Neurodegenerative Disease Data Ontology

Ana Kostovska, Ilin Tolovski, Fatima S. Maikore, Larisa N. Soldatova, Pance Panov

Abstract: In this paper, we report on the ontology for the representation of brain diseases data - NDDO. The proposed ontology facilitates semantic annotation of datasets containing neurodegenerative diagnostic data (i.e. clinical, imaging, biomarker, etc.) and disease progression data collected on patients by the hospitals. Rich semantic annotation of datasets is essential for efficient support of data mining, for example for the identification of suitable algorithms for data analytics, text mining, and reasoning over distributed data and knowledge sources. To address the data analytics perspective, we reused and extended our previous work on ontology of data types (OntoDT) and ontology of core data mining entities (OntoDM-core) to represent specific domain datatypes that occur in the domain datasets. We demonstrate the utility of NDDO on two use cases: semantic annotation of datasets, and incorporating information about clinical procedures used to produce neurodegenerative data.