> <li>Readme.txt: description of the dataset</li> <li>InputData.xlsx: Contains the input data used in the model</li> <li>DistributionFit.xlsx: Compliance testing and distribution parameters for road accidents of any type and collision-type</li> <li>OutputAssignment.xlsx: Results of assignment and alghoritm tests</li> </ul> <p>The dataset was created as part of the E-Laas project (Energy optimal urban logistics As A Service).<br>Project implemented as part of the call ERA-NET Cofund Urban Accessibility and Connectivity (ENUAC China Call) organized by JPI Urban Europe and the National Natural Science Foundation of China (NSFC). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875022.<br> E-Laas project is carried out in an international consortium. Project coordinator in Europe: Chalmers University of Technology (Sweden), project coordinator in China: Shanghai University (China), consortium members: Tsinghua University (China), Warsaw University of Technology (Poland), cooperation partners: Stockholms stad, Trafikkontoret (Sweden), ParkUnload (Spain), Metropolis GZM (Poland), Shanghai Urban-Rural Construction and Transportation Department (China), Volvo Group Trucks Technology and Operations (Sweden).<br>- The Chinese part of the project is funded by National Natural Science Foundation of China.<br>- The Swedish part of the project is funded by Swedish Energy Agency.<br>- The Polish part of the project is funded by the National Science Centre, Poland (project no. 2022/04/Y/ST8/00134). The value of the co-financing is PLN 878,107.00. Project duration 27/04/2023 - 26/04/2026 (36 months).</p>
Respondents' perspectives on the impact of digital data-based health services on disaster risk management in Indonesia.
<p>This data contains respondents' perspectives on the impact of digital data-based health services on disaster risk management. Digital health services are the implementation of digital, information, and communication technologies in the context of health services. Digital health services include: mHealth, Health Information Technology, Wearable Devices, Telehealth and Telemedicine, and Personalized Medicine. </p> <p>Data was collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381) would be advisable.</p>
Research data management consulting requests at Charité - Universitätsmedizin Berlin
<p><strong>The dataset documents</strong> <strong>consulting requests and corresponding consultations on topics related to research data management </strong>at the Charité - Universitätsmedizin Berlin, a university hospital and large biomedical research institution. Version v2.0 includes requests between late 2018 and October 2024.</p> <p>Please note that the documentation is not complete. Sometimes it is detailed, sometimes very brief, and rarely notes are completely absent. In many cases, I made detailed notes outside of this table, and these are not included in the dataset.</p> <p>The shared files all contain the same information or a subset of it. Different file formats have been shared to facilitate reuse and text search.</p> <p>See the readme file for detailed description of data fields and further disclaimers.</p>
Data and statistical code for "Reconciling biodiversity with timber production and revenue via an intensive forest management experiment"
<p><strong>Abstract</strong></p> <p>Understanding how land-management intensification shapes the relationships between biodiversity, yield and economic benefit is critical for managing natural resources. Yet, manipulative experiments that test how herbicides affect these relationships are scarce, particularly in forest ecosystems where considerable time lags exist between harvest revenue and initial investments. We assessed these relationships by combining 7 years of biodiversity surveys (>800 taxa) and forecasts of timber yield and economic return from a replicated, large-scale experiment that manipulated herbicide application intensity in operational timber plantations. Herbicides reduced species richness across trophic groups (-18%), but responses by higher-level trophic groups were more variable (0–38% reduction) than plant responses (-40%). Financial discounting, a conventional economic method to standardize past and future cashflows, strongly modified biodiversity-revenue relationships caused by management intensity. Despite a projected 28% timber yield gain with herbicides, biodiversity-revenue tradeoffs were muted when opportunity costs were high (i.e., economic discount rates ≥7%). Although herbicides can drive biodiversity-yield tradeoffs, under certain conditions, financial discounting provides opportunities to reconcile biodiversity conservation with revenue.</p>
Data from: Species delimitation in endangered groundwater salamanders: implications for aquifer management and biodiversity conservation
Groundwater-dependent species are among the least-known components of global biodiversity, as well as some of the most vulnerable because of rapid groundwater depletion at regional and global scales. The karstic Edwards–Trinity aquifer system of west-central Texas is one of the most species-rich groundwater systems in the world, represented by dozens of endemic groundwater-obligate species with narrow, naturally fragmented distributions. Here, we examine how geomorphological and hydrogeological processes have driven population divergence and speciation in a radiation of salamanders (Eurycea) endemic to the Edwards–Trinity system using phylogenetic and population genetic analysis of genome-wide DNA sequence data. Results revealed complex patterns of isolation and reconnection driven by surface and subsurface hydrology, resulting in both adaptive and non-adaptive population divergence and speciation. Our results uncover new cryptic species diversity and refine the borders of several threatened and endangered species. The U.S. Endangered Species Act has been used to bring state regulation to unrestricted groundwater withdrawals in the Edwards (Balcones Fault Zone) Aquifer, where listed species are found. However, the Trinity and Edwards–Trinity (Plateau) aquifers harbor additional species with similarly small ranges that currently receive no protection from regulatory programs designed to prevent groundwater depletion. Based on regional climate models that predict increased air temperature, together with hydrologic models that project decreased springflow, we conclude that Edwards–Trinity salamanders and other co-distributed groundwater-dependent organisms are highly vulnerable to extinction within the next century.
