Managing complex change in clinical study metadata.
In highly functional metadata-driven software, the interrelationships within the metadata become complex, and maintenance becomes challenging. We describe an approach to metadata management that uses a knowledge-base subschema to store centralized information about metadata dependencies and use cases involving specific types of metadata modification. Our system borrows ideas from production-rule systems in that some of this information is a high-level specification that is interpreted and executed dynamically by a middleware engine. Our approach is implemented in TrialDB, a generic clinical study data management system. We review approaches that have been used for metadata management in other contexts and describe the features, capabilities, and limitations of our system.
Brandt
Cynthia A
CA
Center for Medical Informatics, Yale School of Medicine, New Haven, CT 06520-8009, USA. cynthia.brandt@yale.edu
Gadagkar
Rohit
R
Rodriguez
Cesar
C
Nadkarni
Prakash M
PM
D001185:Artificial Intelligence; D003199:Computer Systems; D003628:Database Management Systems; D020000:Decision Support Systems, Clinical; D010865:Pilot Projects; D012984:Software; D018875:Vocabulary, Controlled