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Answering controlled natural language questions over RDF clinical data

: Karam, Naouel; Streibel, Olga; Karjauv, Aray; Coskun, Goekhan; Paschke, Adrian


Harth, A.:
The Semantic Web. ESWC 2020 Satellite Events. Revised Selected Papers : Heraklion, Crete, Greece, May 31 - June 4, 2020
Cham: Springer Nature, 2020 (Lecture Notes in Computer Science 12124)
ISBN: 978-3-030-62326-5 (Print)
ISBN: 978-3-030-62327-2 (Online)
Extended Semantic Web Conference (ESWC) <17, 2020, Online>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
03WKDA1F; Qurator
Conference Paper
Fraunhofer FOKUS ()
question answering; Controlled Natural Language; clinical study ontology; RDF knowledge base; clinical data

Clinical trial data requires a lot of processing before it can be submitted in accordance with its standardization requirements. After its processing, data has to be stored carefully, often in different systems and formats. Integrating this data without information loss and enabling easy retrieval for later analysis is a highly challenging task. In this demo, we present our system for answering controlled Natural Language questions over RDF clinical data. Questions entered by a user through the proposed interface are annotated on the fly and suggestions are displayed based on an ontology driven auto-completion system. This approach assures a high level of usability and readability while preserving semantic correctness and accuracy of entered questions.