DS-PACK: Tool assembly for the end-to-end support of controlled access human data sharing.

The EU General Data Protection Regulation (GDPR) requirements have prompted a shift from centralised controlled access genome-phenome archives to federated models for sharing sensitive human data. In a data-sharing federation, a central node facilitates data discovery; meanwhile, distributed nodes are responsible for handling data access requests, concluding agreements with data users and providing secure access to the data. Research institutions that want to become part of such federations often lack the resources to set up the required controlled access processes.

Smart Scheduling (SMASCH): multi-appointment scheduling system for longitudinal clinical research studies.

Objective: Facilitate the multi-appointment scheduling problems (MASPs) characteristic of longitudinal clinical research studies. Additional goals include: reducing management time, optimizing clinical resources, and securing personally identifiable information.

Materials And Methods: Following a model view controller architecture, we developed a web-based tool written in Python 3.

DAISY: A Data Information System for accountability under the General Data Protection Regulation.

Background: The new European legislation on data protection, namely, the General Data Protection Regulation (GDPR), has introduced comprehensive requirements for the documentation about the processing of personal data as well as informing the data subjects of its use. GDPR's accountability principle requires institutions, projects, and data hubs to document their data processings and demonstrate compliance with the GDPR. In response to this requirement, we see the emergence of commercial data-mapping tools, and institutions creating GDPR data register with such tools.