This is an old revision of the document!
Table of Contents
Basic Goals and Principles - Recommendation 0
Base Recommendation to develop and activate a FAIR Dataspace for the Helmholtz Association
Description
[Status: Under development, Date: 2023-08-25, Version: 001]
Motivation for this Recommendation:
The Helmholtz Association is determined to make their data available according to the FAIR principles, thus making it findable, accessible, interoperable and reusable. In order to achieve interoperability of datasets among various data infrastructures (DIS) within the Helmholtz Association,
- - a common and agreed procedure to refer to common information is needed.
- - common semantic concepts need to be implemented
- - common data exchange containers and formats need to be defined and implemented
- - common interfaces and data exchange protocols need to be agreed upon
These following recommendations aim to describe procedures to achieve the above-mentioned goals, and identify activities and relevant stakeholder groups to implement these.
As these goals require certain decisions to be made, we describe the decision processes from high-level to lower levels, resulting in agreed procedures. We then describe the conduct of these procedures with respect to the involved stakeholder groups, their responsibilities and actions needed to be taken.
FAIR building blocks
- common use of semantic resources (S) e.g. vocabularies, ontologies.
- common use of PID to harmonize common metadata (M)
- common standards in interfaces to harvest and exchange data (I)
- use of data containers, e.g. FDOs or data crates, to achieve machine actionability (C)
Other important topics
- well defined licenses (L)
- quality assessment and control (Q)
- provenance tracking (P)
- stakeholder roles and responsibilities (R)
- published data is treated similar to other publications including DOIs and author references, citable, with licenses and credits to the authors. This includes accountability for publishing credit systems and others. Data citations improve the data set author’s score.