The OGMS ontology draws on:
Richard H. Scheuermann, Werner Ceusters, and Barry
Smith, “Toward
an Ontological Treatment of Disease and Diagnosis”, Proceedings of the 2009
AMIA Summit on Translational Bioinformatics, 2009, 116-120.
Many existing biomedical vocabulary standards rest on incomplete,
inconsistent or confused accounts of basic terms pertaining to diseases,
diagnoses, and clinical phenotypes. Here we outline what we believe to be a
logically and biologically coherent framework for the representation of such
entities and of the relations between them. We defend a view of disease as
involving in every case some physical basis within the organism that bears a
disposition toward the execution of pathological processes. We present our view
in the form of a list of terms and definitions designed to provide a consistent
starting point for the representation of both disease and diagnosis in
information systems in the future.
This paper in turn draws on the following:
Cornelius Rosse, Anand Kumar, Jose LV Mejino Jr, Daniel L
Cook, Landon T Detwiler and Barry Smith,
“A
Strategy for Improving and Integrating Biomedical Ontologies”,
Proceedings of AMIA Symposium 2005, Washington DC, 639–643.
The integration of biomedical terminologies is indispensable to the process
of information integration. When terminologies are linked merely through the
alignment of their leaf terms, however, differences in context and ontological
structure are ignored. Making use of the SNAP and SPAN ontologies, we show how
three reference domain ontologies can be integrated at a higher level, through
what we shall call the OBR framework (for: Ontology of Biomedical Reality). OBR
is designed to facilitate inference across the boundaries of domain ontologies
in anatomy, physiology and pathology.
Barry Smith, Werner
Ceusters, Anand Kumar and Cornelius Rosse, “On
Carcinomas and Other Pathological Entities”, Comparative and Functional
Genomics,
2005:6(7);
379-387.
Tumors, abscesses, cysts, scars, fractures are familiar types of what we
shall call pathological continuant entities. The instances of such types exist
always in or on anatomical structures, which thereby become transformed into
pathological anatomical structures of corresponding types: a fractured tibia, a
blistered thumb, a carcinomatous colon. In previous work on biomedical
ontologies we showed how the provision of formal definitions for relations such
as is_a, part_of and transformation_of can facilitate the integration of such
ontologies in ways which have the potential to support new kinds of automated
reasoning. We here extend this approach to the treatment of pathologies,
focusing especially on those pathological continuant entities which arise when
organs become affected by carcinomas.
Includes a revised and
corrected
classification of biomedical entities.
Anand Kumar, Yum Lina Yip, Barry Smith, Pierre
Grenon, “Bridging
the Gap between Medical and Bioinformatics: An Ontological Case Study in Colon
Carcinoma”,Computers in Biology and Medicine, 2006; 36, (7-8):
694-711.
Ontological principles are needed in order to bridge the gap between medical and
biological information in a robust and computable fashion. This is essential in
order to draw inferences across the levels of granularity which span medicine
and biology, an example of which include the understanding of the roles of tumor
markers in the development and progress of carcinoma. Such information
integration is also important for the integration of genomics information with
the information contained in the electronic patient records in such a way that
real time conclusions can be drawn. In this paper we describe a large
multi-granular datasource built by using ontological principles and focusing on
the case of colon carcinoma.
Anand Kumar and Barry Smith, “Oncology
Ontology in the NCI Thesaurus”, AIME
2005 (Artificial Intelligence
in Medicine Europe),
(Lecture Notes in Computer Science 3581), 213–220.
The National Cancer Institute’s Thesaurus (NCIT) has been created with the goal
of providing a controlled vocabulary which can be used by specialists in the
various sub-domains of oncology. It is intended to be used for purposes of
annotation in ways designed to ensure the integration of data and information
deriving from these various sub-domains, and thus to support more powerful
cross-domain inferences. In order to evaluate its suitability for this purpose,
we examined the NCIT’s treatment of the kinds of entities which are fundamental
to an ontology of
colon carcinoma. We here describe the problems we uncovered concerning
classification, synonymy, relations and definitions, and we draw conclusions for
the work needed to establish the NCIT as a
referenceontology for the cancer domain in the future.
Anand Kumar, Y. Lina Yip, Barry Smith, Dirk
Marwede, Daniel Novotny, “An
Ontology for Carcinoma Classification for Clinical Bioinformatics”, Medical
Informatics Europe (MIE
2005), Geneva,
635–640.
There are a number of existing classifications and staging schemes for
carcinomas, one of the most frequently used being the TNM classification. Such
classifications represent classes of entities which exist at various anatomical
levels of granularity. We argue that in order to apply such representations to
the Electronic Health Records one needs sound ontologies which take into
consideration the diversity of the domains which are involved in clinical
bioinformatics. Here we outline a formal theory for addressing these issues in a
way that the ontologies can be used to support inferences relating to entities
which exist at different anatomical levels of granularity. Our case study is the
colon carcinoma, one of the most common carcinomas prevalent within the European
population.