The FAIR-IMPACT Implementation stories illustrate good practices in research communities and organisations to support the implementation of the FAIR principles.
Implementation Story
One of the main concerns when we deploy a service, especially those related to data, is how this service can work with others. This is relevant for services to be integrated in the EOSC ecosystem. The creation of the EOSC Interoperability Framework is an effort to analyse the gaps and problems addressed in this context. Also, it provides recommendations to improve this integration. This FAIR Implementation Story outlines the specific aims, actions and experiences of the Digital Repository of Ireland in relation to their participation in this support action.
Implementation Story
One of the main concerns when we deploy a service, especially those related to data, is how this service can work with others. This is relevant for services to be integrated in the EOSC ecosystem. The creation of the EOSC Interoperability Framework is an effort to analyse the gaps and problems addressed in this context. Also, it provides recommendations to improve this integration. This FAIR Implementation Story outlines the specific aims, actions and experiences of the Austrian NeuroCloud in relation to their participation in this support action.
Implementation Story
One of the main concerns when we deploy a service, especially those related to data, is how this service can work with others. This is relevant for services to be integrated in the EOSC ecosystem. The creation of the EOSC Interoperability Framework is an effort to analyse the gaps and problems addressed in this context. In this support action, selected participants analysed the interoperability status of their services using the FAIRCORE4EOSC Compliance Assessment Tool (CAT).
Implementation Story
The support action introduced successful applicants to three tools developed by the FAIRCORE4EOSC (FC4E) project. These include the Data Type Registry (DTR), vocabulary service, and Metadata Schema andCrosswalk Registry (MSCR). This FAIR Implementation Story outlines the specific aims, actions and experiences of Charles University, Herbarium PRC in relation to their participation in this support action.
Implementation Story
The support action introduced successful applicants to three tools developed by the FAIRCORE4EOSC (FC4E) project. These include the Data Type Registry (DTR), vocabulary service, and Metadata Schema and Crosswalk Registry (MSCR).
Implementation Story
The support action introduced successful applicants to three tools developed by the FAIRCORE4EOSC (FC4E) project. These include the Data Type Registry (DTR), vocabulary service, and Metadata Schema and Crosswalk Registry (MSCR).
Implementation Story
The support action introduced successful applicants to three tools developed by the FAIRCORE4EOSC (FC4E) project. These include the Data Type Registry (DTR)2, vocabulary service, and Metadata Schema and Crosswalk Registry (MSCR).
Implementation Story
This FAIR Implementation Story outlines the specific aims, actions and experiences of Kyiv Academic University in relation to participation in the support action.
Implementation Story
The support action introduced successful applicants to three tools developed by the FAIRCORE4EOSC (FC4E) project. These include the Data Type Registry (DTR), vocabulary service, and Metadata Schema and
Crosswalk Registry (MSCR).
Implementation Story
The persistent identification of research outputs is part of good research data management practice and is central to the FAIR Principles and the vision of the European Open Science Cloud (EOSC). There are many types of persistent identifiers (PIDs) currently being used to identify data and other kinds of research outputs but also different actors involved in the creation of outputs and the organisations that employ them or fund their work.
Implementation Story
The persistent identification of research outputs is part of good research data management practice and is central to the FAIR Principles and the vision of the European Open Science Cloud (EOSC). There are many types of persistent identifiers (PIDs) currently being used to identify data and other kinds of research outputs but also different actors involved in the creation of outputs and the organisations that employ them or fund their work.
Implementation Story
The persistent identification of research outputs is part of good research data management
practice and is central to the FAIR Principles and the vision of the European Open Science Cloud
(EOSC). There are many types of persistent identifiers (PIDs) currently being used to identify
data and other kinds of research outputs but also different actors involved in the creation of
outputs and the organisations that employ them or fund their work. To foster harmonisation on
the use of different persistent identifiers, there is a need to define and implement research data
and/or PID policies. FAIR-IMPACT’s Creating EOSC compliant Persistent Identifier (PID) policies
support action.