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.
219
datasets available to search
ShareScore release 0.9.0
Dataset results
219 results for “Management Practices”
Soil microbial and physicochemical data from watersheds impacted by different management practices or wildfire in the Southern Appalachian Mountains, 2023
Four forested watersheds in Western North Carolina with different management practices or disturbance were sampled in the summer of 2023 to compare soil physicochemical, microbial, and functional differences. These data include mineral soil physicochemical properties (location, elevation, aspect, gravimetric moisture content, pH, total carbon and nitrogen, total organic carbon, dissolved organic carbon and nitrogen, total dissolved nitrogen, dissolved inorganic nitrogen (NO3 and NH4), and microbial biomass carbon and nitrogen), soil microbial properties (16S ASV community sequences, ITS ASV community sequences, extracellular enzyme activity, carbon mineralization rates, and ammonium mineralization rates), and organic soil properties (total organic carbon, total carbon and nitrogen, 16S ASV sequences, pH, and moisture). Together, this dataset provides context to understanding the impacts of different management practices and relevant disturbances, such as severe wildfire, on soil in the Southern Appalachian region.
Quantitative Assessment of Research Data Management Practices - 2023
<p>This survey investigates <strong>Research Data Management (RDM) practices across five Swiss higher education institutions</strong>, including EPFL, ETH Zürich, Eawag, FHNW, and DaSCH, with the goal of gathering insights into how researchers manage data and code throughout the lifecycle of their projects, as well as using such findings to inform academic services related to RDM for researchers. Previous surveys, conducted at EPFL in 2017, 2019, and 2021, primarily focused on the planning and publishing stages of the research data lifecycle, such as data management planning and open data dissemination. The 2023 edition expanded to other institutes and places a stronger emphasis on <strong>Active Data Management</strong>, particularly during research projects, including a range of topics such as:</p> <ul> <li>Storage and backup solutions</li> <li>Data and code sharing platforms</li> <li>Documentation and metadata usage</li> <li>Compliance with legal and ethical standards</li> <li>Long-term data preservation strategies</li> <li>Use of open formats and open-source software</li> <li>Adoption of Data Management Plans (DMPs)</li> </ul> <p>This dataset was collected using the SurveyHero platform in compliance with GDPR and Swiss FADP regulations. enuvo GmbH acted as the data processor under a signed Data Processing Agreement. No personal identifiable information was purposefully collected, and data has been aggregated to further ensure respondents’ privacy.</p> <p>Included in this dataset:</p> <ul> <li>A CSV and XLSX file with the aggregated, anonymized data from the survey.</li> <li>Two PDF files containing graphical representations of the survey results, automatically generated by the SurveyHero platform in portrait and landscape mode.</li> <li>A README file providing context.</li> </ul> <p>This dataset is made openly available under the CC-BY 4.0 license. Users are encouraged to reuse it with appropriate attribution.</p>
Dataset for ELGO-DIMITRA Data Management Practices & Requirements: A Scoping Report
<p>This is a comprehensive data repository of the <em>data management survey</em> carried out in Autumn of 2023 through a collaboration between the <a href="https://opensciencestudies.eu/">PHIL_OS</a> project and the <a href="https://agres.elgo.gr/">Research Directorate of the Hellenic Agricultural Organization ELGO-DIMITRA</a>.</p> <p>Please cite as: </p> <blockquote> <p>Tsiroukis F., Leonelli S. and ELGO-DIMITRA (2024) <em>Dataset for ELGO-DIMITRA Data Management Practices & Requirements: A Scoping Report.</em> PHIL_OS Report. DOI: 10.5281/zenodo.14003418</p> </blockquote>
IPBES Data Management Tutorials - Session 6.1: Data management best practices
<p>The <em>IPBES data management tutorials</em> are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The chapter on<em> Examples of implementing the IPBES data management Policy</em> contains examples of how certain data management tasks and workflows were implemented within IPBES so that they follow the data management policy. <strong>Currently, this chapter contains legacy videos and the most recent examples can be found within the IPBES technical guidelines here:</strong> <a href="https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines">https://ict.ipbes.net/ipbes-ict-guide/data-management/technical-guidelines</a></p> <p>This session,<em> data management best practices</em>,<em> </em>provides a general review of some best practices of data management and what to expect for this chapter.</p>
Quantitative assessment of research data management practice - University of Bordeaux
<p>This survey was run at the University of Bordeaux in January 2019 using the questionnaire "Quantitative assessment of research data management practice" :</p> <p>Teperek, M., Krause, J., Lambeng, N., Blumer, E., van Dijck, J., Eggermont, R., … der Velden, Y. T. (2019). Quantitative assessment of research data management practice. Retrieved from : <a href="https://osf.io/mz3fx/">https://osf.io/mz3fx/</a></p> <p>The questionnaire included all the primary and secondary common questions, institution-specific questions regarding services and file sharing (EPFL questions), institution-specific questions for profile information.</p> <p>Data from the 425 responses collected are published here.</p> <p>Details regarding data collection and curation are included in the README file.</p> <p> </p>
Mapping practices of online community management
