Use of ontologies in a pervasive computing environment

Ontologies are entering widespread use in many areas such as knowledge and content management, electronic commerce and the Semantic Web. In this paper we show how the use of ontologies has helped us overcome some important problems in the development of pervasive computing environments. We have integrated ontologies and Semantic Web technology into our pervasive computing infrastructure. Our investigations have shown that Semantic Web technology can be integrated into our CORBA-based infrastructure to augment several important services. This work suggests a number of requirements for future research in the development of ontologies, reasoners, languages and interfaces.

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HIVEing: the effect of a semantic web technology on inter-indexer consistency

Journal of Documentation ◽

10.1108/jd-07-2012-0083 ◽

2014 ◽

Vol 70 (3) ◽

pp. 307-329 ◽

Cited By ~ 3

Author(s):

Hollie White ◽

Craig Willis ◽

Jane Greenberg

Keyword(s):

Semantic Web ◽

Study Data ◽

Web Technology ◽

Future Research ◽

Free Text ◽

Content Type ◽

Document Structure ◽

Semantic Web Technology ◽

Significant Difference ◽

The Impact

Purpose – The purpose of this paper is to examine the effect of the Helping Interdisciplinary Vocabulary Engineering (HIVE) system on the inter-indexer consistency of information professionals when assigning keywords to a scientific abstract. This study examined first, the inter-indexer consistency of potential HIVE users; second, the impact HIVE had on consistency; and third, challenges associated with using HIVE. Design/methodology/approach – A within-subjects quasi-experimental research design was used for this study. Data were collected using a task-scenario based questionnaire. Analysis was performed on consistency results using Hooper's and Rolling's inter-indexer consistency measures. A series of t-tests was used to judge the significance between consistency measure results. Findings – Results suggest that HIVE improves inter-indexing consistency. Working with HIVE increased consistency rates by 22 percent (Rolling's) and 25 percent (Hooper's) when selecting relevant terms from all vocabularies. A statistically significant difference exists between the assignment of free-text keywords and machine-aided keywords. Issues with homographs, disambiguation, vocabulary choice, and document structure were all identified as potential challenges. Research limitations/implications – Research limitations for this study can be found in the small number of vocabularies used for the study. Future research will include implementing HIVE into the Dryad Repository and studying its application in a repository system. Originality/value – This paper showcases several features used in HIVE system. By using traditional consistency measures to evaluate a semantic web technology, this paper emphasizes the link between traditional indexing and next generation machine-aided indexing (MAI) tools.

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