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CSEO - the Cigarette Smoke Exposure Ontology.

Younesi E, Ansari S, Guendel M, Ahmadi S, Coggins C, Hoeng J, Hofmann-Apitius M, Peitsch MC - J Biomed Semantics (2014)

Bottom Line: In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases.The CSEO (version 1.0) is composed of 20091 concepts.Moreover, it showed a promising performance when used to answer domain expert questions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Schloss Birlinghoven, 53754 Sankt Augustin, Germany.

ABSTRACT

Background: In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases. Due to the growing number of such data, there is a need for domain-specific standard ontologies to facilitate the integration of tobacco exposure data.

Results: The CSEO (version 1.0) is composed of 20091 concepts. The ontology in its current form is able to capture a wide range of cigarette smoke exposure concepts within the knowledge domain of exposure science with a reasonable sensitivity and specificity. Moreover, it showed a promising performance when used to answer domain expert questions. The CSEO complies with standard upper-level ontologies and is freely accessible to the scientific community through a dedicated wiki at https://publicwiki-01.fraunhofer.de/CSEO-Wiki/index.php/Main_Page.

Conclusions: The CSEO has potential to become a widely used standard within the academic and industrial community. Mainly because of the emerging need of systems toxicology to controlled vocabularies and also the lack of suitable ontologies for this domain, the CSEO prepares the ground for integrative systems-based research in the exposure science.

No MeSH data available.


Related in: MedlinePlus

Schematic representation of the main ontology classes and class provenance between BFO, ExO, and CSEO. Arrow legend: blue: is-a relations; yellow: ExO: is_associated_with; orange: ExO: interacts_with_an_exposure_stressor_via; brown: MGED: has_experiment_ design; violet: ExO: interacts_with.
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Figure 2: Schematic representation of the main ontology classes and class provenance between BFO, ExO, and CSEO. Arrow legend: blue: is-a relations; yellow: ExO: is_associated_with; orange: ExO: interacts_with_an_exposure_stressor_via; brown: MGED: has_experiment_ design; violet: ExO: interacts_with.

Mentions: The CSEO was designed to be compliant with the Basic Formal Ontology (BFO). The BFO was adopted to define the upper-level standard architecture. The BFO is designed to support development of domain ontologies for scientific research [22]. On the other hand, the ExO is the only existing and intuitive semantic framework used by the exposure science community that provides a good template for plugging in subdomain ontologies related to the exposure domain. Therefore, the ExO superclasses were used as root concepts for the CSEO. Accordingly, the CSEO populates the ExO for the concepts of the cigarette smoke risk subdomain and also complies with requirements of the OBO Foundry and RO (Relation Ontology). FigureĀ 2 depicts the architecture of the CSEO in relation to BFO and ExO and its main classes. Such an architecture is expected to incorporate provenance into the CSEO so that concepts can be traced back to their corresponding upper-level classes in ExO and BFO.


CSEO - the Cigarette Smoke Exposure Ontology.

Younesi E, Ansari S, Guendel M, Ahmadi S, Coggins C, Hoeng J, Hofmann-Apitius M, Peitsch MC - J Biomed Semantics (2014)

Schematic representation of the main ontology classes and class provenance between BFO, ExO, and CSEO. Arrow legend: blue: is-a relations; yellow: ExO: is_associated_with; orange: ExO: interacts_with_an_exposure_stressor_via; brown: MGED: has_experiment_ design; violet: ExO: interacts_with.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4120729&req=5

Figure 2: Schematic representation of the main ontology classes and class provenance between BFO, ExO, and CSEO. Arrow legend: blue: is-a relations; yellow: ExO: is_associated_with; orange: ExO: interacts_with_an_exposure_stressor_via; brown: MGED: has_experiment_ design; violet: ExO: interacts_with.
Mentions: The CSEO was designed to be compliant with the Basic Formal Ontology (BFO). The BFO was adopted to define the upper-level standard architecture. The BFO is designed to support development of domain ontologies for scientific research [22]. On the other hand, the ExO is the only existing and intuitive semantic framework used by the exposure science community that provides a good template for plugging in subdomain ontologies related to the exposure domain. Therefore, the ExO superclasses were used as root concepts for the CSEO. Accordingly, the CSEO populates the ExO for the concepts of the cigarette smoke risk subdomain and also complies with requirements of the OBO Foundry and RO (Relation Ontology). FigureĀ 2 depicts the architecture of the CSEO in relation to BFO and ExO and its main classes. Such an architecture is expected to incorporate provenance into the CSEO so that concepts can be traced back to their corresponding upper-level classes in ExO and BFO.

Bottom Line: In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases.The CSEO (version 1.0) is composed of 20091 concepts.Moreover, it showed a promising performance when used to answer domain expert questions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Schloss Birlinghoven, 53754 Sankt Augustin, Germany.

ABSTRACT

Background: In the past years, significant progress has been made to develop and use experimental settings for extensive data collection on tobacco smoke exposure and tobacco smoke exposure-associated diseases. Due to the growing number of such data, there is a need for domain-specific standard ontologies to facilitate the integration of tobacco exposure data.

Results: The CSEO (version 1.0) is composed of 20091 concepts. The ontology in its current form is able to capture a wide range of cigarette smoke exposure concepts within the knowledge domain of exposure science with a reasonable sensitivity and specificity. Moreover, it showed a promising performance when used to answer domain expert questions. The CSEO complies with standard upper-level ontologies and is freely accessible to the scientific community through a dedicated wiki at https://publicwiki-01.fraunhofer.de/CSEO-Wiki/index.php/Main_Page.

Conclusions: The CSEO has potential to become a widely used standard within the academic and industrial community. Mainly because of the emerging need of systems toxicology to controlled vocabularies and also the lack of suitable ontologies for this domain, the CSEO prepares the ground for integrative systems-based research in the exposure science.

No MeSH data available.


Related in: MedlinePlus