Accountable Human Subject Research Data Processing using Lohpi

Abstract

In human subject research, various data about the studied individuals are collected. Through re-identification and statistical inferences, this data can be exploited for interests other than the ones the subjects initially consented to. Such exploitation must be avoided to maintain trust with the researched population. We argue that keeping data-access policies up-to-date and building accountability on research data processing can reflect subjects' consent and mitigate data misuse. With accountability in mind, we are building Lohpi: a decentralized system for research data sharing with up-to-date access policies. We demonstrate our initial prototype with timely delivery of policy changes along with minimal access control overhead.

Capturing Nutrition Data for Sports: Challenges and Ethical Issues

“…We have built Lohpi [33,34], a distributed system to support dynamic policies. We argue for a decentralized approach, where different institutions can process data on their infrastructures and maintain control of data assets, rather than a central one-fits-all service.…”

Designing a Service for Compliant Sharing of Sensitive Research Data

“…For sensitive data, they only briefly discuss adding encryption and keeping the keys under the control of the gatekeeper. In our earlier work Lohpi [15,16], we argued that the changes occurring during a project's life cycle might affect its data security policies. Thus, we built support for accountability by keeping data security policies up to date securely and efficiently.…”