Title |
Analysing Syntactic Regularities and Irregularities in SNOMED-CT
|
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Published in |
Journal of Biomedical Semantics, December 2012
|
DOI | 10.1186/2041-1480-3-8 |
Pubmed ID | |
Authors |
Eleni Mikroyannidi, Robert Stevens, Luigi Iannone, Alan Rector |
Abstract |
In this paper we demonstrate the usage of RIO; a framework for detecting syntactic regularities using cluster analysis of the entities in the signature of an ontology. Quality assurance in ontologies is vital for their use in real applications, as well as a complex and difficult task. It is also important to have such methods and tools when the ontology lacks documentation and the user cannot consult the ontology developers to understand its construction. One aspect of quality assurance is checking how well an ontology complies with established 'coding standards'; is the ontology regular in how descriptions of different types of entities are axiomatised? Is there a similar way to describe them and are there any corner cases that are not covered by a pattern? Detection of regularities and irregularities in axiom patterns should provide ontology authors and quality inspectors with a level of abstraction such that compliance to coding standards can be automated. However, there is a lack of such reverse ontology engineering methods and tools. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Sweden | 1 | 33% |
Comoros | 1 | 33% |
United Kingdom | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Korea, Republic of | 1 | 4% |
Unknown | 24 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 7 | 28% |
Student > Doctoral Student | 3 | 12% |
Other | 3 | 12% |
Student > Master | 3 | 12% |
Student > Ph. D. Student | 2 | 8% |
Other | 3 | 12% |
Unknown | 4 | 16% |
Readers by discipline | Count | As % |
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Computer Science | 8 | 32% |
Agricultural and Biological Sciences | 5 | 20% |
Medicine and Dentistry | 3 | 12% |
Biochemistry, Genetics and Molecular Biology | 1 | 4% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 4% |
Other | 2 | 8% |
Unknown | 5 | 20% |