Linked Data, an opportunity to mitigate complexity in pharmaceutical research and development Bosse Andersson and Kerstin Forsberg AstraZeneca R&D Clinical Information Strategy email@example.com on Twitter, LinkedIn, Slideshare, Blogspot, citulike
Pharmaceutical research and development
Complexity Pathophysiology? Targets? Phenotypes? Biomarkers? Costs? QoL? Outcomes? Association and interpretationof all data needed has become a too complex task for individuals, or even teams to handle. Health care, pharma, academiaShared datasets Different decisions and different types of applications.
Opportunities Improve the research utility of shared datasets organized for associations, prepared for not yet defined use, ready for automation where computers can function alongside us to mitigate the complexity
It’s like sex and teenagers … Everybody is talking about Linked Data and Semantic Web, … … many have tried parts of it, but … few (if non) have done the real thing, and applied a sustainable and long term approach to use Linked Data principles and Semantic Web technologies to improve the research utility of their data.
Linked Data Management Apragmatic and iterative process Three enablers Linked Data principles, including establishing global namespaces of URI:s Semantic web standards, also for provenance data and dataset descriptions Open ontologies, with the required level of precision and consistency Computers to work alongside scientists to automatically Identify entities and assign URI:s Structure data and capture provenance data Mine for causal relationships and inconsistency