Ontop-temporal: A Tool for Ontology-based Query Answering over Temporal Data

Elem Güzel Kalayci, Guohui Xiao, Vladislav Ryzhikov, Tahir Emre Kalayci, and Diego Calvanese

Proc. of the 27th ACM Int. Conf. on Information and Knowledge Management (CIKM 2018). 2018.

We present Ontop-temporal, an extension of the ontology-based data access system Ontop for query answering with temporal data and ontologies. Ontop is a system to answer SPARQL queries over various data stores, using standard R2RML mappings and an OWL 2 QL domain ontology to produce high-level conceptual views over the raw data. The Ontop-temporal extension is designed to handle timestamped log data, by additionally using (i) mappings supporting validity time specification, and (ii) rules based on metric temporal logic to define temporalised concepts. In this demo we present how Ontop-temporal can be used to facilitate the access to the MIMIC-III critical care unit dataset containing log data on hospital admissions, procedures, and diagnoses. We use the ICD9CM diagnoses ontology and temporal rules formalising the selection of patients for clinical trials taken from the clinicaltrials.gov database. We demonstrate how high-level queries can be answered by Ontop-temporal to identify patients eligible for the trials.


@inproceedings{CIKM-demo-2018,
   title = "Ontop-temporal:  A Tool for Ontology-based Query Answering over
Temporal Data",
   year = "2018",
   author = "Güzel Kalayci, Elem and Guohui Xiao and Vladislav
Ryzhikov and Kalayci, Tahir Emre and Diego Calvanese",
   booktitle = "Proc. of the 27th ACM Int. Conf. on Information and
Knowledge Management (CIKM 2018)",
   pages = "1927--1930",
   doi = "10.1145/3269206.3269230",
}
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