Open sjDCC opened 6 years ago
DFG position: There is full agreement with this recommendation, which is part of the necessary full support of scientific communities to enable them finding their way of the most appropriate and useful means to ensure research data reuse.
Science Europe has developed a Framework for ‘Disciplinary Research Data Management Protocols’, also called Domain Data Protocols (DDPs), as a pragmatic solution to ensure proper implementation of individual DMPs. This approach has been chosen to accommodate the fact that needs can vary largely between different disciplines. Based on this general Framework, scientific communities are encouraged and enabled to set up protocols according to their specific needs and building on their expertise. The Framework document was published in January 2018 to support research communities to develop community standards for RDM.
EIROforum has published its input for the consultation which is available online (20180724-EIROforum-position-paper-EOSC.pdf). The paper highlights a number of practical points EIROforum members consider essential to ensure the EOSC can effectively interlink People, Data, Services and Training, Publications, Projects and Organisations, including aspects related to Rec. #7 “Disciplinary interoperability frameworks”.
As a port of tools and data infrastructure, I would like to remark the importance of computing resources to support the community data lifecycle, not only in storage capacity but also in processing for supporting analysis in a "FAIR" way and data curation to ensure the data quality.
We (the RCN) are not sure if the responsibility is placed correctly here. This cannot be top down, but must come from the research communities. Research funders can fund the infrastructure, but the disciplines together with repositories and RIs must find frameworks that work for their disciplines.
INAF (astronomy) position: Astronomy has already a disciplinary interoperable framework, funding is exactly what's lacking to keep it properly in shape.
FAIR principle I2 states “(meta)data use vocabularies that follow FAIR principles”. The status of disciplinary vocabularies of all kinds of “knowledge organisation systems” (KOS: vocabularies, classifications, ontologies, thesauri, and other semantic systems) is unclear. Moreover, the longevity/maintenance of such KOSs is not guaranteed. Registries and repositories of such KOSs are to be stimulated.
There should be flexibility for research communities to interpret the FAIR principles within their discipline or sector and further develop their own principles and practices. Data stewards will play an important role in the implementation and support of FAIR Data and interoperability frameworks and should thus be adequately trained and employed in adequate numbers for this to occur. An interesting question is to what extent disciplinary or sectoral data should be interoperable across disciplines and sectors given the increasing demand for interdisciplinary and intersectoral collaboration?
On item 3 of this recommendation publishers are also stakeholders. At Elsevier the queries from editors and researchers in the community come, via journal publishers, to the Research Data Management team asking about developments in best practices or recommended practices in their fields of research. This tends to particularly relevant for researchers/institutions who are starting to address research data management as part of their research cycles (in contrast with institutions where best practices are already well established).
Research communities must be supported to develop and maintain their disciplinary interoperability frameworks. These incorporate principles and practices for data management and sharing, community agreements, data formats, metadata standards, tools and data infrastructure.
Enabling mechanisms must be funded and implemented to support research communities to develop and maintain their disciplinary interoperability frameworks. Stakeholders: Funders; Standards bodies; Data services; Global coordination fora.
Disciplines and interdisciplinary research programmes should be encouraged to engage with international collaboration mechanisms to develop interoperability frameworks. Stakeholders: Funders; Policymakers; Institutions; Data stewards; Global coordination fora.
Mechanisms that promote the exchange of good practices and lessons learned within and across disciplines should be facilitated. Stakeholders: Data services; Research communities; Global coordination fora.