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Presentations: Discipline specific systems with FAIR principles
Marian, Ludmila. (2023, June 14). Towards a FAIR-enabled Platform for the IAEA's Nuclear Data Collections and Services.
Feger, Sebastian Stefan, De Col, Valentina, AL-Najdawi, Moayad, Tobon, Hector, Martinez, German, Cadavid, Juan Carlos, & Bonaiuti, Enrico. (2023, June 14). Introducing FAIR Scores in a Global Agricultural Science Reporting Service: An Analysis of the First Reporting Period.
Sefton, Peter, Musgrave, Simon, & Thieberger, Nick. (2023, June 14). Towards a Generic Research Data Commons: A highly scalable standard based repository framework for Language and other Humanities data.
Fellegi, Zsófia, & Palkó, Gábor. (2023, June 14). Publishing Digital Text Editions on the Semantic Web.
|External Resource: Link to the Community Notes|
Towards a FAIR-enabled Platform for the IAEA’s Nuclear Data Collections and Services
This paper presents an approach towards creating a repository for nuclear data collections and services that implements the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The proposed platform provides an integrated environment for data collections, resources, and services to support the worldwide nuclear science and technology community. The repository is designed to organize different type of resources in a structured way and to provide a unified access point to all the heterogeneous collections that the Nuclear Data Section (NDS) hosts. The repository is implemented using a hybrid approach, where the core part of the system is based on the Invenio RDM framework. This part integrates with existing NDS and IAEA services, as well as with several newly built micro-services that implement specialized nuclear data retrieval and visualization products. In addition, the platform provides a secure and reliable environment to store and preserve nuclear resources. The presentation will provide a detailed description of the various aspects of the platform, including the architecture, data and service integration, security, and scalability.
Introducing FAIR Scores in a Global Agricultural Science Reporting Service: An Analysis of the First Reporting Period
1ICARDA; 2LMU Munich; 3CodeObia; 4CIAT
Communicating the meaning and value of the FAIR (Findable, Accessible, Interoperable, and Reusable) principles and suitable implementation strategies to research communities and their broader ecosystem is a crucial challenge. Automated FAIR scoring algorithms are being developed to provide immediate machine-driven insight into (meta)data compliance. They are also expected to return instructions to improve FAIR compliance where applicable. However, we still lack a systematic understanding of how automated FAIR scoring impacts adoption in repositories that implement them. Accordingly, we are excited to share findings from the first large-scale machine-driven FAIR scoring of global agricultural research at One CGIAR, a global partnership of international organizations dedicated to sustainable food production. Characteristics that make this analysis particularly interesting include the organization-wide visibility of the FAIR scoring and the mandatory reporting of all scientific resources in the preceding calendar year. We find that 39% of the 418 records received updates. Out of those, 7.3% resulted in improved FAIR scores. Those improved records outperformed the mean FAIR scores of the complete 2022 reporting data, while falling behind them before the update. We further show differences according to the knowledge product type and outline how we gather additional data on users’ perceptions for the OR2023 presentation.
Towards a Generic Research Data Commons: A highly scalable standard-based repository framework for Language and other Humanities data
1University of Queensland, Australia; 2Monash University, Australia; 3University of Melbourne, Australia
We will present a standards-based generalized architecture for large-scale repositories for research and preservation illustrated with real world examples drawn from a number of languages and cultural archive projects. This work is taking place in the context of the Australian Humanities and Social Sciences Research Data Commons, particularly the Language Data component thereof and the long-established PARADISEC cultural archive. The standards used include the Oxford Common File Layout for storage, Research Object CRATE (RO-Crate) for consistent linked-data description of FAIR digital objects, and a language data metadata profile to ensure long-term interoperability between systems and re-usability over time. We also discuss data licensing and authorization for access to non-open resources. We suggest that the approach shown here may be used in other disciplines or for other kinds of digital library, repository or archival systems.
Publishing Digital Text Editions on the Semantic Web
1Research Centre for the Humanities, Institute for Literary Studies, Hungary; 2Eötvös Loránd University of Budapest, Department for Digital Humanities
In recent years, the phenomenon of the semantic web and linked open data has become a hot topic in digital philology. Although TEI XML (the “lingua franca” of digital philology) is itself a semantic document description language, it does not in itself cross the boundary between a network of documents and a network of data. Previous attempts to link TEI XML to the semantic web have not been successful, and have not contributed to the use of philological data outside the narrow framework of its creation. We have therefore opted for a hybrid solution that can implement both a high level of external connectivity, and the specificity required by the discipline. The architecture is based on the interconnection of services and software such as Wikdata, GitHub and Zenodo, as well as Wikibase and Invenio RDM. It is illustrated through the concrete publishing practice of the DigiPhil project.
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