Time-related patient data retrieval for the case studies from the pharmacogenomics research network.
There are lots of question-based data elements from the pharmacogenomics research network (PGRN) studies. Many data elements contain temporal information. To semantically represent these elements so that they can be machine processiable is a challenging problem for the following reasons: (1) the designers of these studies usually do not have the knowledge of any computer modeling and query languages, so that the original data elements usually are represented in spreadsheets in human languages; and (2) the time aspects in these data elements can be too complex to be represented faithfully in a machine-understandable way. In this paper, we introduce our efforts on representing these data elements using semantic web technologies. We have developed an ontology, CNTRO, for representing clinical events and their temporal relations in the web ontology language (OWL). Here we use CNTRO to represent the time aspects in the data elements. We have evaluated 720 time-related data elements from PGRN studies. We adapted and extended the knowledge representation requirements for EliXR-TIME to categorize our data elements. A CNTRO-based SPARQL query builder has been developed to customize users' own SPARQL queries for each knowledge representation requirement. The SPARQL query builder has been evaluated with a simulated EHR triple store to ensure its functionalities.
Mayo Clinic, Rochester, MN, USA.
Qian
Q
Zhu
Cui
C
Tao
Ying
Y
Ding
Christopher G
CG
Chute
D001185:Artificial Intelligence; D035843:Biomedical Research / Q000458:organization & administration*; D003627:Data Interpretation, Statistical; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D010597:Pharmacogenetics / Q000458:organization & administration / Q000706:statistics & numerical data*; D012107:Research Design; D012985:Software Design; D013997:Time Factors