• DocumentCode
    3196240
  • Title

    Data and metadata models in electrophysiology domain: Separation of data models into semantic hierarchy and its integration into EEGBase

  • Author

    Papez, V. ; Moucek, Roman

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of West Bohemia, Plzen, Czech Republic
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    539
  • Lastpage
    543
  • Abstract
    Increasing requirements on data sharing in the domain of electrophysiology lead to proposing new terminologies and data models. A current trend is to describe data by ontologies and semantic web resources. However, classic technologies and models cannot be replaced in a short time. Due to this, dependencies between various data models should be explicitly described and properties, which the models have in common, should be unified. This work summarizes the current state in data modeling. It describes various ways to model and store data and transformation mechanisms between data models. It deals with well-known concepts (relational and object oriented model) as well as with emerging concepts (ontologies). Finally, the hierarchical metadata model consisting of levels with different expressive power is introduced.
  • Keywords
    bioinformatics; data models; electroencephalography; medical computing; meta data; object-oriented methods; ontologies (artificial intelligence); semantic Web; storage management; EEGBase; data modeling; data sharing; data storage; electrophysiology domain; hierarchical metadata model; object oriented model; ontologies; relational model; semantic Web resources; semantic hierarchy; transformation mechanisms; Brain models; Data models; Erbium; Object oriented modeling; Ontologies; Terminology; Database; Electroencephalography; Electrophysiology; Event-Related Potentials; Neuroinformatics; Object Oriented Model; Ontology; Relational Model; Semantic Web; XML; XSD;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732554
  • Filename
    6732554