A case study in ontology library construction

Heijst, GertJan van; Falasconi, Sabina; Abu‐Hanna, Ameen; Schreiber, Guus; Stefanelli, Mario

doi:10.1016/0933-3657(95)00005-q

Cited by 40 publications

(20 citation statements)

References 15 publications

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“…Whatever specific notations are used, the combination of conceptual and formal specifications provides great advantages, which the great majority of current terminological systems do not enjoy, mainly due to the lack of formal specifications. A challenging research issue is the automatic reasoning with (part of) these specifications, for example, as attempted in ontology-based knowledge acquisition such as in GAMES [37] and PRO-TEGE [38].…”

Section: Methodsmentioning

confidence: 99%

Analysis and Design of an Ontology for Intensive Care Diagnoses

Keizer¹,

Abu‐Hanna²,

Cornet³

et al. 1999

Methods Inf Med

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Information about the patient's health status and about medical problems in general, play an important role in stratifying a patient population for quality assurance of intensive care. A terminological system which supports both the description of health problems for daily care practice and the aggregation of diagnostic information for evaluative research, is desirable for description of the patient population. This study describes the engineering of an ontology that facilitates a terminological system for intensive care diagnoses. We analyzed the criteria for such an ontology and evaluated existing terminological systems according to these criteria. The analysis shows that none of the existing terminological systems completely satisfies all our criteria. We describe choices regarding design, content and representation of a new ontology on which an adequate terminological system is based. The proposed ontology is characterized by the explicit and formal representation of the domain model, the metaspecification of its concepts, the vocabulary to define concepts and the nomenclature to support the composition of new concepts.

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Section: Methodsmentioning

confidence: 99%

Analysis and Design of an Ontology for Intensive Care Diagnoses

Keizer¹,

Abu‐Hanna²,

Cornet³

et al. 1999

Methods Inf Med

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“…To determine how the QR models can be formalised as ontologies, an ontological perspective on QR is taken. Previous research distinguishes different types of ontologies based on the type of ontological commitments they make [29]. For example, the ontological commitments of a knowledge representation language consist of the domain independent concepts.…”

Section: Export Of Qr Models Into Owlmentioning

confidence: 99%

Semantic Techniques for Enabling Knowledge Reuse in Conceptual Modelling

Gracia

Liem

Lozano

et al. 2010

Lecture Notes in Computer Science

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Abstract. Conceptual modelling tools allow users to construct formal representations of their conceptualisations. These models are typically developed in isolation, unrelated to other user models, thus losing the opportunity of incorporating knowledge from other existing models or ontologies that might enrich the modelling process. We propose to apply Semantic Web techniques to the context of conceptual modelling (more particularly to the domain of qualitative reasoning), to smoothly interconnect conceptual models created by different users, thus facilitating the global sharing of scientific data contained in such models and creating new learning opportunities for people who start modelling. This paper describes how semantic grounding techniques can be used during the creation of qualitative reasoning models, to bridge the gap between the imprecise user terminology and a well defined external common vocabulary. We also explore the application of ontology matching techniques between models, which can provide valuable feedback during the model construction process.

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“…While our group focused on medical records and ontologies, at least four other groups worked on developing re-usable problem solving methodologies -Mark Musen and his colleagues at Stanford with PROTÉGÉ and EON [78][79][80]124], Bob Wielinga and his colleagues in Amsterdam with the generic KADS methodology [114,133,134], Mario Stefanelli and colleagues in Pavia's work applying KADS and related ideas to medicine in GAMES [38,112,126], and John Fox's work on ProForma with its emphasis on safety critical systems [42,44]. The first three took the distinction between the 'ontology' and the 'problem solving' method as basic, but concentrated more heavily on making the problem solving methods re-usable.…”

Section: Decision Support and Drug Informationmentioning

confidence: 99%

AIM: a personal view of where I have been and where we might be going

Rector

2001

Artificial Intelligence in Medicine

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My own career in Medical Informatics and AI in Medicine has oscillated between concerns with medical records and concerns with knowledge representation with decision support as a pivotal integrating issue. It has focused on using AI to organise information and reduce 'muddle' and improve the user interfaces to produce 'useful and usable systems' to help doctors with a 'humanly impossible task'. Increasingly knowledge representation and ontologies have become the fulcrum for orchestrating re-use of information and integration of systems. Encouragingly, the dilemma between computational tractability and expressiveness is lessening, and ontologies and description logics are joining the mainstream both in AI in Medicine and in Intelligent Information Management generally. It has been shown possible to scale up ontologies to meet medical needs, and increasingly ontologies are playing a key role in meeting the requirements to scale up the complexity of clinical systems to meet the ever increasing demands brought about by new emphasis on reduction of errors, clinical accountability, and the explosion of knowledge on the Web.

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A case study in ontology library construction

Cited by 40 publications

References 15 publications

Analysis and Design of an Ontology for Intensive Care Diagnoses

Analysis and Design of an Ontology for Intensive Care Diagnoses

Semantic Techniques for Enabling Knowledge Reuse in Conceptual Modelling

AIM: a personal view of where I have been and where we might be going

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