Finding reusable structured resources for the integration of environmental research data. (November 2020)

• Record Type: Journal Article
• Authors: Campos, Patricia M.C.; Reginato, Cassio C.; Almeida, João Paulo A.; Barcellos, Monalessa P.; de Almeida Falbo, Ricardo; Silva Souza, Vítor E.; Guizzardi, Giancarlo
• Is Part Of: Environmental modelling & software. Volume 133(2020)
• Publication Date: 2020-11
• Subjects: Data integration -- Environmental research data -- Knowledge resources -- Reuse -- Systematic search -- Ontology; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104813
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Successful data integration requires careful examination of data semantics, a task that has often been approached with the use of ontologies. However, there are some barriers to build ontologies for data integration in complex domains such as the environmental one. A relevant problem is the development of new ontologies disregarding previous knowledge resources such as reference models and vocabularies. This paper addresses this challenge by proposing a systematic approach (dubbed CLeAR) for the identification and selection of reusable artifacts for building ontologies with the purpose of research data integration. CLeAR follows some principles of the systematic literature reviews, supporting the search for structured resources in the scientific literature. We apply CLeAR to the environmental domain. A total of 543 publications were surveyed. The results obtained provide a set of 75 structured resources for the environmental domain, evaluated according domain coverage and some quality attributes (e.g., proper documentation, community acceptance). Highlights: We address the reuse of resources to facilitate ontology-based data integration. We propose a systematic approach for identifying and selecting reusable resources. We apply the approach to the water quality domain. We provide an overview of reusable resources in the literature. We provide practical guidelines for evaluating available resources.