In the context of the EOSC-Pillar project, Work Package 6 (EOSC in action: Use cases and community-driven pilots) delivers use cases to analyse different tools and services used for the "FAIRification". Among them, Use Case 1 (Defining procedures and services to enforce data provenance for thematic communities and beyond) aims at elaborating cross-domain, FAIR-oriented procedures and recommendations to enforce data provenance in two scientific domains: Materials Science/Nanoscience and Climate Science. Learn more about use case
FAIR-IMPACT has the ambitious goal of realising an EOSC of FAIR data and services by supporting the ...
The IMI FAIRplus project aims to make datasets used or generated in other IMI projects more FAIR (Fi...
Data management is growing in complexity as largescale applications take advantage of the loosely co...
Due to the increasing complexity of data analysis workflows, provenance management is a key componen...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
EOSC-Pillar was a project funded by the European Union's H2020 research and innovation program, runn...
The exchange of research data and physical specimens has become an issue of major importance for mod...
The exchange of research data and physical specimens has become an issue of major importance for mod...
FAIR data and workflow efforts are a response to the increasing volume and complexity of scientific ...
The FAIR principle F4 states that (Meta)data are registered or indexed in a searchable resource. Suc...
Here we elaborate and implement FAIR-oriented procedures and recommendations to enforce data provena...
eScience allows scientific research to be carried out in highly distributed environments. The comple...
As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project...
Data provenance is key to understanding and interpreting the results of scientific experiments. This...
FAIR-IMPACT has the ambitious goal of realising an EOSC of FAIR data and services by supporting the ...
The IMI FAIRplus project aims to make datasets used or generated in other IMI projects more FAIR (Fi...
Data management is growing in complexity as largescale applications take advantage of the loosely co...
Due to the increasing complexity of data analysis workflows, provenance management is a key componen...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
Due to data exploration complexity, provenance management is a key component in order to guarantee s...
EOSC-Pillar was a project funded by the European Union's H2020 research and innovation program, runn...
The exchange of research data and physical specimens has become an issue of major importance for mod...
The exchange of research data and physical specimens has become an issue of major importance for mod...
FAIR data and workflow efforts are a response to the increasing volume and complexity of scientific ...
The FAIR principle F4 states that (Meta)data are registered or indexed in a searchable resource. Suc...
Here we elaborate and implement FAIR-oriented procedures and recommendations to enforce data provena...
eScience allows scientific research to be carried out in highly distributed environments. The comple...
As part of the EOSC project family the FAIRsFAIR - Fostering Fair Data Practices in Europe - project...
Data provenance is key to understanding and interpreting the results of scientific experiments. This...
FAIR-IMPACT has the ambitious goal of realising an EOSC of FAIR data and services by supporting the ...
The IMI FAIRplus project aims to make datasets used or generated in other IMI projects more FAIR (Fi...
Data management is growing in complexity as largescale applications take advantage of the loosely co...