PErsoNal Genome QUery IN Healthcare and Clinical Practice (PENGQUIN)

Abstract

Medical care is in the process of becoming increasingly personalized through the use of patient genetic information. At present, data useful for clinical care, including genetic data, is commonly diffuse, organized arbitrarily, and stored in data silos. Thus, unstructured organization, high costs for data storage and generation, and tight privacy restrictions pose serious challenges to scaling personalized clinical strategies. I propose an early stage Ph.D. that aims to improve the connectedness and shareability of genomic data storage(s), while preserving data privacy, to decrease the costs of using patient genome data in clinical practice. In this pursuit, I will integrate various domains of semantic web research into a novel, holistic framework designed for use in clinical practice. Specifically, I will (a) store patient data using Solid pods, (b) represent personal genome sequence data in RDF as Linked Data, (c) attach policies to stored data, and (d) query data through link traversal queries.