Conference proceeding
Threshold Determination and Engaging Materials Scientists in Ontology Design
METADATA AND SEMANTICS RESEARCH, MTSR 2015, v 544, pp 39-50
01 Jan 2015
Abstract
This paper reports on research exploring a threshold for engaging scientists in semantic ontology development. The domain application, nanocrystalline metals, was pursued using a multi-method approach involving algorithm comparison, semantic concept/term evaluation, and term sorting. Algorithms from four open source term extraction applications (RAKE, Tagger, Kea, and Maui) were applied to a test corpus of preprint abstracts from the arXiv repository. Materials scientists identified 92 terms for ontology inclusion from a combined set of 228 unique terms, and the term sorting activity resulted in 9 top nodes. The combined methods were successful in engaging domain scientists in ontology design, and give a threshold capacity measure (threshold acceptability) to aid future work. This paper presents the research background and motivation, reviews the methods and procedures, and summarizes the initial results. A discussion explores term sorting approaches and mechanisms for determining thresholds for engaging scientist in semantically-driven ontology design and the concept of ontological empowerment.
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11 Record Views
2 citations in Scopus
Details
- Title
- Threshold Determination and Engaging Materials Scientists in Ontology Design
- Creators
- Jane Greenberg - Drexel UniversityYue Zhang - Drexel UniversityAdrian Ogletree - Drexel UniversityGarritt J. Tucker - Drexel UniversityDaniel Foley - Drexel University
- Contributors
- E Garoufallou (Editor)R J Hartley (Editor)P Gaitanou (Editor)
- Publication Details
- METADATA AND SEMANTICS RESEARCH, MTSR 2015, v 544, pp 39-50
- Series
- Communications in Computer and Information Science
- Publisher
- Springer Nature
- Number of pages
- 12
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics); Computer Science (Computing)
- Web of Science ID
- WOS:000368260500004
- Scopus ID
- 2-s2.0-84945937676
- Other Identifier
- 991019168517104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods
- Robotics