Web Ontology Language Requirements w.r.t Expressiveness of Taxonomy and Axioms in Medicine

Golbreich, Christine; Dameron, Olivier; Gibaud, Bernard; Burgun, Anita

doi:10.1007/978-3-540-39718-2_12

Cited by 19 publications

(13 citation statements)

References 15 publications

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“…We believe, however, that the single most important factor is the lack of support for modeling principles in ontology development environments. This is the case not only in frame-based systems such as Protégé-used for developing the FMA-but also, as noted by Golbreich et al [27] in description logic-based systems, including OWL editors.…”

Section: Why Do Ontologies Fail To Comply With Modeling Principles?mentioning

confidence: 86%

Law and order: Assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy

Zhang

Bodenreider

2006

Computers in Biology and Medicine

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The objective of this study is to provide an operational definition of principles with which wellformed ontologies should comply. We define 15 such principles, related to classification (e.g., no hierarchical cycles are allowed; concepts have a reasonable number of children), incompatible relationships (e.g., two concepts cannot stand both in a taxonomic and partitive relation), dependence among concepts, and the co-dependence of equivalent sets of relations. Implicit relations-embedded in concept names or inferred from a combination of explicit relations-are used in this process in addition to the relations explicitly represented. As a case study, we investigate the degree to which the Foundational Model of Anatomy (FMA)-a large ontology of anatomy-complies with these 15 principles. The FMA succeeds in complying with all the principles: totally with one and mostly with the others. Reasons for non-compliance are analyzed and suggestions are made for implementing effective enforcement mechanisms in ontology development environments. The limitations of this study are also discussed.

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Section: Why Do Ontologies Fail To Comply With Modeling Principles?mentioning

confidence: 86%

Law and order: Assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy

Zhang

Bodenreider

2006

Computers in Biology and Medicine

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“…The fuzzy DL f KD -ALCIQ extends the fuzzy DL f KD -ALC [9] with inverse roles and QCRs. Although QCRs are not part of OWL they will be added in the future since they are very important for practical applications [4]. Additionally, we have presented a detailed reasoning algorithm for deciding f KD -ALCIQ ABox consistency.…”

Section: Discussionmentioning

confidence: 99%

“…In order for applications to publish information on the Semantic Web they have to use OWL and DLs to represent knowledge. Today, DLs and OWL have been used in many applications, like medical [4], image analysis [5], [6], databases [7] and more. This extensive use has highlighted many deficiencies of OWL, which led to requirements for language extensions [4].…”

Section: Introductionmentioning

confidence: 99%

Reasoning with qualified cardinality restrictions in fuzzy Description Logics

Stoilos¹,

Stamou²,

Kollias³

2008

2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence)

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Abstract-Description Logics (DLs) are modern knowledge representation formalisms which are used today in many applications for reasoning with structured knowledge. Moreover, they are used in the Semantic Web (an extension of the current web) through the ontology language OWL. On the other hand fuzzy Description Logics (fuzzy-DLs) have been proposed as expressive logical formalisms capable of capturing and reasoning with vague and imprecise knowledge in the Semantic Web. In the current paper we investigate on the problem of reasoning with qualified cardinality restrictions (QCRs) in fuzzy DLs, extending previous results on simple number restrictions, thus we present a tableaux algorithm for the the fuzzy-DL fKD-ALCIQ.

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“…It does not rely on any representation formalism. However, it turned out that the consistency rules could not be easily represented in ontology languages such as OWL [18]. Extensions such as RuleML 3 or SWRL 4 could provide very interesting future extensions.…”

Section: Discussionmentioning

confidence: 99%

Using semantic dependencies for consistency management of an ontology of brain–cortex anatomy

Dameron

Musen

Gibaud

2007

Artificial Intelligence in Medicine

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ContextA symbolic model allows developers to represent general knowledge about a domain and the meaning that is commonly associated with it. This knowledge can be used by itself (e.g., for teaching), or indirectly as a reference to process specific facts (e.g., to assist queries or data retrieval). In the latter case, symbolic models are perceived as a key feature to provide software assistance for tasks that now require domain-aware intervention by a human. As interoperability of these software applications is desirable, shared conceptual models, and specifically ontologies, play a major role in a Semantic Web context [1]. Since these models are to be usable by software, they must meet explicit representation and consistency requirements. For medical applications, anatomy provides a common reference used to reason about pathology or localization of functional activity [2,3]. The Foundation Model of Anatomy (FMA) [4] and Galen [5] are two major conceptual models that provide a symbolic representation of human anatomy. However, neither of them provides a satisfactory representation of brain-cortex anatomy. The major sources of neuroanatomical knowledge are paper-based atlases [6,7] and terminological systems such as Neuronames [8].We are working on an ontology of brain-cortex anatomy. Our goal is more to formalize existing knowledge than it is to propose new anatomical concepts or relationships. Our model has been described in previous publications [9,10]. It comprises 304 concepts and 1254 relationships that represent the organization of anatomical structures. Because the brain surface presents complicated folding patterns, typical anatomical structures are gyri (the bulges of cerebral matter, similar to hills), the sulci (the hollow foldings, similar to valleys) and lobes (sets of gyri). Our model's taxonomy hierarchy is composed of three levels. First, the generic level contains concepts such as Lobe or Sulcus, and is mainly used to define the domain and range of the relationships. Second, the abstract level represents a prototypical brain hemisphere, and contains concepts such as Frontal Lobe or Central Sulcus. Third, the lateralized level is used to represent left/right asymmetries, and contains concepts such as Left Frontal lobe. For mereology, the model identifies several relationships such as hasDirectAnatomicalPart, hasAnatomicalPart, hasSegment and their properties, inspired from previous theoretical works [11,12]. The model also represents neighborhood relationships such as the separation of two cortical structures by a sulcus, anatomical continuity, and sulci connection.In this context, managing the semantic consistency of the ontology has been one of our main concerns.

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Web Ontology Language Requirements w.r.t Expressiveness of Taxonomy and Axioms in Medicine

Cited by 19 publications

References 15 publications

Law and order: Assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy

Law and order: Assessing and enforcing compliance with ontological modeling principles in the Foundational Model of Anatomy

Reasoning with qualified cardinality restrictions in fuzzy Description Logics

Using semantic dependencies for consistency management of an ontology of brain–cortex anatomy

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