Day: 10 November 2015

The upcoming EU Data Protection Regulation: what consequences could it have for research?

As they are now, the EU Parliament’s amendments to the Data Protection Regulation (DPR) prohibit the use of identifiable health data without specific consent and set tough limits on the use of pseudonymised data. Learn what this could mean for research! What is going on? In January 2012, the European Commission proposed a comprehensive reform of data protection rules in the EU. The current rules from 1995 do not cover the areas of globalisation and technological developments like social networks and cloud computing sufficiently. The EU aims to complete the new version of the policy by the end of 2015 meaning that at this very moment representatives from the three EU institutions – the European Parliament, European Commission and the Council of Ministers – are working together to agree on a final text of the draft law. Read here in more detail why the reform of the data protection rules from 1995 is needed. Although the idea to control what is going on with your personal data is good, one can go really far and overprotect things beyond decent levels. For example, What consequences could it have for research? This new regulation as it is now will make the process […]

CODATA report on best practice for research data management policies

Denmark is one of the world leaders in digital health and knows a lot about data and data management. Today we present the report on Current Best Practice for Research Data Management Policies from May 2014 produced by the Danish e-Infrastructure Cooperation and the Danish Digital library. The researchers conducted a survey to identify the key elements of current good practice in research data policies. So, what makes a good policy? According to the study, each good research policy starts with the following considerations: An account of the general drivers and principles: these include the validation of research results, research opportunities for data reuse, the principle of open access by default to the outputs of publicly-funded research, and broader societal and economic benefits. A discussion of the requirements for the effective data sharing: e.g. ‘intelligent openness’ and the need for data to be ‘discoverable, accessible, assessable, intelligible, useable, and whenever possible interoperable to specific quality standards‘. A statement of the necessary limits of openness: these are imposed, in particular, by the need to protect personal information, by the requirement to respect commercial considerations and by security concerns. At the core of each good policy, the following elements are present: A […]

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