Doctoral Students' Educational Needs in Research Data Management: Quantitative Data of Perceived Importance and Current Competencies
<p>These data sets include numerically coded answers to Likert-like scale questions concerning the importance and perceived current research data management competencies of doctoral students. Interviewees were 35 doctoral students and faculty members. Interview forms are attached. The data is connected with the research article: https://doi.org/10.2218/ijdc.v16i1.684</p>
Data and Code from: On-farm land management strategies and production challenges in United States Organic Agricultural Systems.
<p>This repository contains data and code used in:</p> <p>Isaac Mpanga, Russel Trondstad, Jessica Guo, David LeBauer, and John Omololu, 2021. On-farm land management strategies and production challenges in United States Organic Agricultural Systems. Current Research in Environmental Sustainability.</p> <p>It provides USDA Surveys of Agricultural Production from 2008-2019 to investigate state and national trends by state in organic farm area, number, and sales, as well to evaluate national trends in on-farm land-use practices and challenges facing US organic production.</p> <p>It also includes code used to transform, visualize, and analyze the data, and derived data products - notably organic farm area and sales with values imputed to correct for redacted state level measures.</p>
Data From: Toward a Better Data Management Plan: The Impact of DMPs on Grant Funded Research Practices
<p>Researchers from Montana State University analyzed 186 National Science Foundation (NSF) data management plans, using the Data Management Plans As a Research Tool (DART) rubric.</p>
Research Beyond the Lab, Spring Term 2022, Global Health Engineering, ETH Zurich. Raw data and analysis-ready derived data on waste management in public spaces in Zurich, Switzerland.
<p>This repository contains all raw and derived data produced as part of the <a href="https://rbtl-fs22.github.io/website/">ETH Zurich course "Research Beyond the Lab: Open Science and Research Methods for a Global Engineer" (151-8102-00L)</a> offered in spring term 2022.</p> <p>Students were assigned teams of four to conduct a collaborative research project broadly addressing the theme of “Trash in the Public Spaces of Zurich” in collaboration with <a href="https://www.stadt-zuerich.ch/ted/de/index/entsorgung_recycling.html">Entsorgung & Recycling Zürich (ERZ)</a>, the waste management department at Stadt Zürich.</p> <p>Research methods and design are taught in the first half of the course. Surveys and a waste characterisation study are then designed based on the research questions students have developed in their respective teams. The collected raw data is used in the course to teach principles of research data management, tidy data structures, reproducible research with R & RStudio, and collaboration and version control with Git & GitHub.</p>
Data from: Shifts in ground-dwelling predator communities in response to changes in management intensity in Alpine meadows
<p>Here, we provide raw abundance data from a small-scale case study on the effects of management intensity on ground-dwelling macro-invertebrate communities in extensively and intensively managed hay meadows in South Tyrol, Italy. The fauna was sampled with the pitfall trap methods in two seasons (autumn 2018 and spring 2019). The predatory groups Araneae, Opiliones, Carabidae, Staphylinidae, and Formicidae were identified to species level, the rest – where possible – to family level.</p> <p>The data can be found as absolute numbers (i.e., individuals per pitfall trap) and as standardised numbers (i.e., individuals per sampling day). Additionally, we provide ecological species traits on rarity (for the area of South Tyrol), moisture requirements and ecological tolerance, as well as the Red List statuses.</p>
ELIXIR-CONVERGE - Survey of benefits of an Data Management expert network
<p>The aim of this short survey to was to gauge the perceived benefits of having established a network of Research Data Management professionals across the ELIXIR nodes, as part of the ELIXIR-CONVERGE project. </p> <p>Survey responses to the following questions were collected between 17 May and 11 July 2022 after an open invitation to the <a href="https://elixir-europe.org/about-us/how-funded/eu-projects/converge/wp1/dm-network">ELIXIR Data Management Network</a>:</p> <ul> <li>Is the ELIXIR Data Management Network providing you with any benefit? </li> <li>What benefits?</li> <li>Ideas for more ways of working?</li> <li>Are you associated with an ELIXIR node?</li> <li>What is your role?</li> </ul> <p>Included are survey responses raw data, and a pdf that summarises the responses.</p> <p> </p>
