The European Open Science Cloud (EOSC) is being developed as a globally accessible, multidisciplinary data infrastructure. The EOSC will federate existing scientific data and digital infrastructures for data exploitation that are now spread across disciplines and EU member states.
The objective of the EOSC is to give the EU a global lead in research data management and ensure that European scientists reap the full benefits of data-driven science by offering a virtual environment with free at the point of use, open and seamless services for storage, management, analysis and re-use of research data across borders and scientific disciplines (EOSC implementation Roadmap, March 2018).
Currently, different European research communities and research infrastructures use varying data management practices and follow heterogeneous access policies. Key to the success of the EOSC is therefore standardisation, collaboration and data provenance.
Against this background the FAIR Data Principles, first coined in 2014 and published in 2016 (Wilkinson, M., Dumontier, M., Aalbersberg, I. et al), guide the design and implementation of the EOSC. The FAIR principles are a set of guiding principles seeking to increase re-usability of data (including data related algorithms, tools, workflows, protocols, services and other kinds of digital research objects). They put specific emphasis on enhancing the ability of machines to automatically find and use data, in addition to supporting its reuse by individuals. FAIR plays an essential role in promoting open science to improve and accelerate scientific research. FAIR stands for Findable, Accessible, Interoperable, and Reusable.
Legal interoperability
Within the context of EOSC and the FAIR principles, legal interoperability requires, in particular, that data should be reusable. It concerns the ability to combine datasets from multiple sources without conflicts among restrictions imposed by the conditions or the license that each dateset carries. For example, assume that Anna wishes to embed two resources X and Y in a new content, Z, that she is working on. Both X and Y carry a Creative Commons (CC) open license but resource X carries an Attribution-NonCommercial license (CC-BY-NC) while resource Y carries a Creative Commons Attribution-ShareAlike license (CC-BY-SA). If Anna assigns a non-commercial open license to Z (for example the CC-BY-SA-NC), she will breach the terms of the license carried by Y. If Anna chooses a license that allows commercial use of Z (for example by using the CC-BY-SA license) she will breach the terms of the license carried by X. In other words, the licenses carried by X and Y separately, cannot be combined and reused in Anna’s derivative work Z.
It also follows that the fewest restrictions contained in the source datasets will result in the fewest restrictions contained in the combined or derivative datasets. This implies that only where the data is free of any restrictions and is in the public domain (for example CC0 or PDDL dedication), legal interoperability will be maximised.
Legal interoperability also concerns situations where regulatory or policy measures restrict the disclosure of data, or that datasets may be made available only in certain jurisdictions or under certain conditions. Examples include legal restrictions based on intellectual property law, national security, the protection of endangered species or privacy regulations, such as GDPR. A number of mechanisms are used in practice to restrict access to data where such regulatory or policy measures exist e.g., embargo, data redaction, data generalisation or simply restricting any access to the data.
The FAIR principles do not necessarily mean that data should always be open and they do not restrict the recognition of legitimate reasons for shielding data. However in cases where access to the data is restricted or subject to conditions, legal interoperability requires that the metadata is FAIR, enabling data provenance and discovery, that the conditions for access and use are clearly and readily determinable through automated means and that they do not conflict with each other.
X-officio is currently preparing a study for the EOSC Secretariat on legal interoperability within the context of the EOSC and the implementation of the FAIR principles. A summary of the recommendations made will be integrated into the EOSC Interoperability Framework report, prepared by the EOSC Secretariat FAIR Working Group.