The ability to perform automated conversions between data conforming to different specifications is a key ingredient to achieve interoperability among heterogeneous systems-which, in turn, is at the basis of the creation of so-called Systems of Systems. These conversions require the definition of mappings between concepts of separate data specifications, which is typically a hard and time-consuming task. In this paper, we present a technique to automatically suggest mappings to users, based on both linguistic and structural similarities between terms. The approach has been implemented in our prototype tool, SMART (SPRINT Mapping & Annotation Recommendation Tool), and it has been validated through tests carried out using specifications from the transportation domain.

SMART: Towards automated mapping between data specifications

Kalwar S.;Sadeghi M.;Nemirovskiy A.;Rossi M.
2021-01-01

Abstract

The ability to perform automated conversions between data conforming to different specifications is a key ingredient to achieve interoperability among heterogeneous systems-which, in turn, is at the basis of the creation of so-called Systems of Systems. These conversions require the definition of mappings between concepts of separate data specifications, which is typically a hard and time-consuming task. In this paper, we present a technique to automatically suggest mappings to users, based on both linguistic and structural similarities between terms. The approach has been implemented in our prototype tool, SMART (SPRINT Mapping & Annotation Recommendation Tool), and it has been validated through tests carried out using specifications from the transportation domain.
2021
Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
1-891706-52-7
Automated mapping
Linguistic similarity
Natural language processing
Ontology
Structural similarity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1186112
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