Limits...
Logic-based assessment of the compatibility of UMLS ontology sources.

Jiménez-Ruiz E, Grau BC, Horrocks I, Berlanga R - J Biomed Semantics (2011)

Bottom Line: We then propose general principles and specific logic-based techniques to effectively detect and repair such errors.Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone.The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departamento de Lenguajes y Sistemas Informáticos, Universitat Jaume I, Campus de Riu Sec, Castellón, Spain. ernesto.jimenez.ruiz@gmail.com.

ABSTRACT

Background: The UMLS Metathesaurus (UMLS-Meta) is currently the most comprehensive effort for integrating independently-developed medical thesauri and ontologies. UMLS-Meta is being used in many applications, including PubMed and ClinicalTrials.gov. The integration of new sources combines automatic techniques, expert assessment, and auditing protocols. The automatic techniques currently in use, however, are mostly based on lexical algorithms and often disregard the semantics of the sources being integrated.

Results: In this paper, we argue that UMLS-Meta's current design and auditing methodologies could be significantly enhanced by taking into account the logic-based semantics of the ontology sources. We provide empirical evidence suggesting that UMLS-Meta in its 2009AA version contains a significant number of errors; these errors become immediately apparent if the rich semantics of the ontology sources is taken into account, manifesting themselves as unintended logical consequences that follow from the ontology sources together with the information in UMLS-Meta. We then propose general principles and specific logic-based techniques to effectively detect and repair such errors.

Conclusions: Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone. The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents.

No MeSH data available.


Unsatisfiability due to inherent incompatibilities between FMA and NCI
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3105494&req=5

Figure 3: Unsatisfiability due to inherent incompatibilities between FMA and NCI

Mentions: Detecting incompatibilities between the sources. Even if the mappings between two ontology sources are the intended ones, the sources may describe a particular aspect of the domain in incompatible ways. For example, consider Figure 3 describing the notion of “Visceral Pleura” in FMA and NCI. The three mappings between the entities “Visceral Pleura”, “Lung” and “Thoracic Cavity” in both ontologies are clearly the intended ones. However, their integration results in Visceral_Pleura becoming unsatisfiable. According to NCI, the visceral pleura is located in a lung; furthermore, it is a pleural tissue, which can only be located in the thoracic cavity. However, according to FMA the thoracic cavity is an immaterial anatomical entity, whereas the lung is a material anatomical entity. Finally, material and immaterial entities are disjoint, as implied by FMA. Therefore, the visceral pleura is located in some anatomical entity that is both material and immaterial, which leads to a contradiction.


Logic-based assessment of the compatibility of UMLS ontology sources.

Jiménez-Ruiz E, Grau BC, Horrocks I, Berlanga R - J Biomed Semantics (2011)

Unsatisfiability due to inherent incompatibilities between FMA and NCI
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105494&req=5

Figure 3: Unsatisfiability due to inherent incompatibilities between FMA and NCI
Mentions: Detecting incompatibilities between the sources. Even if the mappings between two ontology sources are the intended ones, the sources may describe a particular aspect of the domain in incompatible ways. For example, consider Figure 3 describing the notion of “Visceral Pleura” in FMA and NCI. The three mappings between the entities “Visceral Pleura”, “Lung” and “Thoracic Cavity” in both ontologies are clearly the intended ones. However, their integration results in Visceral_Pleura becoming unsatisfiable. According to NCI, the visceral pleura is located in a lung; furthermore, it is a pleural tissue, which can only be located in the thoracic cavity. However, according to FMA the thoracic cavity is an immaterial anatomical entity, whereas the lung is a material anatomical entity. Finally, material and immaterial entities are disjoint, as implied by FMA. Therefore, the visceral pleura is located in some anatomical entity that is both material and immaterial, which leads to a contradiction.

Bottom Line: We then propose general principles and specific logic-based techniques to effectively detect and repair such errors.Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone.The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents.

View Article: PubMed Central - HTML - PubMed

Affiliation: Departamento de Lenguajes y Sistemas Informáticos, Universitat Jaume I, Campus de Riu Sec, Castellón, Spain. ernesto.jimenez.ruiz@gmail.com.

ABSTRACT

Background: The UMLS Metathesaurus (UMLS-Meta) is currently the most comprehensive effort for integrating independently-developed medical thesauri and ontologies. UMLS-Meta is being used in many applications, including PubMed and ClinicalTrials.gov. The integration of new sources combines automatic techniques, expert assessment, and auditing protocols. The automatic techniques currently in use, however, are mostly based on lexical algorithms and often disregard the semantics of the sources being integrated.

Results: In this paper, we argue that UMLS-Meta's current design and auditing methodologies could be significantly enhanced by taking into account the logic-based semantics of the ontology sources. We provide empirical evidence suggesting that UMLS-Meta in its 2009AA version contains a significant number of errors; these errors become immediately apparent if the rich semantics of the ontology sources is taken into account, manifesting themselves as unintended logical consequences that follow from the ontology sources together with the information in UMLS-Meta. We then propose general principles and specific logic-based techniques to effectively detect and repair such errors.

Conclusions: Our results suggest that the methodologies employed in the design of UMLS-Meta are not only very costly in terms of human effort, but also error-prone. The techniques presented here can be useful for both reducing human effort in the design and maintenance of UMLS-Meta and improving the quality of its contents.

No MeSH data available.