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Scientific Knowledge Engineering: a conceptual delineation and overview of the state of the art

Published online by Cambridge University Press:  29 March 2016

Paulo Sérgio M. Dos Santos Open the ORCID record for Paulo Sérgio M. Dos Santos [Opens in a new window]  and
Guilherme H. Travassos Open the ORCID record for Guilherme H. Travassos [Opens in a new window]
Paulo Sérgio M. Dos Santos
Affiliation:
Ilha do Fundão, Centro de Tecnologia, Bloco H, Sala 317, Rio de Janeiro, RJ, Brazil e-mail: [email protected], [email protected]
Guilherme H. Travassos
Affiliation:
Ilha do Fundão, Centro de Tecnologia, Bloco H, Sala 317, Rio de Janeiro, RJ, Brazil e-mail: [email protected], [email protected]
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Abstract

As a community work, scientific contributions are usually built incrementally, involving some transformation, expansion or refutation of existing conceptual and propositional networks. As the body of knowledge increases, scientists concentrate more effort on ensuring that new hypotheses and observations are needed and consistent with previous findings. In this paper, we will characterize Knowledge Engineering as an important groundwork for structuring scientific knowledge. We argue that knowledge-based computational infrastructures can support researchers in organizing and making explicit the main aspects needed to make inferences or extract conclusions from an existing body of knowledge. This view is also comparatively built, contrasting it with alternatives for manipulating scientific knowledge, namely data-intensive approaches and the computational discovery of scientific knowledge. The current state of the art is presented with 22 knowledge representations and computational infrastructure implementations, with their main relevant properties analyzed and compared. Based on this review and on the theoretical foundations of Knowledge Engineering, a high level step-by-step approach for specifying and constructing scientific computational environments is described. The paper concludes by indicating paths for further development of the view initiated here, especially related to the technical specificities that originates from applying Knowledge Engineering to scientific knowledge.

Type
Articles
Information
The Knowledge Engineering Review , Volume 31 , Issue 2 , March 2016 , pp. 167 - 199
Copyright
© Cambridge University Press, 2016 

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References

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