BOOK-CHAPTER

Theory: computing with knowledge to represent and share understanding

Mark GaheganWilliam PikeJunyan Luo

Year: 2009 Cambridge University Press eBooks Pages: 13-33   Publisher: Cambridge University Press

Abstract

The cornerstone of HERO's technological research was our effort to build a HERO collaboratory, which Pike et al. describe in Chapter 3. Another area of HERO technological research attempted to link human understanding and formal systems, such as databases, analyses, and models. Ahlqvist and Yu demonstrate two ways that HERO explored this linkage in Chapter 4. This chapter lays the conceptual foundations for the technologically focused work of Chapters 3 and 4. It concentrates on computing with knowledge structures and on knowledge sharing between participants who may not be co-located. The chapter is organized around the following five questions: Why is a conceptual understanding of collaborative work in general, and HERO work in particular, important, and what advantages does it offer? What is the nature of concepts that human–environment scientists create and use in their attempts to understand and model Earth's complex environmental systems? How can computational systems represent concepts? What languages and reasoning systems can facilitate concept representation and exploit its structure? How can a community of collaborators share conceptual understanding? What roles might conceptual tools play in an evolving national cyberinfrastructure for human–environment sciences? In the end, the chapter shows that before we can begin to collaborate we must be able to answer each of the questions above. The answers to these questions enable us to develop a collaboratory infrastructure for the sharing of meaning, concepts, information, and ultimately knowledge.

Keywords:
HERO Collaboratory Cornerstone Linkage (software) Computer science Data science World Wide Web Geography Artificial intelligence Archaeology Chemistry

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Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Quality and Management
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Biomedical Text Mining and Ontologies
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
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