TECHNOLOGY
Challenges ( and Solutions ) for Big Data Integration Leveraging big data represents an opportunity to advance different fields across the biomedical sciences and healthcare industries including personalized medicine , systems biology , clinical research , drug discovery , drug development and public health .
Five challenges were identified from the participants :
1 . Health-related data are fragmented across multiple and unconnected data sources ( patient registries , bio-banks , social networks , and others ).
2 . There is no clear code of practice for data sharing . Data are stored in databases that belong to multiple institutions and stakeholders across the biomedical research and healthcare fields .
3 . The prevailing biomedical R & D model is segmented into basic , preclinical and clinical research silos . This ‘ compartmentalization ’ of the biomedical R & D and healthcare data chain , with value expected for the citizen / patient as a passive end-user , is a major hurdle to a data-sharing culture .
4 . There is as yet no clear code of practice to ensure personal privacy while preserving openness in data sharing .
5 . Current funding and career appraisal systems for biomedical researchers mainly recognize investigator-driven research . Mechanisms recognizing collaborative inter-disciplinary networks are in their infancy .
But recommendations to these challenges were offered .
Legal : Introduce appropriate legal and ethical frameworks to support data-sharing while developing appropriate security and oversight measures to reduce the risk of personal data loss ( for example the European Data Protection Regulation ). Big data presents other challenges with respect to ownership and liability that will need to be resolved .
Society : Increase citizen and patient involvement in the management and processing of their own health data and restore public trust in science ( such as health data co-operatives ). Organization : Develop codes of conduct and research practices
18 May 2015