Title: PErsoNal Genome QUery IN healthcare and clinical practice (PENGQUIN)

Abstract:

Medical care is in the process of becoming increasingly per-

sonalized through the use of patient genetic information. At present,

data useful for clinical care, including genetic data, is commonly dif-

fuse, organized arbitrarily, and stored in data silos. Thus, unstructured

organization, high costs for data storage and generation, and tight pri-

vacy restrictions pose serious challenges to scaling personalized clinical

strategies. I propose an early stage Ph.D. that aims to improve the con-

nectedness and shareability of genomic data storage(s), while preserving

data privacy, to decrease the costs of using patient genome data in clini-

cal 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.

** Included a peer-reviewed write-up, a 15-minute presentation, and a poster presentation. **

Title: Genome Pods for Clinical Practice

Abstract: In this talk, we will have a closer look at the storage, querying and sharing of personal genome data with Solid pods. We will investigate the opportunities and challenges presented by Solid decentralized storage of genomic data, specifically the size, semantic representation potential, and privacy controls that would allow for sharing potential. The talk will also include a short demo showing early Solid pod storage and user viewing of genomic data files via a web application interface.

Title: Personalized Medicine through personal data pods.

Abstract: Medical care is in the process of becoming increasingly personalized through the use of patient genetic

information. Concurrently, privacy concerns regarding collection and storage of sensitive personal

genome sequence data have necessitated public debate and legal regulation. Here we identify two

fundamental challenges associated with privacy and shareability of genomic data storage and propose

the use of Solid pods to address these challenges. We establish that personal data pods using Solid

specifications can enable decentralized storage, increased patient control over their data, and support of

Linked Data formats, which when combined, could offer solutions to challenges currently restricting

personalized medicine in practice.