PRONOM is an online technical registry providing impartial and definitive information about file formats, software products and other technical components required to support long-term access of electronic records.
Data obtained from the open survey developed by the LEARN project (http://www.learn-rdm.eu/) as a self-assessment tool to assist institutions discover how ready they are for managing research data. This dataset replaces the first one published at http://doi.org/10.5281/zenodo.61903. The survey is based on the issues posed to institutions by the LERU Roadmap for Research Data published at the end of 2013, and available at: http://www.learn-rdm.eu/material/leru_roadmap_for_research_data The survey has thirteen questions addressing the main elements to be taken into account in developing an institutional strategy for research data management. Each question has three possible answers representing green, yellow or red light. The more ‘green light’ responses recorded, the readier an institution probably is for managing its research data. The survey is available in English at http://learn-rdm.eu/en/rdm-readiness-survey/ and in Spanish at http://learn-rdm.eu/encuesta-rdm/
BioSchemas relies and extends from schema.org and aims to reuse existing standards and reach consensus among a wide number of life sciences organizations and communities.
This document describes RML, a generic mapping language, based on and extending [R2RML]. The RDF Mapping language (RML) is a mapping language defined to express customized mapping rules from heterogeneous data structures and serializations to the RDF [RDF-CONCEPTS] data model. RML is defined as a superset of the W3C-standardized mapping language [R2RML], aiming to extend its applicability and broaden its scope, adding support for data in other structured formats. [R2RML] is the W3C standard to express customized mappings from relational databases to RDF. RML follows exactly the same syntax as R2RML; therefore, RML mappings are themselves RDF graphs. The present document describes the RML language and its concepts through definitions and examples.
The Compliance Assessment Toolkit will support the EOSC PID policy with services to encode, record, and query compliance with the policy. To do so, a wide range of compliance requirements ( TRUST, FAIR, PID Policy, Reproducibility, GDPR, Licences) will be evaluated as use cases for definition of a conceptual model. At the same time, vocabularies, concepts, and designs are intended to be re-usable for other compliance needs: TRUST, FAIR, POSI, CARE, Data Commons.