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

Santana F, Schober D, Medeiros Z, Freitas F, Schulz S - Bioinformatics (2011)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Informatics Center, Federal University of Pernambuco (CIn/UFPE), Recife, Brazil. fss3@cin.ufpe.br

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.

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Related in: MedlinePlus

Epidemiological triad. The main infection components are host, agent and environment. The vector is frequently related to all components making it a hub node in the transmission network, and hence a good target for infection control approaches.
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Figure 1: Epidemiological triad. The main infection components are host, agent and environment. The vector is frequently related to all components making it a hub node in the transmission network, and hence a good target for infection control approaches.

Mentions: The table exemplifies the main players in a typical disease transmission path such as described in the classical epidemiological triad (Fig. 1). Transmission process and disease manifestation are the result of an interaction between the infective agent (pathogen) and a susceptible host in a given environment. The host is any organism capable of being infected by the agent. Vectors are defined as organisms merely transmitting the infectious agents, without being the intended host for the parasitic pathogen. Another role that participants of this interaction process can play is the role of pathogen reservoirs, e.g. animals, plant, soil or inanimate matter (Neves et al., 2005).Fig. 1.


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

Santana F, Schober D, Medeiros Z, Freitas F, Schulz S - Bioinformatics (2011)

Epidemiological triad. The main infection components are host, agent and environment. The vector is frequently related to all components making it a hub node in the transmission network, and hence a good target for infection control approaches.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117366&req=5

Figure 1: Epidemiological triad. The main infection components are host, agent and environment. The vector is frequently related to all components making it a hub node in the transmission network, and hence a good target for infection control approaches.
Mentions: The table exemplifies the main players in a typical disease transmission path such as described in the classical epidemiological triad (Fig. 1). Transmission process and disease manifestation are the result of an interaction between the infective agent (pathogen) and a susceptible host in a given environment. The host is any organism capable of being infected by the agent. Vectors are defined as organisms merely transmitting the infectious agents, without being the intended host for the parasitic pathogen. Another role that participants of this interaction process can play is the role of pathogen reservoirs, e.g. animals, plant, soil or inanimate matter (Neves et al., 2005).Fig. 1.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Informatics Center, Federal University of Pernambuco (CIn/UFPE), Recife, Brazil. fss3@cin.ufpe.br

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.

Show MeSH
Related in: MedlinePlus