• DocumentCode
    260340
  • 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
  • fYear
    2014
  • fDate
    10-12 Nov. 2014
  • Firstpage
    277
  • Lastpage
    282
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Bioengineering (BIBE), 2014 IEEE International Conference on
  • Conference_Location
    Boca Raton, FL
  • Type

    conf

  • DOI
    10.1109/BIBE.2014.70
  • Filename
    7033593