Ontology patterns for tabular representations of biomedical knowledge on neglected tropical diseases

Bioinformatics. 2011 Jul 1;27(13):i349-56. doi: 10.1093/bioinformatics/btr226.

Abstract

Motivation: Ontology-like domain knowledge is frequently published in a tabular format embedded in scientific publications. We explore the re-use of such tabular content in the process of building NTDO, an ontology of neglected tropical diseases (NTDs), where the representation of the interdependencies between hosts, pathogens and vectors plays a crucial role.

Results: As a proof of concept we analyzed a tabular compilation of knowledge about pathogens, vectors and geographic locations involved in the transmission of NTDs. After a thorough ontological analysis of the domain of interest, we formulated a comprehensive design pattern, rooted in the biomedical domain upper level ontology BioTop. This pattern was implemented in a VBA script which takes cell contents of an Excel spreadsheet and transforms them into OWL-DL. After minor manual post-processing, the correctness and completeness of the ontology was tested using pre-formulated competence questions as description logics (DL) queries. The expected results could be reproduced by the ontology. The proposed approach is recommended for optimizing the acquisition of ontological domain knowledge from tabular representations.

Availability and implementation: Domain examples, source code and ontology are freely available on the web at http://www.cin.ufpe.br/~ntdo.

Contact: fss3@cin.ufpe.br.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Disease Vectors
  • Humans
  • Internet
  • Knowledge
  • Neglected Diseases*
  • Parasitic Diseases*
  • Programming Languages
  • Software
  • Terminology as Topic*
  • Tropical Climate