Automatic semantic enrichment of data services

Oliveira, Bruno C. N.; Huf, Alexis; Salvadori, Ivan; Siqueira, Frank

doi:10.1145/3151759.3151783

Cited by 2 publications

(1 citation statement)

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“…Therefore, legacy data services are able to serve both semantic description and representations to their consumers. This paper is an Enhancement of data services extended version of (Oliveira et al, 2017), that includes the generation of semantic service descriptions, contains an expanded exposition of the mechanism responsible for high performance results and provides further evaluations of the architecture. Results show that our approach can achieve suitable F-Measure scores and reasonable performance in terms of processing time and memory consumption.…”

Section: Introductionmentioning

confidence: 99%

OntoGenesis: an architecture for automatic semantic enhancement of data services

Oliveira

Huf

Salvadori

et al. 2019

IJWIS

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Purpose This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to semantically enrich data services, so that they can dynamically provide both semantic descriptions and data representations. Design/methodology/approach The enrichment approach is designed to intercept the requests from data services. Therefore, a domain ontology is constructed and evolved in accordance with the syntactic representations provided by such services in order to define the data concepts. In addition, a property matching mechanism is proposed to exploit the potential data intersection observed in data service representations and external data sources so as to enhance the domain ontology with new equivalences triples. Finally, the enrichment approach is capable of deriving on demand a semantic description and data representations that link to the domain ontology concepts. Findings Experiments were performed using real-world datasets, such as DBpedia, GeoNames as well as open government data. The obtained results show the applicability of the proposed architecture and that it can boost the development of semantic data services. Moreover, the matching approach achieved better performance when compared with other existing approaches found in the literature. Research limitations/implications This work only considers services designed as data providers, i.e., services that provide an interface for accessing data sources. In addition, our approach assumes that both data services and external sources – used to enhance the domain ontology – have some potential of data intersection. Such assumption only requires that services and external sources share particular property values. Originality/value Unlike most of the approaches found in the literature, the architecture proposed in this paper is meant to semantically enrich data services in such way that human intervention is minimal. Furthermore, an automata-based index is also presented as a novel method that significantly improves the performance of the property matching mechanism.

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Section: Introductionmentioning

confidence: 99%