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Open Access Open Badges Research article

Semantic representation of monogenean haptoral Bar image annotation

Arpah Abu1, Lim Lee Hong Susan1, Amandeep Singh Sidhu23 and Sarinder Kaur Dhillon1*

Author Affiliations

1 Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia

2 Curtin Sarawak Research Institute, Curtin University, Sarawak, Malaysia

3 School of Biomedical Sciences, Faculty of Health Sciences, Curtin University, Perth, Australia

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BMC Bioinformatics 2013, 14:48  doi:10.1186/1471-2105-14-48

Published: 12 February 2013



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.