34 research outputs found
WĂŒsteria
The last two decades have seen considerable efforts directed towards making Electronic Health Records interoperable through improvements in medical ontologies, terminologies and coding systems. Unfortunately, these efforts have been hampered by a number of influential ideas inherited from the work of Eugen WĂŒster, the father of terminology standardization and the founder of ISO TC 37. We here survey WĂŒsterâs ideas â which see terminology work as being focused on the classification of concepts in peopleâs minds â and we argue that they serve still as the basis for a series of influential confusions. We argue further that an ontology based unambiguously, not on concepts, but on the classification of entities in reality can, by removing these confusions, make a vital contribution to ensuring the interoperability of coding systems and healthcare records in the future
What do identifiers in HL7 identify? An essay in the ontology of identity
Health Level 7 (HL7) is an organization seeking to provide universal standards for the exchange of healthcare information. In a document entitled âHL7 Version 3
Standard: Data Typesâ, the HL7 organization advances descriptions of data types recom- mended for use as identifiers. We will argue that the descriptions supplied provide insufficient guidance as to what exactly the entities are which these data types uniquely identify. Are they real things, such as persons or pieces of equipment? Or are they representations of such real things in information artifacts? We here outline the problems faced by HL7 in providing answers to such questions, problems which arise because of the lack of anything like a coherent ontology in the HL7 standard, and we make some recommendations for future improvements
Introducing realist ontology for the representation of adverse events
The goal of the REMINE project is to build a high performance prediction, detection and monitoring platform for managing Risks against Patient Safety (RAPS). Part of the work involves developing in ontology enabling computer-assisted RAPS decision support on the basis of the disease history of a patient as documented in a hospital information system. A requirement of the ontology is to contain a representation for what is commonly referred to by the term 'adverse event', one challenge being that distinct authoritative sources define this term in different and context-dependent ways. The presence of some common ground in all definitions is, however, obvious. Using the analytical principles underlying Basic Formal Ontology and Referent Tracking, both developed in the tradition of philosophical realism, we propose a formal representation of this common ground which combines a reference ontology consisting exclusively of representations of universals and an application ontology which consists representations of defined classes. We argue that what in most cases is referred to by means of the term 'adverse event' - when used generically - is a defined class rather than a universal. In favour of the conception of adverse events as forming a defined class are the arguments that (1) there is no definition for 'adverse event' that carves out a collection of particulars which constitutes the extension of a universal, and (2) the majority of definitions require adverse events to be (variably) the result of some observation, assessment or (absence of) expectation, thereby giving these entities a nominal or epistemological flavour
Signs and Meanings
A background piece on the role of ontology in technology research, focusing especially on the use-mention confusion
Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain
Ontology is a burgeoning field, involving researchers from the computer science, philosophy, data and software engineering, logic, linguistics, and terminology domains. Many ontology-related terms with precise meanings in one of these domains have different meanings in others. Our purpose here is to initiate a path towards disambiguation of such terms. We draw primarily on the literature of biomedical informatics, not least because the problems caused by unclear or ambiguous use of terms have been there most thoroughly addressed. We advance a proposal resting on a distinction of three levels too often run together in biomedical ontology research: 1. the level of reality; 2. the level of cognitive representations of this reality; 3. the level of textual and graphical artifacts. We propose a reference terminology for ontology research and development that is designed to serve as common hub into which the several competing disciplinary terminologies can be mapped. We then justify our terminological choices through a critical treatment of the âconcept orientationâ in biomedical terminology research
Negative findings in electronic health records and biomedical ontologies: a realist approach
PURPOSEâA substantial fraction of the observations made by clinicians and entered into patient records are expressed by means of negation or by using terms which contain negative qualifiers (as in âabsence of pulseâ or âsurgical procedure not performedâ). This seems at first sight to present problems for ontologies, terminologies and data repositories that adhere to a realist view and thus reject any reference to putative non-existing entities. Basic Formal Ontology (BFO) and Referent
Tracking (RT) are examples of such paradigms. The purpose of the research here described was to test a proposal to capture negative findings in electronic health record systems based on BFO and RT.
METHODSâWe analysed a series of negative findings encountered in 748 sentences taken from 41 patient charts. We classified the phenomena described in terms of the various top-level categories and relations defined in BFO, taking into account the role of negation in the corresponding descriptions. We also studied terms from SNOMED-CT containing one or other form of negation. We then explored ways to represent the described phenomena by means of the types of representational units available to realist ontologies such as BFO.
RESULTSâWe introduced a new family of âlacksâ relations into the OBO Relation Ontology. The relation lacks_part, for example, defined in terms of the positive relation part_of, holds between a particular p and a universal U when p has no instance of U as part. Since p and U both exist, assertions involving âlacks_partâ and its cognates meet the requirements of positivity.
CONCLUSIONâBy expanding the OBO Relation Ontology, we were able to accommodate nearly all occurrences of negative findings in the sample studied
Signs and Meanings
A background piece on the role of ontology in technology research, focusing especially on the use-mention confusion
Referent tracking for corporate memories
For corporate memory and enterprise ontology systems to be maximally useful,
they must be freed from certain barriers placed around them by traditional
knowledge management paradigms. This means, above all, that they must mirror
more faithfully those portions of reality which are salient to the workings of the
enterprise, including the changes that occur with the passage of time. The purpose
of this chapter is to demonstrate how theories based on philosophical realism can
contribute to this objective. We discuss how realism-based ontologies (capturing
what is generic) combined with referent tracking (capturing what is specific) can
play a key role in building the robust and useful corporate memories of the future
A Unified Framework for Biomedical Terminologies and Ontologies
The goal of the OBO (Open Biomedical Ontologies) Foundry initiative is to create and maintain an evolving collection of non-overlapping interoperable ontologies that will offer unambiguous representations of the types of entities in biological and biomedical reality. These ontologies are designed to serve non-redundant annotation of data and scientific text. To achieve these ends, the Foundry imposes strict requirements upon the ontologies eligible for inclusion. While these requirements are not met by most existing biomedical terminologies, the latter may nonetheless support the Foundryâs goal of consistent and non-redundant annotation if appropriate mappings of data annotated with their aid can be achieved. To construct such mappings in reliable fashion, however, it is necessary to analyze terminological resources from an ontologically realistic perspective in such a way as to identify the exact import of the âconceptsâ and associated terms which they contain. We propose a framework for such analysis that is designed to maximize the degree to which legacy terminologies and the data coded with their aid can be successfully used for information-driven clinical and translational research