Semantic representation of monogenean haptoral Bar image annotation

Digitised monogenean images are usually stored in file system directories in an unstructured manner. In this paper we propose a semantic representation of these images in the form of a Monogenean Haptoral Bar Image (MHBI) ontology, which are annotated with taxonomic classification, diagnostic hard p...

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Bibliographic Details
Published in:BMC bioinformatics 2013-02, Vol.14 (1), p.48-48, Article 48
Main Authors: Abu, Arpah, Susan, Lim Lee Hong, Sidhu, Amandeep Singh, Dhillon, Sarinder Kaur
Format: Article
Language:English
Subjects:
Animals
Controlled vocabularies
Fishes - anatomy & histology
Fishes - classification
Identification and classification
Image Processing, Computer-Assisted - methods
Knowledge Bases
Methods
Semantics
Vocabulary, Controlled
Zoology
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Summary:Digitised monogenean images are usually stored in file system directories in an unstructured manner. In this paper we propose a semantic representation of these images in the form of a Monogenean Haptoral Bar Image (MHBI) ontology, which are annotated with taxonomic classification, diagnostic hard part and image properties. The data we used are basically of the monogenean species found in fish, thus we built a simple Fish ontology to demonstrate how the host (fish) ontology can be linked to the MHBI ontology. This will enable linking of information from the monogenean ontology to the host species found in the fish ontology without changing the underlying schema for either of the ontologies. In this paper, we utilized the Taxonomic Data Working Group Life Sciences Identifier (TDWG LSID) vocabulary to represent our data and defined a new vocabulary which is specific for annotating monogenean haptoral bar images to develop the MHBI ontology and a merged MHBI-Fish ontologies. These ontologies are successfully evaluated using five criteria which are clarity, coherence, extendibility, ontology commitment and encoding bias. In this paper, we show that unstructured data can be represented in a structured form using semantics. In the process, we have come up with a new vocabulary for annotating the monogenean images with textual information. The proposed monogenean image ontology will form the basis of a monogenean knowledge base to assist researchers in retrieving information for their analysis.
ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-14-48