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103 results for “Research data management·”
Figure 2 from: Neylon C (2017) Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers. Research Ideas and Outcomes 3: e14673. https://doi.org/10.3897/rio.3.e14673
Figure 2 - The core issues and principles that a Research Data Management policy should address, adapted from Hodson and Molloy 2015
Figure 1 from: Neylon C (2017) Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers. Research Ideas and Outcomes 3: e14673. https://doi.org/10.3897/rio.3.e14673
Figure 1 - Illustration of the categories through which many research data management and sharing policies develop, with examples of the language used.
Figure 2 from: Neylon C (2017) Building a Culture of Data Sharing: Policy Design and Implementation for Research Data Management in Development Research. Research Ideas and Outcomes 3: e21773. https://doi.org/10.3897/rio.3.e21773
Figure 2 - The Cultural Science model of Hartley and Potts (2014).The co-creation of culture and group in the context of an external environment.
Figure 2 from: Neylon C (2017) Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers. Research Ideas and Outcomes 3: e21705. https://doi.org/10.3897/rio.3.e21705
Figure 2 - The core issues and principles that a Research Data Management policy should address, adapted from Hodson and Molloy (2015)
Figure 1 from: Neylon C (2017) Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers. Research Ideas and Outcomes 3: e21705. https://doi.org/10.3897/rio.3.e21705
Figure 1 - Illustration of the categories through which many research data management and sharing policies develop, with examples of the language used.
Supplementary material 1 from: Borghi J, Abrams S, Lowenberg D, Simms S, Chodacki J (2018) Support Your Data: A Research Data Management Guide for Researchers. Research Ideas and Outcomes 4: e26439. https://doi.org/10.3897/rio.4.e26439
A formatted version of the Support Your Data RDM rubric.
Wednesday 6 May: Research data Management across borders, Niels Brügger, Aarhus University
<p>Wednesday 6 May: Research data Management across borders, Niels Brügger, Aarhus University</p>
Research Data Management in Health and Biomedical Citizen Science: Practices and Prospects
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Data from: An ecosystem services perspective on brush management: research priorities for competing land use objectives
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Data from: General rules for environmental management to prioritise social-ecological systems research based on a value of information approach
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Data Publication accompanying the paper "Methods to Evaluate Lifecycle Models for Research Data Management"
<p>The publications listed in dlc.bib were collected in 2017 and analysed.<br> The xml representations can be found in raw<br> dlc.csv includes the data summary.<br> </p>
Figure 1 from: Briney KA, Coates H, Goben A (2020) Foundational Practices of Research Data Management. Research Ideas and Outcomes 6: e56508. https://doi.org/10.3897/rio.6.e56508
Figure 1 Simple workflow diagram for a Western Blot.
Figure 2 from: Briney KA, Coates H, Goben A (2020) Foundational Practices of Research Data Management. Research Ideas and Outcomes 6: e56508. https://doi.org/10.3897/rio.6.e56508
Figure 2 Example folder structure and file naming convention for a research team.
Data from: Data management, archiving and sharing for biologists and the role of research institutions in the technology-oriented age
Data are one of the primary outputs of science. Although certain sub-disciplines of biology have pioneered efforts to ensure their long-term preservation and facilitate collaborations, data continue to disappear, owing mostly to technological, regulatory and ideological hurdles. In this review, we describe the important steps towards proper data management and archiving, and provide a critical discussion on the importance of long term data conservation. We then illustrate the rise in data archiving through the Joint Data Archiving Policy and the Dryad Digital Repository. In particular, we discuss data integration and how the limited availability of large scale datasets can hinder new discoveries. Finally, we propose solutions to increase the rate of data preservation. For example, by generating mechanisms insuring proper data management and archiving, by providing training in data management, and by transforming the traditional role of research institutions and libraries as data generators towards managers and archivers.
Figure 1 from: Borisenko A, Young R, Hanner R (2024) A lab-centric, workflow-based data management system for environmental DNA research. Research Ideas and Outcomes 10: e120483. https://doi.org/10.3897/rio.10.e120483
Figure 1 Schematic representation of key ontological entities of an eDNA data management system.
Figure 2 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 2 - Information and data flows in the BVH system.
Figure 1 from: Canhos D (2017) Data Management Plan: Brazil's Virtual Herbarium. Research Ideas and Outcomes 3: e14675. https://doi.org/10.3897/rio.3.e14675
Figure 1 - System architecture of the BVH and supporting systems.
Figure 1 from: Neylon C (2017) Building a Culture of Data Sharing: Policy Design and Implementation for Research Data Management in Development Research. Research Ideas and Outcomes 3: e21773. https://doi.org/10.3897/rio.3.e21773
Figure 1 - The Institutional Analysis and Design framework adapted from (Ostrom 2005).
Figure 1 from: Irawan D, Rachmi C (2018) Promoting data sharing among Indonesian scientists: A proposal of generic university-level Research Data Management Plan (RDMP). Research Ideas and Outcomes 4: e28163. https://doi.org/10.3897/rio.4.e28163
Figure 1 Current situation of data lifecycle (Irawan 2018).
Data from: Data management, archiving and sharing for biologists and the role of research institutions in the technology-oriented age
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ScienceDex guides
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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.