Summary
Objectives: There exists a communication gap between the biomedical informatics community on
one side and the computer science/artificial intelligence community on the other side
regarding the meaning of the terms “semantic integration" and “knowledge representation“.
This gap leads to approaches that attempt to provide one-to-one mappings between data
elements and biomedical ontologies. Our aim is to clarify the representational differences
between traditional data management and semantic-web-based data management by providing
use cases of clinical data and clinical research data re-representation. We discuss
how and why one-to-one mappings limit the advantages of using Semantic Web Technologies
(SWTs).
Methods: We employ commonly used SWTs, such as Resource Description Framework (RDF) and Ontology
Web Language (OWL). We reuse pre-existing ontologies and ensure shared ontological
commitment by selecting ontologies from a framework that fosters community-driven
collaborative ontology development for biomedicine following the same set of principles.
Results: We demonstrate the results of providing SWT-compliant re-representation of data
elements from two independent projects managing clinical data and clinical research
data. Our results show how one-to-one mappings would hinder the exploitation of the
advantages provided by using SWT.
Conclusions: We conclude that SWT-compliant re-representation is an indispensable step, if using
the full potential of SWT is the goal. Rather than providing one-to-one mappings,
developers should provide documentation that links data elements to graph structures
to specify the re-representation.
Keywords
Semantic Web - artificial intelligence - knowledge management - common data model
