GDPRtEXT - GDPR as a Linked Data Resource

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

The use of personal data is critical to ensure quality and reliability in scientific research. The new Regulation [European Union (EU)] 2016/679 of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data [general data protection regulation (GDPR)], repealing Directive 95/46/EC, strengthens and harmonises the rules for protecting individuals’ privacy rights and freedoms within and, under certain conditions, outside the EU territory. This new and historic legal milestone both prolongs and updates the EU acquis of the previous Data Protection Directive 95/46/EC. The GDPR fixes both general rules applying to any kind of personal data processing and specific rules applying to the processing of special categories of personal data such as health data taking place in the context of scientific research, this including clinical and translational research areas. This article aims to provide an overview of the new rules to consider where scientific projects include the processing of personal health data, genetic data or biometric data and other kinds of sensitive information whose use is strictly regulated by the GDPR in order to give the main key facts to researchers to adapt their practices and ensure compliance to the EU law to be enforced in May 2018.

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.