126 research outputs found
Providing a Realist Perspective on the eyeGENE Database System
One of the achievements of the eyeGENE Network is a repository of DNA samples of patients with inherited eye diseases and an associated database that tracks key elements of phenotype and genotype information for each patient. Although its database structure serves its direct research needs, eyeGENE has set a goal of enhancing this structure to become increasingly well integrated with medical information standards over time. This goal should be achieved by ensuring semantic interoperability with other information systems but without adopting the incoherencies and inconsistencies found in available biomedical standards. Therefore, eyeGENE’s current pragmatic perspective with focus on data and information, rather than what the information is about, should shift to a realism-based perspective that includes also the portion of reality described, and the competing opinions that clinicians may hold about it. An analysis of eyeGENE’s database structure and user interfaces suggests that such a transition is possible indeed
Malaria Diagnosis and the Plasmodium Life Cycle: the BFO Perspective
Definitive diagnosis of malaria requires the demonstration through laboratory tests of the presence within the patient of malaria parasites or their components. Since malaria parasites can be present even in the absence of malaria, and since symptoms of malaria can be manifested even in the absence of malaria parasites, malaria diagnosis raises important issues for the adequate understanding of disease, etiology and diagnosis. One approach to the resolution of these issues adopts a realist view, according to which the needed clarifications will be derived from a careful representation of the entities on the side of the patient which form the ultimate truthmakers for clinical statements. We address a challenge to this realist approach relating to the diagnosis of malaria, and show how this challenge can be resolved by appeal to Basic Formal Ontology (BFO) and to the Ontology for General Medical Science (OGMS) constructed in its terms
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
Ontology as the core discipline of biomedical informatics: Legacies of the past and recommendations for the future direction of research
The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources â for example pertaining to genes and proteins, drugs and diseases â secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable
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
Aboutness: Towards Foundations for the Information Artifact Ontology
The Information Artifact Ontology (IAO) was created to serve as a domainâneutral resource for the representation of types of information content entities (ICEs) such as documents, dataâbases, and digital imâages. We identify a series of problems with the current version of the IAO and suggest solutions designed to advance our understanding of the relations between ICEs and associated cognitive representations in the minds of human subjects. This requires embedding IAO in a larger framework of ontologies, including most importantly the Mental Funcâtioning Ontology (MFO). It also requires a careful treatment of the aboutness relations between ICEs and associated cognitive representaâtions and their targets in reality, which implies in turn a new treatment of the relation of truthmaking
Foundation for the Electronic Health Record: An ontological analysis of the HL7 Reference Information Model
Despite the recent advances in information and communication technology that have
increased our ability to store and circulate information, the task remains of ensuring that the right sorts of information reach the right sorts of people. In what follows we defend the thesis that efforts to develop efficient means for sharing information across healthcare systems and organizations would benefit from a careful analysis of human action in healthcare organizations, and that the communication of healthcare information and knowledge needs to rest on a sound ontology of social interaction. We illustrate this thesis in relation to the HL7 RIM, which is one centrally important tool for communication in the healthcare domain
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
Ontology and medical terminology: Why description logics are not enough
Ontology is currently perceived as the solution of first resort for all problems related to biomedical terminology, and the use of description logics is seen as a minimal requirement on adequate ontology-based systems. Contrary to common conceptions, however, description logics alone are not able to prevent incorrect representations; this is because they do not come with a theory indicating what is computed by using them, just as classical arithmetic does not tell us anything about the entities that are added or subtracted. In this paper we shall show that ontology is indeed an essential part of any solution to the problems of medical terminology â but only if it is understood in the right sort of way. Ontological engineering, we shall argue, should in every case go hand in hand with a sound ontological theory
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
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