## 3 Results
### Applications of the Phenotypic Query Approach
#### 3.1.2 Use of Study Data Query Language in the Leipzig Health Atlas  
It is important to not only model phenotypes in PheSOs but also represent them in a user-friendly way (e.g., on websites) and make them browsable by experts from different disciplines (e.g., epidemiologists or physicians). This increases the visibility and reusability of these phenotypes (according to FAIR data principles). The phenotype class representations can be used to run simple phenotypic queries directly on research data management systems (RDMSs) with anonymised patient data. This would allow experts to retrieve case numbers to obtain an overview of the available research data without having to build complex queries in the RDMS native language. A first prototypic approach [47] of the above-described connection between phenotype class representations and an RDMS was implemented in the Leipzig Health Atlas project [48]. One outcome of the project is a repository (also called the Leipzig Health Atlas (LHA)) for storing heterogeneous scientific projects, associated publications, results (e.g., (bio)medical and clinical data sets, models, and tools), and their metadata [49]. The LHA follows the FAIR data principles and was built on the SEEK management platform [50], which provides the basis for a repository with archiving, presentation, and secure sharing \begin{table}
\begin{tabular}{l c} \hline
**Criteria from Section 2.4** & **Resulting FHIR Search Queries** \\ \hline
**Inclusions:** & GET [base]/Patient?gender=male \\ (ic1) male subjects & \&birthdate=gt1956-05-13\&birthdate=le1982-05-13 \\ (ic2) age between 40 and 65 years & \&birthdate=gt1956-05-13\&birthdate=le1982-05-13 \\ (i.e., age in years \(\geq\) 40 and \textless{}66) & \\ (ic3a) BMI \(\geq\) 30 kg/m\({}^{2}\) & GET [base]/Observation?code=[[http://loinc.org](http://loinc.org)]([http://loinc.org](http://loinc.org)) \(|\) 3137-7 \\ (requires height and weight) & GET [base]/Observation?code=[[http://loinc.org](http://loinc.org)]([http://loinc.org](http://loinc.org)) \(|\) 3141-9 \\ (ic3b) at least one observation of & GET [base]/Observation \\ systolic blood pressure &?component-code-value-quantity=[[http://loinc.org](http://loinc.org)]([http://loinc.org](http://loinc.org)) \(|\) 8480-6 \\ \(\geq\)130 mmHg & \&ge130\(|\) [[http://unitsofmeasure.org](http://unitsofmeasure.org)]([http://unitsofmeasure.org](http://unitsofmeasure.org)) \(|\) mmHg] \\ in the last month & \&date=ge2022-04-13T09:00:00 \\ \hline
**Exclusions:** & GET [base]/Condition \\ (ec1) myocardial infarction &?code=[[http://snomed.info/sct](http://snomed.info/sct)]([http://snomed.info/sct](http://snomed.info/sct)) \(|\) 22298006, \\ (ec2) stroke & [[http://snomed.info/sct](http://snomed.info/sct)]([http://snomed.info/sct](http://snomed.info/sct)) \(|\) 230690007 \\ \hline \end{tabular}
\end{table} 
Table 1: Example FHIR Search queries for the inclusion and exclusion criteria listed in Section 2.4. The query execution timestamp is assumed to be 13 May 2022 09:00:00. Here, “[base]” is a placeholder for an FHIR server uniform resource location (URL). capabilities. We have extended SEEK with methods to represent the phenotype classes of uploaded PheSOs. Another component of the LHA is the LHA Data Portal for managing study data and metadata and for querying data by user-specified filter criteria. The data portal is based on the LIFE Data Portal [51] (closed source, developed in the LIFE Study, Leipzig, Germany), and it uses the vendor-neutral and platform-independent CDISC ODM format for exchanging and archiving clinical and translational study data [52] to enable efficient and flexible storage and provision of study data in a standardised manner. Each query created with the data portal web client is internally translated into the custom domain-specific language Study Data Query Language (SDQL) [53]. SDQL reuses the conceptual abstract CDISC ODM entities to utilise known and well-defined terminologies.