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.

The Leipzig Health Atlas—An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online

“…While the SEEK platform only allows to represent research data as data files, the LHA Data Portal 14,10,31 supports efficient but flexible storing, querying and providing the reserach-and metadata making use of the CDISC ODM (Operational Data Model 9 ) format. It also uses the Study Data Query Language (SDQL), a novel domain specific language we created to specify filter criteria for querying the data 32,33 . The SDQL reuses the conceptual abstract ODM entities to utilize known and well-defined vocabularies to enable an ODM-compliant data retrieval.…”

“…The SDQL reuses the conceptual abstract ODM entities to utilize known and well-defined vocabularies to enable an ODM-compliant data retrieval. Queries supporting the identification and classification of individuals or characteristics that meet specific phenotypic criteria (e.g., 'select men aged 40-60 with myocardial infarction') have been called phenotypic queries 33 . They are used, e.g., for feasibility studies or to define study cohorts.…”

“…They are used, e.g., for feasibility studies or to define study cohorts. To model and represent phenotypes as well as for generating phenotypic queries in SDQL, we developed the Phenotype Manager (PhenoMan), an ontology-based phenotyping framework 34,33 . The PhenoMan imports the phenotype specifications (including generated queries) into the LHA using the extended REST interface of SEEK.…”

“…The queries are integrated as links to the LHA Data Portal and can be executed by clicking the links (magnifier icon). When the user is logged in, the Data Portal returns the corresponding results, i.e., the number of available persons meeting all criteria of the query 33 .…”

“…When the user is logged in, the Data Portal returns the corresponding results, i.e., the number of available persons meeting all criteria of the query. 33 oposSOM-Browser: An Interactive Access to Health-Related Omics Data…”