Data on public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland
<p>A public participatory GIS -survey dataset detailing public perceptions of, attitudes towards, and values for managing urban green infrastructure for carbon, biodiversity, and well-being outcomes in Helsinki, Finland.</p>
Linked Open Data Management Services: A Comparison
<p>Thanks to a variety of software services, it has never been easier to produce, manage and publish Linked Open Data. But until now, there has been a lack of an accessible overview to help researchers make the right choice for their use case. This dataset release will be regularly updated to reflect the latest data published in a comparison table developed in Google Sheets [1]. The comparison table includes the most commonly used LOD management software tools from NFDI4Culture to illustrate what functionalities and features a service should offer for the long-term management of FAIR research data, including:</p> <ul> <li>ConedaKOR</li> <li>LinkedDataHub</li> <li>Metaphacts</li> <li>Omeka S</li> <li>ResearchSpace</li> <li>Vitro</li> <li>Wikibase</li> <li>WissKI</li> </ul> <p>The table presents two views based on a comparison system of categories developed iteratively during workshops with expert users and developers from the respective tool communities. First, a short overview with field values coming from controlled vocabularies and multiple-choice options; and a second sheet allowing for more descriptive free text additions. The table and corresponding dataset releases for each view mode are designed to provide a well-founded basis for evaluation when deciding on a LOD management service. The Google Sheet table will remain open to collaboration and community contribution, as well as updates with new data and potentially new tools, whereas the datasets released here are meant to provide stable reference points with version control.</p> <p>The research for the comparison table was first presented as a paper at DHd2023, Open Humanities – Open Culture,<strong> </strong>13-17.03.2023, Trier and Luxembourg [2].</p> <p>[1] Non-editing access is available here: <a href="http://docs.google.com/spreadsheets/d/1FNU8857JwUNFXmXAW16lgpjLq5TkgBUuafqZF-yo8_I/edit?usp=share_link">docs.google.com/spreadsheets/d/1FNU8857JwUNFXmXAW16lgpjLq5TkgBUuafqZF-yo8_I/edit?usp=share_link</a> To get editing access contact the authors.</p> <p>[2] Full paper will be made available open access in the conference proceedings.</p>
New Data Types in Data Management and Archiving [Webinar recording]
<p>New Data Types in Data Management and Archiving workshop focused on the management, archiving and access to new types of data (NDTs), i.e. administrative, transactional and social media data. The program consisted of four presentations tackling various issues related to handling the NDTs in data repositories and sharing these data in the community of social researchers. Martin Vávra (CSDA) was speaking about current capacities among CESSDA SPs for handling NDTs, Brian Kleiner (FORS) was talking about the coordinated approach to handling NDTs CESSDA SPs. Yevhen Voronin (GESIS) gave a presentation about social media data sharing in social research and Pascal Jurgens (Johannes Gutenberg University Mainz) was speaking about Social Science in the Embattled Digital Age: Adversarial Creation, Use and Sharing of New Data Types. The speakers’ presentations were followed by the panel discussion, where audience members were encouraged to participate and brought in their own experiences of archivists, data managers and researchers. The event was a part of the CESSDA training activities.</p> <p>The video is available on the <a href="https://www.youtube.com/watch?v=j13GsqwDO2Q">CESSDA Training YouTube channel.</a></p>
US National Native Bee Monitoring RCN Data Management Workshop: Public Domain Videos
<p>The US National Native Bee Monitoring Research Coordination Network (RCN) held a two-day workshop on data management best practices for native bee inventory, survey, and monitoring data on March 28 and 30, 2023. Videos in this data set were played at the workshop. These videos are released into the public domain. This data set includes the following videos:</p> <ul> <li>Ecological Metadata Standards to Enable Data Reuse by Julien Brun</li> <li>Useful Photo Management for Bee Species by Sam Droege</li> <li>Trait Data Models and Vocabulary by Jen Hammock</li> <li>Symbiota: open-source community portals for insect data management by Andrew Johnston</li> <li>Moving data from the field to the world by Jonathan Koch</li> <li>Exploring data using Discover Life by Clare Maffei</li> <li>USDA Data Sharing Policies and Opportunities by Cynthia Sims Parr</li> <li>Why Share Species Interaction Data? by Jorrit H. Poelen</li> <li>Big-Bee: Sharing Bee Interactions & Traits by Katja C. Seltmann</li> <li>Let’s talk about data by Katja C. Seltmann</li> <li>Responsible use of museum specimens & their data by Erika M. Tucker</li> </ul>
US National Native Bee Monitoring RCN Data Management Workshop: CC BY Videos
<p>The US National Native Bee Monitoring Research Coordination Network (RCN) held a two-day workshop on data management best practices for native bee inventory, survey, and monitoring data on March 28 and 30, 2023. Videos in this data set were played at the workshop. These videos are released with a CC BY license. Please cite the presenter(s) of the video(s) you use. This data set includes the following videos:</p> <ul> <li>The ABeeCs of Data Attribution: Please use your magic words by David Bloom</li> <li>Darwin Core Geography: How to make your locality data complete and accurate by David Bloom</li> <li>Best Practices for Managing Native Bee Molecular Data by Michael G. Branstetter</li> <li>A Trait Database for Bees by Elizabeth A. Crisfield</li> <li>Biotic interaction data and invasive species assessment by Quentin Groom</li> <li>OpenTraits Network (OTN) & TRY Plant Trait Database by Jens Kattge</li> <li>Semantics modeling of phenotypic trait data with ontologies by Diego S. Porto</li> <li>WorldFAIR: towards making plant-pollinator data FAIR by Maarten Trekels</li> </ul>
Data management in the social sciences in Macedonia [Webinar recording]
<p>This webinar aimed to introduce social science researchers to the basic principles of data management, including the creation of a Data management plan, which is an important tool for planning the research project.</p> <p>The webinar consisted of three parts. The first part introduced researchers with the basic principles of data management including the benefits of adopting Data management plans (DMPs). The DMP follows the research projects’ life cycle, starting with the initial phases of Planning and Organization and documentation of research data. This part also included a presentation of best practices for creation of appropriate structure of folders and data files, as well as instructions for their naming, documentation and organization.</p> <p>The second part of the webinar focused on the following three phases of the project life cycle: Data processing, Preservation and Protection. Contemporary social science presumes the respect of high level ethical standards during the handling of research data, in accordance with legal rules and best practices in this area.</p> <p>The last part of the webinar was dedicated to the phases of Publication - familiarizing the researchers with the possibilities of data preservation and publishing; and Data discovery - discussing the ways and means to acquire social science data, including the secondary use of data produced by other researchers.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=n05WTs58CMY"> the CESSDA Training YouTube channel</a>.</p>
Research Data Management and data protection in the Social Sciences [Workshop recording]
<p>This online workshop organized by The Austrian Social Science Data Archive (AUSSDA) focused on the Research Data Management basics, Data Management Plans and common data protection issues in the Social Sciences.</p> <p>The first part of the workshop was dedicated to RDM basics and Data Management Plans (DMPs). In many projects, DMPs are mandatory deliverables that need to be submitted at the beginning of a project and are updated throughout the project life cycle. During the workshop, it was explained which aspect funders expect to be part of DMPs in Social Sciences and how researchers can benefit from (writing) these documents.</p> <p>In the second part of the workshop, data protection issues that are common in Social Sciences were addressed and how they can be handled. In particular, differences in the curation of quantitative and qualitative data need in order to comply with data protection regulations in general and AUSSDA deposit guidelines in particular. Presentation on how AUSSDA scans quantitative data for potential data protection violations using STATA and gives participants the opportunity to test the code on their own data and devices.</p> <p>The video is available on<a href="https://www.youtube.com/watch?v=DhiL9J-Iwqg"> the CESSDA Training YouTube channel</a>.</p> <p> </p>
Supplementary data for "Ecological assessment of combined sewer overflow management practices through the analysis of benthic and hyporheic sediment bacterial assemblages of an intermittent stream"
<p><strong>Supplementary data for the Pozzi <em>et al.</em> paper entitled "Ecological assessment of combined sewer overflow management practices through the analysis of benthic and hyporheic microbial assemblages and a tracking of exogenous bacterial taxa in a peri-urban intermittent stream".</strong></p> <p># Created by Dr Adrien C. MEYNIER POZZI on June, 29th, 2023<br> # Part of DOmic research project funded by the Agence de l’Eau - Rhône Méditerranée Corse [AE-RMC, Project 2020 0702 DOmic, 2020-2023], and of the DOmic extension funded by the EUR H2O'Lyon [ANR-17-EURE-0018] of Université de Lyon<br> # Part of the Chaudanne river long-term experiment site belonging to the Observatoire de Terrain en Hydrologie Urbaine (OTHU)<br> # Part of the work conducted in the team on Opportinistic Bacterial Pathogen in the Environment (BPOE) led by Dr. Benoit Cournoyer<br> # Samples were obtained in 2 campaigns, corresponding to periods before (2010-2011) or after (2018) the implementation of the 91/271/EEC European Directive that limited Combined-Sewer Overflow (CSO) discharges to the Chaudanne river<br> # Samples consisted in surface water, benthic and hyporheic sediments taken in run, riffle and pool geomorphologic features, either upstream or downstream the CSO outlet, plus positive and negative controls</p> <table> <tbody> <tr> <td><strong>Metadata. Name and description of data tables provided as supplementary information</strong></td> </tr> <tr> <td><strong>Data Name</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Data S1. River hydrology variables and hydraulic gradients at surveyed transects</td> <td>Array to describe the hydrologic variables and gradients at the studied transects. Top line is header, second line is metadata for each recorded variable, and third line is the unit of the variable, if any.</td> </tr> <tr> <td>Data S2. Environmental variables (water physical-chemistry, nutrients, FIBs, MTEs, PAHs) with metadata</td> <td>An array to list environmental variables for all true samples (n=90) included in the study. Sample identifiers and dates are provided. First 8 rows list the CAS number, SANDRE number, unit, method, limit of quantification and norm for each variable, if any.</td> </tr> <tr> <td>Data S3. Hydrological indices and synthetic variables computed with ClustOfVar</td> <td>Hydrological indices computed for the river flow, precipitations and CSO overflows computed over a 3-week period preceding each sampling date.</td> </tr> <tr> <td>Data S4. Discharge events selected to compute CSO dilution ratios</td> <td>An array to describe CSO events included for the computation of the CSO dilution ratio (SI Data 6A) together with 6 tables and 3 figures (SI Data 6B to 6J) describing the CSO event ratio all year round over the studied period, as well as for events that occurred before or after the CSO was modified and during low flow or high flow season. In SI Data 6A, top line is header and second line is metadata for each recorded variable.</td> </tr> <tr> <td>Data S5. Raw environmental matrix for use in R</td> <td>An array to list experimental design and environmental variables for all true samples and controls. Several environmental variables were synthetized using the ClustOfVar method (Chavent et al (2012) 10.18637/jss.v050.i13). Format is directly usable in R software.</td> </tr> </tbody> </table> <p> </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.