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8 results for “research lifecycle”
Participatory Research Lifecycle
<p>This is a wheel that represents the participatory research lifecycle designed in the ACTION project (H2020)</p>
Research Data Management Lifecycle
<p>The Research Data Management (RDM) lifecycle describes the various phases of a research project from a data management perspective. The Cycle diagram illustrates all the steps with multiple levels of granularity and details. The text free images can be used for other purposes where a cycle diagram is needed.</p>
Research Data Management: Data Lifecycle
<p>This diagram has been created by the team of data steward at the University of Bologna (Alma Mater Studiorum - Università di Bologna, UniBo) in October 2022. It proposes a data lifecycle model inspired by the University of Virginia Library’s model (<a href="https://guides.lib.virginia.edu/c.php?g=515290&p=3522215">https://guides.lib.virginia.edu/c.php?g=515290&p=3522215</a>). It has been developed in parallel to the Research Data Management Decision Tree, available here: <a href="https://doi.org/10.5281/zenodo.7190004">https://doi.org/10.5281/zenodo.7190004</a></p> <p>Emphasis is put on a careful planning of data management, which should always precede data collection (and re-use of existing data). A reference to the opportunity of creating and maintaining a Data Management Plan (DMP) has been added. This is not always compulsory, but is increasingly required by funders.</p> <p>Collecting, analysing and storing data (and possibly sharing them with a group) remain at the heart of the lifecycle, constituting what we called “data handling”. Here, the process is not linear, and researchers tend to move from one stage to another in a recursive fashion. </p> <p>At any point during data handling, it is possible to deposit data: the responsibility for storing and safekeeping is passed on to the repository, the time-scale shifts from short-term to long-term, and data become citable (and possibly discoverable) by the wider scholarly community and beyond. Importantly, deposited data can always be re-used as the basis for a new round of collection/analysis/storage that will lead to a new deposit, and so on.</p>
Digital Twin or Digital Model: An Analysis of Definitions along the Product Lifecycle - Research data
<p>This research data contains the statements of the authors Grieves, Stark and Tao with regard to selected characteristics of Digital Twins. According to these statements different case studies along the product life cycle are classified as Digital Twin or Digital Model.</p> <p>Version 2 added a change in characteristic 2.</p>
Research Space and DMPTool - Streamlining the research lifecycle and enhancing FAIR principles with a series of interoperable tools
<p>A video demonstration of the integration between the Electronic Lab Notebook, RSpace, and the DMPTool. Presented at the FORCE11 annual conference on December 7, 2021.</p>
Digital Research Data Lifecycle
<p>This "Digital Research Data Lifecycle" diagram was first presented at the Digital Humanities Now Conference (27-29.January.2021), Stockholm University.<br>This diagram is part of the "Exploring the potential of 3D and spectral imaging methods and tools for understanding the past" invited presentation, given by V. Moitinho de Almeida.</p> <p>Further invited speakers: Douglas Biber (Northern Arizona University), Johanna Drucker (UCLA), Béatrice Joyeux-Prunel (University of Geneva), Christof Schöch (Trier University, Kathryn Eccles (University of Oxford), Tuomo Hiippala (University of Helisinki), Mike Kestemont (University of Antwerp), Jane Winters (School of Advanced Study, University of London), Anna Bentkowska-Kafel (King's College London; emerita), Giles Bergel (University of Oxford), Ian Gregory (Lancaster University), Nuria Rodríguez Ortega (University of Málaga). </p> <p>For more information about the Conference, please check: <a href="https://dahj.org/newsblog/dh-now">https://dahj.org/newsblog/dh-now</a></p> <p>Another way of citing this diagram: Moitinho de Almeida, V. (2021). “Digital Research Data Lifecycle”. In: <em>Exploring the potential of 3D and spectral imaging methods and tools for understanding the past</em> (presentation), Digital Humanities Now Conference (27-29.January.2021), Stockholm University. <a href="https://doi.org/10.5281/zenodo.14110887">https://doi.org/10.5281/zenodo.14110887</a></p>
Harvard Biomedical Research Data Lifecycle
<p>The Biomedical Data Lifecycle is a representation of stages in your research regarding data collection, use, and storage. At the core is how to "Store & Manage" the data for your project. How data is managed is integral to each stage in the diagram. Though the process is generally linear from "Plan & Design" to "Publish & Reuse," you may find yourself jumping around this lifecycle throughout your project. For example, "Data Management Plans" are created at the planning stage but will be used throughout the research process in subsequent stages. The plan dictates how you will handle the data collected and created, and how you will share and disseminate that data, all while considering data documentation, safety, and reuse. </p> <p>This lifecycle diagram was created by the <a href="https://datamanagement.hms.harvard.edu/">Harvard Longwood Medical Area Research Data Management Working Group</a>.</p> <p><strong>RDM-lifecycle-v5.png</strong>: This diagram depicts the core stages of the research lifecycle. The center of the wheel has a grey circle labeled "Store & Manage." The second layer is cut into six segments labeled "Plan & Design" in dark blue, "Collect & Create" in light green, "Analyze & Collaborate" in dark green, "Evaluate & Archive" in gold, "Share & Disseminate" in red, and "Publish & Reuse" in orange. Guiding arrows are at the edge of each segment, showing the process to be continuous like a wheel. In this version, all segment labels are in title case, and the "Evaluate & Archive" segment has been updated to gold to increase accessibility.</p> <p><strong>RDM-lifecycle-2tier-v5.png</strong>: This diagram includes an outer layer that represents the processes and concepts integral to each stage. The third layer expands the colors of each of the six sections and includes sub-elements of activities or resources that are involved in each of the six segments. In this version, all section labels are in title case, and the "Evaluate & Archive" segment has been updated to gold to increase accessibility.</p> <p><strong>RDM-lifecycle-2tier-v5-template.ai</strong>: Adobe Illustrator template can be used to customize the outer second tier text and the number of segments 2, 3, or 4, to meet the needs of different schools or data groups. Complete instructions for using the template can be found in the <a href="https://zenodo.org/record/8075934">zip file included in version 2</a>. These materials are licensed under a <a href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.</p>
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>
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.