About the Project
The promise of Big Data in Health Care is to scale-up research from the current blizzard of small papers coming from researchers rushing to publish from small databases, to more accurate research outcomes, from more brains, working with more data, across a variety of populations and settings, and working collaboratively around important research questions. The Health e-Research Centre as part of the Farr Institute is leading innovation in the linking of data and methodology.
In order to achieve this vision there is a required shift in what is published, and how it is published, moving away from the traditional, stale method of scholarly communication, to a more integrated, data and metadata-led approach.The recent introduction of data focused publications from the world leading journals Science and Nature indeed demonstrates that the future of scholarly publishing has moved beyond the traditional journal article. Instead, Research Objects (ROs) (www.researchobject.org) that gather together digital artefacts such as code, data and scientific workflows in a machine-readable mechanism, are becoming first class citizens in scholarly communication. Unlike conventional papers, ROs share the research process, and not just the results.
In support of a move towards research objects, the US National Institute of Health (NIH) has recently dedicated $32 million in funding (http://www.nih.gov/news/health/oct2014/od-09.htm) toward the development of a “data commons” – a shared resource for biomedical research, where researchers can publish and discover research objects. A proposed Farr Commons (www.farrcommons.org) will similarly act as a shared resource for Health Research within the Farr Institute, providing a “data catalogue” to enable researchers to publish and integrate their research data as Research Objects. There are however significant outstanding technical challenges in making these Research Objects - and the research described within - findable, accessible, interoperable and reusable, as part of a commons, by both human and machine investigators.This PhD aims to lead the research and development of the research object approach, and its application to the realisation of a "data commons” for health data within the Farr Institute, with the potential to have a significant impact the landscape of scholarly publication.
Student Background Required: This project will be suitable for a highly motivated individual with a first class (or equivalent) undergraduate degree in computer science, with excellent experience in programming. Completed (or soon to be completed) master studies in a related area (including health informatics, knowledge representation) would be an advantage. A knowledge or interest to learn about Web and Semantic Web technologies such as Linked Data, JSON-LD, as well as Ontologies and Structured Vocabularies such as the Open Annotation Model and the W3C PROV Provenance Model.
Full application details and further information on HeRC PhD training opportunities can be found here:
http://www.findaphd.com/search/PhDDetails.aspx?CAID=2588
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