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7 results for “FAIR digital objects”
Comparison tables for evaluating FAIR Digital Object and Linked Data
<p>RO-Crate and tables from the paper "<em>Evaluating FAIR Digital Object and Linked Data as distributed object systems</em>" <a href="https://doi.org/10.48550/arXiv.2306.07436">https://doi.org/10.48550/arXiv.2306.07436</a></p> <p>We systematically evaluate FDO and its implementations as a global distributed object system, by using five different conceptual frameworks that cover interoperability, middleware, FAIR principles, EOSC requirements and FDO guidelines themself.</p> <ul> <li>table1.html<br> Considering FDO and Web according to the quality levels of the Interoperability Framework for Fast Data (Delgado 2016)</li> <li> <p>table2.html<br> Mapping the Metamodel concepts from the Interoperability Framework for Fast Data (Delgado 2016) to equivalent concepts for FDO and Web.</p> </li> <li> <p>table3.html<br> Checking FDO guidelines (Bonino et al. 2019; Anders et al. 2023) against its current implementations as DOIP (DONA 2018) and Linked Data Platform (LDP) (Bonino da Silva Santos, Guizzardi, and Sales 2022), with suggestions for required additions</p> </li> <li> <p>table4.html<br> Comparing FAIR Digital Object (with the DOIP 2.0 protocol (DONA 2018)) and Web technologies (using Linked Data) as middleware infrastructures (Zarras 2004)</p> </li> <li> <p>table5.html</p> <p>Assessing RDA’s FAIR Data Maturity Model (FAIR Data Maturity Model Working Group 2020; Bahim et al. 2020) (first 2 columns) against the FDO guidelines (Bonino et al. 2019), FDO implemented with the protocol DOIPv2 (DONA 2018), Linked Data Platform (LDP) (Bonino da Silva Santos, Guizzardi, and Sales 2022) and examples from Linked Data practices in general. (— indicates Unspecified, may be possible with additional conventions)</p> </li> </ul> <p>A web rendering of this RO-Crate is available at <a href="https://w3id.org/ro/doi/10.5281/zenodo.8075229">https://w3id.org/ro/doi/10.5281/zenodo.8075229</a></p>
FAIR Digital Object and DiSSCo Research Infrastructure Design
<p>This presentation is about how <a href="https://dissco.eu">DiSSCo</a> (Distributed System of Scientific Collections) is using the FAIR Digital Object as the cornerstone of a research infrastructure design. DiSSCo -- a new Research Infrastructure currently in the preparation phase -- will digitally unify European natural science assets under common curation and access and will ensure that data is Findable, Accessible, Interoperable and Reusable (FAIR). DiSSCo will integrate a fragmented landscape of natural science collections, transforming it into a unified, robust, quality ensured knowledge base of unprecedented scale for bio- and geodiversity.</p> <p>With a brief historical context of FAIR Digital Object, this presentation introduces the concept of Digital Specimen. Then it highlights the incorporation of outputs from several <a href="https://rd-alliance.org/">RDA</a> (Research Data Alliance) interests and working groups in the design decision.</p>
Figure 1 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 1 Conceptual model of a Knowledge Object (KO) containing a payload, machine-actionable service and deployment specifications, metadata and a unique persistent identifier. We are exploring aligning our conceptual model with emerging best practices for FAIR Digital Objects. Derived from Wittenburg et al's Digital Objects as Drivers towards Convergence in Data Infrastructures (Wittenburg et al. 2019).
Figure 3 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 3 This figure illustrates the dual nature of Knowledge Objects: knowledge-as-resource and knowledge-as-service. A KO can be curated and maintained in a repository, pass metadata to a knowledge graph or deployed into applications. Different to other digital objects, the methods to deploy the KO to applications via custom or generic runtimes called by microservices are built into the KO.
Figure 2 from: Conte M, Flynn AJ, Barrison P, Boisvert P, Landis-Lewis Z, Friedman C (2023) Digital objects to make computable biomedical knowledge FAIR: an infrastructural approach to knowledge representation, dissemination and implementation. Research Ideas and Outcomes 9: e109307. https://doi.org/10.3897/rio.9.e109307
Figure 2 (L) Sample KO as viewed from the KGrid Library, from which the KO can be implemented in a hosted runtime environment or downloaded. (R) Sample output results from deploying the KO.
Supplementary material 1 from: Niehues A, de Visser C, Hagenbeek FA, Karu N, Kindt ASD, Kulkarni P, Pool R, Boomsma DI, van Dongen J, van Gool AJ, `t Hoen PAC (2022) A Multi-omics Data Analysis Workflow Packaged as a FAIR Digital Object. Research Ideas and Outcomes 8: e94042. https://doi.org/10.3897/rio.8.e94042
Members of the ACTION Consortium
Supplementary material 1 from: Agosti D, Bénichou L, Casino A, Nielsen L, Ruch P, Kishor P, Penev L, Mergen P, Arvanitidis C (2024) Liberate the power of biodiversity literature as FAIR digital objects. Research Ideas and Outcomes 10: e126586. https://doi.org/10.3897/rio.10.e126586
Liberate the power of biodiversity literature as FAIR digital objects
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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OpenNeuro
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