Ontological modelling and execution of phenotypic queries in the Leipzig Health Atlas

Abstract:

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

Projects: SMITH - Smart Medical Information Technology for Healthcare

Publication type: InCollection

Book Title: German Medical Data Sciences: Bringing Data to Life

Publisher: IOS Press

Human Diseases: No Human Disease specified

Citation: In German Medical Data Sciences: Bringing Data to Life of Studies in health technology and informatics, IOS Press

Date Published: 1st May 2021

Registered Mode: imported from a bibtex file

Help
help Submitter
Activity

Views: 722

Created: 24th Feb 2023 at 17:05

help Tags

This item has not yet been tagged.

help Attributions

None

Related items

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies