An overview of the model integration process: From pre-integration assessment to testing. (January 2017)

• Record Type: Journal Article
• Authors: Belete, Getachew F.; Voinov, Alexey; Laniak, Gerard F.
• Is Part Of: Environmental modelling & software. Volume 87(2017)
• Page Start: 49
• Page End: 63
• Publication Date: 2017-01
• Subjects: Integrated modeling -- Interoperability -- Interfaces -- Wrapping -- Components -- Web services; 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.2016.10.013
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems. Highlights: We identified five major phases of model integration. Pre-integration assessment can help to visualize the integrated system and resolve inconsistency before we spend resources. The strategy we will use to migrate an existing model into integration should be more feasible than re-implementing it.