DataSHIELD: taking the analysis to the data, not the data to the analysis

Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis

BBMRI-ERIC Policy for Access to and Sharing of Biological Samples and Data

<p>BBMRI-ERIC1 is a pan-European research infrastructure which facilitates access to human biological samples (e.g., tissue, blood, DNA) and associated clinical and research data from individual biobanks. BBMRI-ERIC is a European infrastructure with the aim to encourage and expedite effective and ethical access to samples and data from biobanks, preferably in the context of high-level research collaboration between providers (e.g., biobanks, including scientists and physicians who contributed to the biobanks) and requesters. As of early 2017, BBMRI-ERIC consists of 19 Member States and one international organisation (IARC). BBMRI-ERIC operates on a non-profit basis. This access policy presents three areas of guidance:<br> i) ethical principles;<br> ii) governance procedures; and<br> iii) practical procedures for access.<br> Together with existing legal frameworks, these three areas provide the ethical and legal framework and practical procedures to guide access to and use of biological samples and associated data, as well as to tools and resources developed by BBMRI-ERIC. This policy is a binding document for BBMRI-ERIC itself, for BBMRI-ERIC Partner Biobanks, and for any requesters, who are seeking access to samples/data from BBMRI-ERIC Partner Biobanks via BBMRI-ERIC. It will not supersede access policies and procedures of individual biobanks but will provide a framework that BBMRI-ERIC Partner Biobanks must adhere to.<br> This policy will be amended/changed in accordance with changes in the regulatory framework.</p

A framework for quality management in the biomedical research infrastructures (BMS RIs)

Thirteen biomedical research infrastructures (BMS RIs) have been prioritised by the European Strategy Forum on Research Infrastructures as ESFRI Projects or ESFRI Landmarks. This working paper describes a core set of eight principles on quality management recognised by all BMS RIs