Visions and Challenges in Managing and Preserving Data to Measure Quality of Life

TL;DR

This paper discusses the challenges in managing health-related data for quality of life assessment, emphasizing privacy, data sharing, and proposing a self-regulated open health archive system.

Contribution

It introduces a novel design for a self-regulated Open Health Archive system focused on quality of life data, addressing privacy and data sharing issues.

Findings

Highlights human data bleeding problem and privacy concerns.

Proposes a decentralized, self-regulated data management system.

Encourages open data sharing without complex access protocols.

Abstract

Health-related data analysis plays an important role in self-knowledge, disease prevention, diagnosis, and quality of life assessment. With the advent of data-driven solutions, a myriad of apps and Internet of Things (IoT) devices (wearables, home-medical sensors, etc) facilitates data collection and provide cloud storage with a central administration. More recently, blockchain and other distributed ledgers became available as alternative storage options based on decentralised organisation systems. We bring attention to the human data bleeding problem and argue that neither centralised nor decentralised system organisations are a magic bullet for data-driven innovation if individual, community and societal values are ignored. The motivation for this position paper is to elaborate on strategies to protect privacy as well as to encourage data sharing and support open data without requiring a complex access protocol for researchers. Our main contribution is to outline the design of a self-regulated Open Health Archive (OHA) system with focus on quality of life (QoL) data.