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Semantic Integration for Research Environments

Semantic Integration for Research Environments

Tomasz Gubala, Marian Bubak, Peter Sloot
Copyright: © 2009 |Pages: 17
ISBN13: 9781605663746|ISBN10: 1605663743|EISBN13: 9781605663753
DOI: 10.4018/978-1-60566-374-6.ch026
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MLA

Gubala, Tomasz, et al. "Semantic Integration for Research Environments." Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, edited by Mario Cannataro, IGI Global, 2009, pp. 514-530. https://doi.org/10.4018/978-1-60566-374-6.ch026

APA

Gubala, T., Bubak, M., & Sloot, P. (2009). Semantic Integration for Research Environments. In M. Cannataro (Ed.), Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare (pp. 514-530). IGI Global. https://doi.org/10.4018/978-1-60566-374-6.ch026

Chicago

Gubala, Tomasz, Marian Bubak, and Peter Sloot. "Semantic Integration for Research Environments." In Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, edited by Mario Cannataro, 514-530. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-374-6.ch026

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Abstract

Research environments for modern, cross-disciplinary scientific endeavors have to unite multiple users, with varying levels of expertise and roles, along with multitudes of data sources and processing units. The high level of required integration contrasts with the loosely-coupled nature of environments which are appropriate for research. The problem is to support integration of dynamic service-based infrastructures with data sources, tools and users in a way that conserves ubiquity, extensibility and usability. This chapter presents a close examination of related achievements in the field and the description of proposed approach. It shows that integration of loosely-coupled system components with formallydefined vocabularies may fulfill the listed requirements. The authors demonstrate that combining formal representations of domain knowledge with techniques like data integration, semantic annotations and shared vocabularies, enables the development of systems for modern e-Science. For demonstration they present how several semantically-augmented experiments are modeled in the ViroLab virtual laboratory for virology.

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