Characterizing Semantic Mappings Adaptation via Biomedical KOS Evolution: A Case study Investigating SNOMED CT and ICD

Abstract : Mappings established between Knowledge Organization Systems (KOS) increase semantic interoperability between biomedical information systems. However, biomedical knowledge is highly dynamic and changes affecting KOS entities can potentially invalidate part or the totality of existing mappings. Understanding how mappings evolve and what the impacts of KOS evolution on mappings are is therefore crucial for the definition of an automatic approach to maintain mappings valid and up-to-date over time. In this article, we study variations of a specific KOS complex change (split) for two biomedical KOS (SNOMED CT and ICD-9-CM) through a rigorous method of investigation for identifying and refining complex changes, and for selecting representative cases. We empirically analyze and explain their influence on the evolution of associated mappings. Results point out the importance of considering various dimensions of the information described in KOS, like the semantic structure of concepts, the set of relevant information used to define the mappings and the change operations interfering with this set of information.
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Communication dans un congrès
AMIA 2013 Annual Symposium, Nov 2013, Washington DC, United States. 2013
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https://hal.inria.fr/hal-00945883
Contributeur : Chantal Reynaud <>
Soumis le : jeudi 13 février 2014 - 10:59:14
Dernière modification le : mardi 24 avril 2018 - 13:39:17

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  • HAL Id : hal-00945883, version 1

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Julio Cesar Dos Reis, Cédric Pruski, Marcos Da Silveira, Chantal Reynaud-Delaître. Characterizing Semantic Mappings Adaptation via Biomedical KOS Evolution: A Case study Investigating SNOMED CT and ICD. AMIA 2013 Annual Symposium, Nov 2013, Washington DC, United States. 2013. 〈hal-00945883〉

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