<p>Results of an online survey conducted during the period 13-31st March 2018. Responses were collected through a Google form; instructions and context were made available on a <a href="http://www.cottica.net/2018/03/13/mapping-online-community-management-practices-can-i-have-a-little-help-with-my-thesis/">web page</a>, the link of which was disseminated through Facebook, Twitter and on the e-mint mailing list (dedicated to professional online community managers on Yahoo. </p> <p>Each row of the file represents one questionnaire; each column represents one question.</p> <ul> <li>The first 9 questions are all of the format "To manage your online community, which of these courses of actions do you take, and how often?". The answers were given on a Likert-4 scale.</li> <li>The 10th question was "Do you want to add any other activity that uses up significant chunks of your community management time?". The answers were given in free form text.</li> <li>The 11th question was "How old is the community you manage? If you manage more than one, refer to the oldest." The answers were given as multiple choice, with three possible choices.</li> <li>The 12th question was "How large is the community you manage? If you manage more than one, refer to the largest.". The answers were given as multiple choice, with five possible choices.</li> </ul> <p>This work is part of my PhD Thesis.</p>
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 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>
Dataset of Survey on Current Email Management Practices
<p>This dataset contains anonymised survey responses from a comprehensive study conducted to explore current email management practices among users. The survey aimed to gain insights into how individuals handle and organize their email communications in various contexts. The survey questionnaire consisted of carefully designed questions related to email usage patterns, organisational strategies, folder structures, and automation utilised for email management. The survey also explored participants' preferences for automated rule-based filtering functionality and any challenges they face in effectively managing their mailbox.</p> <p>Researchers and professionals interested in email management and information organisation can leverage this dataset for research, analysis, and potential improvements in email client design and functionality.</p> <p>We kindly request that any publications or research utilising this dataset appropriately acknowledge and cite the original source to ensure proper attribution to the survey and its participants.</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>
Fig. 1 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 1. Map of Bowater Mersey Paper Company Ltd land in Nova Scotia. Bowater Mersey lands highlighted. Site descriptions: 1 & 2 – 40-80 yr, CT; 3 & 4 – 40-80 yr, none; 5 – 80-120 yr, US; 6 & 7 – 80- 120, none; 8 – 120+ yr, S; 9 – 120+ yr, S/SH; 10 & 11 – 120+ yr, none. CT = Commercial thinning; US = Uniform selection harvest; SH = Shelterwood harvest; S = Selection harvest.
Fig. 2 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 2. Overstory composition for dominant tree species based on importance value (Importance Value = Relative Density + Relative Dominance + Relative Frequency). Site descriptions: 1 & 2 – 40-80 yr, CT; 3 & 4 – 40-80 yr, none; 5 – 80-120 yr, US; 6 & 7 – 80-120, none; 8 – 120+ yr, S; 9 – 120+ yr, S/SH; 10 & 11 – 120+ yr, none. CT = Commercial thinning; US = Uniform selection harvest; SH = Shelterwood harvest; S = Selection harvest.
Fig. 7 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 7. Mean species richness of beetles in different forest stand age classes, including standard deviation from both the present study and Bishop (1998).
Fig. 5 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 5. Rarefaction curve demonstrating projected species richness for number of individuals based on Bishop (1998), and the present study (Dollin et al.) beetle collections.
Fig. 8 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 8. Mean species richness across harvest treatment, including standard deviation, for 11 stands in southwestern Nova Scotia.
Fig. 3 in Saproxylic beetle (Coleoptera) communities and forest management practices in coniferous stands in southwest Nova Scotia, Canada
Fig. 3. Volume of coarse woody debris (CWD) by decay class for 11 stands in southwestern Nova Scotia as measured by Thompson (2004). Decay classes are summarized as follows: "1" is freshly dead, little to no rot; in "2", the bole is mostly sound; "3" has well-established rot and significant bark loss; "4" is advanced decay; and "5" is rotted through but still of wood character. Site descriptions: 1 & 2 – 40-80 yr, CT; 3 & 4 – 40-80 yr, none; 5 – 80-120 yr, US; 6 & 7 – 80-120, none; 8 – 120+ yr, S; 9 – 120+ yr, S/SH; 10 & 11 – 120+ yr, none. CT = Commercial thinning; US = Uniform selection harvest; SH = Shelterwood harvest; S = Selection harvest.
Information flows around agricultural best management practices in central Pennsylvania
<p>This dataset was collected between February and April 2019, to assess the information network of agricultural Best-Management Practices (BMPs) in central Pennsylvania, a sub-region of the Chesapeake Bay watershed.</p> <p>It contains information flows (or "messages") relating to 16 specific BMPs, including:</p> <ul> <li>the BMP it relates to (e.g. riparian buffers, manure management planning, no-till, cover-cropping, etc.);</li> <li>the source and target of the information (actors);</li> <li>the kind of message (e.g. funding, regulation, technical assistance, etc.);</li> <li>the weight (strength) of messages (only for those received by farmers directly).</li> </ul> <p>Over 3900 messages/information flows were recorded, involving 57 actors.</p> <p>This data was used to conduct the study "Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania".</p>
Digital Twins - from industrial management to healthcare practice
<p>A guest seminar offered by SCImPULSE Foundation CTO Taghi Aliyev for the University of Parma (IT) master "ARTE" https://www.masterarte-unipr.it/</p>
i-SoMPE Inventory A: List and description of 58 innovative soil management practices
<p>List and description of 58 innovative soil management practices (inventory A)</p>
i-SoMPE Inventory A: Adoption rate of 58 innovative soil management practices
<p>Adoption rate of 58 innovative soil management practices (maps of inventory 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.