Article thumbnail

An ontologically founded architecture for information systems in clinical and epidemiological research

By Alexandr Uciteli, Silvia Groß, Sergej Kireyev and Heinrich Herre


This paper presents an ontologically founded basic architecture for information systems, which are intended to capture, represent, and maintain metadata for various domains of clinical and epidemiological research. Clinical trials exhibit an important basis for clinical research, and the accurate specification of metadata and their documentation and application in clinical and epidemiological study projects represents a significant expense in the project preparation and has a relevant impact on the value and quality of these studies

Topics: Proceedings
Publisher: BioMed Central
OAI identifier:
Provided by: PubMed Central

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

Suggested articles


  1. (1973). A: Foundations of Set Theory.
  2. (2007). Abstract vs. social roles — Towards a general theoretical account of roles. Applied Ontology
  3. Basic Formal Ontology
  4. (2011). Bundesministerium für Bildung und Forschung (BMBF). []. doi:10.1186/2041-1480-2-S4-S1 Cite this article as: Uciteli et al.: An ontologically founded architecture for information systems in clinical and epidemiological research.
  5. CDISC Clinical Research Glossary.
  6. (1983). Clinical Trials: A Practical Approach.
  7. Descriptive Ontology for Linguistic and Cognitive Engineering
  8. Domain-Specific Concepts and Ontological Reduction within a Data Dictionary Framework.
  9. (2010). Furberg CD, DeMets DL: Fundamentals of Clinical Trials.
  10. (2006). General Formal Ontology (GFO): A Foundational Ontology Integrating Objects and Processes. Part I: Basic Principles (Version 1.0). Research Group Ontologies in Medicine (Onto-Med),
  11. (2008). GFO-Bio: A biological core ontology. Applied Ontology
  12. (2006). Heller B: Semantic foundations of medical information systems based on top-level ontologies. KnowledgeBased Systems
  13. (1988). Individuality: an essay on the foundations of metaphysics. Albany: State university of New York press;
  14. (2010). Information technology — Metadata registries (MDR) — Part 3: Registry metamodel and basic attributes.
  15. International Organization for Standardization.
  16. ISO/IEC 24707: Information technology – Common Logic (CL): a framework for a family of logic-based languages.
  17. (1990). Keisler HJ: Model theory.
  18. (1999). Metaphysics and its task: the search for the categorial foundation of knowledge.
  19. (2008). Mundlos S: The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease.
  20. Ontology Language
  21. Ontology of Time and Situoids in Medical Conceptual Modeling.
  22. Phenotypic Quality Ontology
  23. (1976). Philosophische Untersuchungen zu Raum, Zeit und Kontinuum.
  24. (2010). Rebholz-Schuhmann D: Interoperability between phenotype and anatomy ontologies. Bioinformatics
  25. (2003). Sabatti C: The Human Phenome Project. Nature Genetics
  26. (1983). Situations and attitudes.
  27. Standardized Terminology for Clinical Trial Protocols Based on Ontological Top-Level Categories. In Computer-based Support for Clinical Guidelines and Protocols.
  28. (1979). SW: Clinical research in general medical journals: a 30-year perspective.
  29. (2011). T: Modeling surgical processes: A four-level translational approach. Artif Intell Med
  30. (2004). The Theory of Top-Level Ontological Mappings and its Application to Clinical Trial Protocols. In Engineering Knowledge in the Age of the Semantic Web:
  31. (2002). Towards Ontological Foundations for UML Conceptual Models.
  32. (1922). Tractatus logico-philosophicus.
  33. (1976). Über die Individualität und das Individuationsprinzip.
  34. (1997). What Exactly Are Genomes, Genotypes and Phenotypes? And What About Phenomes?
  35. Zentrum für Klinische Studien