Preferences regarding Disclosure of Risk for Parkinson's Disease in a Population-based Study.

Background: Preferences for risk disclosure in population-based studies assessing Parkinson's disease (PD) risk have not been assessed so far.

Objectives: To examine preferences for risk disclosure in a subset of the European Healthy Brain Aging (HeBA) multicenter study.

Methods: After a remote PD risk assessment, a structured pilot-questionnaire on risk disclosure was first presented to participants (≥50 years, without neurodegenerative diseases) during in-person visits at the Innsbruck study site.

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.

Presenting and sharing clinical data using the eTRIKS Standards Master Tree for tranSMART.

Motivation: Standardization and semantic alignment have been considered one of the major challenges for data integration in clinical research. The inclusion of the CDISC SDTM clinical data standard into the tranSMART i2b2 via a guiding master ontology tree positively impacts and supports the efficacy of data sharing, visualization and exploration across datasets.

Results: We present here a schema for the organization of SDTM variables into the tranSMART i2b2 tree along with a script and test dataset to exemplify the mapping strategy.

SmartR: an open-source platform for interactive visual analytics for translational research data.

Summary: In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies.