Ontop-temporal: A Tool for Ontology-based Query Answering over Temporal Data
Güzel Kalayci E
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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.
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Güzel Kalayci E; Brandt S; Calvanese D; Ryzhikov V; Xiao G; Zakharyaschev M (2019)Predictive analysis gradually gains importance in industry. For instance, service engineers at Siemens diagnostic centres unveil hidden knowledge in huge amounts of historical sensor data and use this knowledge to improve ...
Brandt S; Güzel Kalaycı E; Kontchakov R; Ryzhikov V; Xiao G; Zakharyaschev M (AAAI Press, 2017)We advocate datalogMTL, a datalog extension of a Horn fragment of the metric temporal logic MTL, as a language for ontology-based access to temporal log data. We show that datalogMTL is EXPSPACE-complete even with punctual ...
Calvanese D; Guzel Kalaycı E; Ryzhikov V; Xiao G; Zakharyaschev M (IJCAI Workshop 40, 2016)We present a new metric temporal logic HornMTL over dense time and its datalog extension datalogMTL. The use of datalogMTL is demonstrated in the context of ontology-based data access over meteorological data. We show ...