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Clinical Narrative Temporal Relation Ontology (CNTRO)

The rapid increase in the volume of electronic medical records (EMR) available for research purposes provides new opportunities to create semantically interoperable healthcare applications and solutions for individualized and evidence-based medicine. An important aspect of EMR is the temporal ordering of clinical events. Time is essential in clinical research. Exposing the temporal dimension in medical data analysis provides new research paths such as (1) uncovering temporal patterns at the disease and patient level to better understand the progression of a disease, (2) explaining past events such as the possible causes of a clinical situation, and (3) predicting future events such as possible complexities based on a patient's current status.

Discovery, analysis and dissemination of temporal oriented information, however, requires a robust and semantically crisp model of the temporal dimension of clinical data. The Semantic Web and the Web Ontology Language (OWL) provide a suitable environment for modeling the temporal dimension of the clinical data and reasoning about them. The use of OWL to represent temporal assertions brings many benefits. First, the Semantic Web and OWL provide a standard mechanism with explicit and formal semantic knowledge representation. Secondly, the Semantic Web offers automated reasoning capabilities. OWL is built on formalisms that adhere to Description Logic (DL) formalism and therefore allows reasoning and inference. In addition, the Semantic Web Rule Language (SWRL) can be used to add rules to OWL and enable Horn-like rules that can be used to infer new knowledge from an OWL based ontology and reason about OWL individuals. Thirdly, once we have an ontology that can represent temporal assertions in the clinical domain precisely, we can annotate temporal expressions and relations with respect to the ontology and store the instances as RDF triples. The information then become "machine-understandable". Tools and services such as reasoners, editors, querying systems, and storage mechanisms that have been developed by the Semantic Web community can be directly applied to the temporal data.

While the Semantic Web and the Web Ontology Language (OWL) provide a suitable foundation, it is still necessary to arrive at a shared set of semantics and operational rules. CNTRO builds on previous threads along this line and attempts to harmonize them into a unified model - an OWL based ontology of temporal relations for the purpose of clinical research. The purpose of this ontology is to allow temporal information of clinical data can be semantically annotated and queried and to use inference to expose new temporal features and relations based on the semantic assertions and definitions of the temporal aspects in the ontology.