Software tools for data collection: microcomputer-assisted interviewing
Social Science Computer Review
Communications of the ACM
A very high level programming language for data processing applications
Communications of the ACM
Model-driven architecture for cancer research
SEFM '07 Proceedings of the Fifth IEEE International Conference on Software Engineering and Formal Methods
Model evolution and management
MBEERTS'07 Proceedings of the 2007 International Dagstuhl conference on Model-based engineering of embedded real-time systems
Form follows function: model-driven engineering for clinical trials
FHIES'11 Proceedings of the First international conference on Foundations of Health Informatics Engineering and Systems
Journal of Biomedical Informatics
Hi-index | 0.00 |
To make reliable, safe, and effective use of data outside the context of its collection, we require an adequate understanding of its meaning. In data-intensive science, as in many other applications of computing, this necessitates the association of each item of data with complex, detailed metadata. The most important, most useful piece of metadata is often a description of the form used in data acquisition. This paper discusses, with examples, the requirements for standard metamodels or languages for forms, sufficient for the automatic association of form data with a computable description of its semantics, and also for the automatic generation of form structures and completion workflows. It explains how form models in specific domains can be used to facilitate data sharing, and to improve data quality, and semantic interoperability.