Formal nursing terminology systems: a means to an end

In response to the need to support diverse and complex information requirements, nursing has developed a number of different terminology systems. The two main kinds of systems that have emerged are enumerative systems and combinatorial systems, although some systems have characteristics of both approaches. Differences in the structure and content of terminology systems, while useful at a local level, prevent effective wider communication, information sharing, integration of record systems, and comparison of nursing elements of healthcare information at a more global level. Formal nursing terminology systems present an alternative approach. This paper describes a number of recent initiatives and explains how these emerging approaches may help to augment existing nursing terminology systems and overcome their limitations through mediation. The development of formal nursing terminology systems is not an end in itself and there remains a great deal of work to be done before success can be claimed. This paper presents an overview of the key issues outstanding and provides recommendations for a way forward

An Object-Oriented Approach to Knowledge Representation in a Biomedical Domain

An object-oriented approach has been applied to the different stages involved in developing a knowledge base about insulin metabolism. At an early stage the separation of terminological and assertional knowledge was made. The terminological component was developed by medical experts and represented in CORE. An object-oriented knowledge acquisition process was applied to the assertional knowledge. A frame description is proposed which includes features like states and events, inheritance and collaboration. States and events are formalized with qualitative calculus. The terminological knowledge was very useful in the development of the assertional component. It assisteed in understanding the problem domain, and in the implementation stage, it assisted in building good inheritance hierarchies

Interpretation of an international terminology standard in the development of a logic-based compositional terminology

Purpose: Version 1.0 of the International Classification for Nursing Practice (ICNP®) is a logic-based compositional terminology. International Organization for Standardization (ISO) 18104:2003 Health Informatics¿Integration of a reference terminology model for nursing is an international standard to support the development, testing and implementation of nursing terminologies. Methods: This study examines how ISO 18104:2003 has been interpreted in the development of ICNP® Version 1.0 by identifying mappings between ICNP® and the ISO standard. Representations of diagnostic and interventional statements within ICNP® are also analyzed according to the requirements mandated by the ISO standard. Results: All structural components of ISO 18104:2003 i.e. semantic categories, semantic domains, qualifiers and semantic links are represented either directly or in interpreted form within ICNP®. The formal representations within ICNP® of diagnostic and interventional statements meet the requirement of the ISO standard. Conclusions: The findings of this study demonstrate that ICNP® Version 1.0 conforms to ISO 18104:2003. More importantly perhaps, this study provides practical examples of how components of a terminology standard might be interpreted and it examines how such a standard might be used to support the definition of high-level schemata in developing logic-based compositional terminologies

Logical ontology for mediating between nursing intervention terminology systems

Objectives: Several researchers have proposed the use of logical ontologies as reference terminologies'. However, there are a number of unresolved issues. This article describes the development of a logical ontology for nursing interventions and presents the results of evaluation. Methods: Initially this study involved the development in GRAIL of two separate experimental ontologies: an ontology based on the textual content of informal definitions for nursing interventions drown from the Nursing interventions Classification; and an ontology based On labels for the some nursing interventions. Following initial bench-testing, the ontology based on labels was selected for extension (to accommodate also nursing intervention components of the Home Health Care Classification System and the Omaha System), for further testing and for external evaluation. Results: A hierarchy of nursing interventions generated automatically from the experimental antolagy based on informal definitions cantained only 3 hierarchical relationships, compared to 214 for the initial ontology based on labels. For the final extended ontology based on labels, the generated hierarchy contained the three source terminology systems in entirety - there were a total of 2861 hierarchical relationships. While the results of comporative bench testing of the final ontology were fovourable, the results of external evaluation were mixed and showed little agreement between reviewers. Conclusion: This study suggests that while a logical ontology based on labels might be a useful tool for mediating between nursing intervention terminology systems, a formative consensus type development methodology might improve the approach by helping to harmonise ideological differences that may exist across the nursing profession

Ontology-assisted database integration to support natural language processing and biomedical data-mining

Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for the purposes of making computers understand medical natural language

Computational Ontologies and Information Systems II: Formal Specification

This paper extends the study of ontologies in Part I of this study (Volume 14, Article 8) in the context of Information Systems. The basic foundations of computational ontologies presented in Part I are extended to formal specifications in this paper. This paper provides a review of the formalisms, languages, and tools for specifying and implementing computational ontologies Directions for future research are also provided

Using graph transformation algorithms to generate natural language equivalents of icons expressing medical concepts

A graphical language addresses the need to communicate medical information in a synthetic way. Medical concepts are expressed by icons conveying fast visual information about patients' current state or about the known effects of drugs. In order to increase the visual language's acceptance and usability, a natural language generation interface is currently developed. In this context, this paper describes the use of an informatics method ---graph transformation--- to prepare data consisting of concepts in an OWL-DL ontology for use in a natural language generation component. The OWL concept may be considered as a star-shaped graph with a central node. The method transforms it into a graph representing the deep semantic structure of a natural language phrase. This work may be of future use in other contexts where ontology concepts have to be mapped to half-formalized natural language expressions.Comment: Presented at the TSD 2014 conference: Text, Speech and Dialogue, 17th international conference. Brno, Czech Republic, September 8-12, 2014. 10 pages, 7 figure