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Formalizing mappings to optimize automated schema alignment: application to rare diseases.

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Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France.
INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, Villetaneuse, France.


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.

[Indexed for MEDLINE]

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