Formalizing Mappings to Optimize Automated Schema Alignment: Application to Rare Diseases.

In the era of data sharing and systems interoperability, the automation of data schema alignment has become a priority. Discovering data mappings is the aim of many alignment approaches that have been described in the literature and the effectiveness of which depends on data specifications. In this...

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Publicado en:Studies in Health Technology & Informatics Vol. 205; pp. 283 - 288
Autores principales: MAAROUFI, Meriem, CHOQUET, Rémy, LANDAIS, Paul, JAULENT, Marie-Christine
Formato: research tables/charts Journal Article
Publicado: Sage Publications Inc. 2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2014
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        atl: Formalizing Mappings to Optimize Automated Schema Alignment: Application to Rare Diseases.
      aug:
        au:
          MAAROUFI, Meriem
          CHOQUET, Rémy
          LANDAIS, Paul
          JAULENT, Marie-Christine
        affil: Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France
      sug:
        subj:
          Rare Diseases
          Maps
          Elements
          Arterial Pressure
          Literature
      ab: In the era of data sharing and systems interoperability, the automation of data schema alignment has become a priority. Discovering data mappings is the aim of many alignment approaches that have been described in the literature and the effectiveness of which depends on data specifications. In this context, we propose a method for mappings formalization that allows automated data integration processes optimization. This method, involving both data element level and value element level, allows an automated inference of mappings expressed by rules. In this paper, we start by describing the methods used to achieve this mappings formalization. Then, we explain how it has been validated by characterizing data from two use cases. We end up by discussing the objectives of the proposed formalization.
      pubtype: Academic Journal
      doctype:
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        tables/charts
        Journal Article
      ougenre: Article
    language: English
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