A practical alignment service should be flexible enough to handle the varied alignment scenarios that arise in the real world, while minimizing the need for manual configuration. MAPLE, an orchestration framework for ontology alignment, supports this goal by coordinating a few loosely coupled actors, which communicate and cooperate to solve a matching task using explicit metadata about the input ontologies, other available resources and the task itself. The alignment task is thus summarized by a report listing its characteristics and suggesting alignment strategies. The schema of the report is based on several metadata vocabularies, among which the Lime module of the OntoLex-Lemon model is particularly important, summarizing the lexical content of the input ontologies and describing external language resources that may be exploited for performing the alignment. In this paper, we propose a REST API that enables the participation of downstream alignment services in the process orchestrated by MAPLE, helping them self-adapt in order to handle heterogeneous alignment tasks and scenarios. The realization of this alignment orchestration effort has been performed through two main phases: we first described its API as an OpenAPI specification (a la API-first), which we then exploited to generate server stubs and compliant client libraries. Finally, we switched our focus to the integration of existing alignment systems, with one fully integrated system and an additional one being worked on, in the effort to propose the API as a valuable addendum to any system being developed.

Fiorelli, M., Stellato, A. (2020). A Lime-Flavored REST API for Alignment Services. In Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020), Marseille, France (pp. 52-60). European Language Resources Association.

A Lime-Flavored REST API for Alignment Services

Manuel Fiorelli;Armando Stellato
2020-05-01

Abstract

A practical alignment service should be flexible enough to handle the varied alignment scenarios that arise in the real world, while minimizing the need for manual configuration. MAPLE, an orchestration framework for ontology alignment, supports this goal by coordinating a few loosely coupled actors, which communicate and cooperate to solve a matching task using explicit metadata about the input ontologies, other available resources and the task itself. The alignment task is thus summarized by a report listing its characteristics and suggesting alignment strategies. The schema of the report is based on several metadata vocabularies, among which the Lime module of the OntoLex-Lemon model is particularly important, summarizing the lexical content of the input ontologies and describing external language resources that may be exploited for performing the alignment. In this paper, we propose a REST API that enables the participation of downstream alignment services in the process orchestrated by MAPLE, helping them self-adapt in order to handle heterogeneous alignment tasks and scenarios. The realization of this alignment orchestration effort has been performed through two main phases: we first described its API as an OpenAPI specification (a la API-first), which we then exploited to generate server stubs and compliant client libraries. Finally, we switched our focus to the integration of existing alignment systems, with one fully integrated system and an additional one being worked on, in the effort to propose the API as a valuable addendum to any system being developed.
mag-2020
Settore INF/01 - INFORMATICA
Settore ING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI
English
Rilevanza internazionale
Articolo scientifico in atti di convegno
Lime; OntoLex; VocBench; MAPLE; Ontology Matching
https://aclanthology.org/2020.ldl-1.8
Fiorelli, M., Stellato, A. (2020). A Lime-Flavored REST API for Alignment Services. In Proceedings of the 7th Workshop on Linked Data in Linguistics (LDL-2020), Marseille, France (pp. 52-60). European Language Resources Association.
Fiorelli, M; Stellato, A
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/330431
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