Title :
An Ontology-Based Framework for Analysis Recommendation
Author :
Henriques, Gabriela ; Stacey, Deborah
Author_Institution :
Sch. of Comput. Sci., Univ. of Guelph, Guelph, ON, Canada
Abstract :
One of the challenges with data analysis revolves around selecting the best analysis method for a data set that will provide appropriate and meaningful results. This paper presents an ontology-based framework to address challenges around selecting an analysis method that can best represent a data set and the information you want to get out of it. Two ontologies were developed, one to capture semantic and syntactic descriptions on a data source, and likewise one to capture the description of analysis methods. Ontologies were selected for their flexibility in providing a description between a set of concepts and relationships along with their ability to reason between these descriptions.
Keywords :
bioinformatics; data analysis; ontologies (artificial intelligence); analysis method description; analysis method selection challenges; analysis recommendation; data analysis revolves; data set analysis; data set information; data set representtaion; data source semantic description; data source syntactic description; ontology flexibility; ontology selection; ontology-based framework; Algorithm design and analysis; Data analysis; Educational institutions; Ontologies; Semantics; Surveillance; Syntactics; Analysis Recommendation; Data Analysis; Knowledge Engineering; Leveraging Knowledge; Ontology; Syndromic Surveillance;
Conference_Titel :
Bioinformatics and Bioengineering (BIBE), 2014 IEEE International Conference on
Conference_Location :
Boca Raton, FL
DOI :
10.1109/BIBE.2014.70
