The ACGT Master Ontology and its applications--towards an ontology-driven cancer research and management system.
OBJECTIVE
This paper introduces the objectives, methods and results of ontology development in the EU co-funded project Advancing Clinico-genomic Trials on Cancer-Open Grid Services for Improving Medical Knowledge Discovery (ACGT). While the available data in the life sciences has recently grown both in amount and quality, the full exploitation of it is being hindered by the use of different underlying technologies, coding systems, category schemes and reporting methods on the part of different research groups. The goal of the ACGT project is to contribute to the resolution of these problems by developing an ontology-driven, semantic grid services infrastructure that will enable efficient execution of discovery-driven scientific workflows in the context of multi-centric, post-genomic clinical trials. The focus of the present paper is the ACGT Master Ontology (MO).


METHODS
ACGT project researchers undertook a systematic review of existing domain and upper-level ontologies, as well as of existing ontology design software, implementation methods, and end-user interfaces. This included the careful study of best practices, design principles and evaluation methods for ontology design, maintenance, implementation, and versioning, as well as for use on the part of domain experts and clinicians.


RESULTS
To date, the results of the ACGT project include (i) the development of a master ontology (the ACGT-MO) based on clearly defined principles of ontology development and evaluation; (ii) the development of a technical infrastructure (the ACGT Platform) that implements the ACGT-MO utilizing independent tools, components and resources that have been developed based on open architectural standards, and which includes an application updating and evolving the ontology efficiently in response to end-user needs; and (iii) the development of an Ontology-based Trial Management Application (ObTiMA) that integrates the ACGT-MO into the design process of clinical trials in order to guarantee automatic semantic integration without the need to perform a separate mapping process.
Brochhausen
Mathias
M
Institute of Formal Ontology and Medical, Information Science, Saarland University, P.O. Box 15 11 50, 66041 Saarbrücken, Germany. mathias.brochhausen@ifomis.uni-saarland.de
Spear
Andrew D
AD
Cocos
Cristian
C
Weiler
Gabriele
G
Martín
Luis
L
Anguita
Alberto
A
Stenzhorn
Holger
H
Daskalaki
Evangelia
E
Schera
Fatima
F
Schwarz
Ulf
U
Sfakianakis
Stelios
S
Kiefer
Stephan
S
Dörr
Martin
M
Graf
Norbert
N
Tsiknakis
Manolis
M
D000818:Animals; D019295:Computational Biology; D003628:Database Management Systems; D016208:Databases, Factual; D006801:Humans; D008490:Medical Informatics; D008495:Medical Oncology; D009369:Neoplasms; D018875:Vocabulary, Controlled