Medical data transformation using rewriting
This paper presents a system for declaratively transforming medical subjects' data into a common data model representation. Our work is part of the "GAAIN" project on Alzheimer's disease data federation across multiple data providers. We present a general purpose data transformat...
Saved in:
Published in | Frontiers in neuroinformatics Vol. 9; p. 1 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Research Foundation
20.02.2015
Frontiers Media S.A |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | This paper presents a system for declaratively transforming medical subjects' data into a common data model representation. Our work is part of the "GAAIN" project on Alzheimer's disease data federation across multiple data providers. We present a general purpose data transformation system that we have developed by leveraging the existing state-of-the-art in data integration and query rewriting. In this work we have further extended the current technology with new formalisms that facilitate expressing a broader range of data transformation tasks, plus new execution methodologies to ensure efficient data transformation for disease datasets. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Edited by: Richard A. Baldock, Medical Research Council Human Genetics Unit, UK Reviewed by: Natalya Kizilova, Kharkov National University, Ukraine; Albert Burger, Heriot-Watt University, UK This article was submitted to the journal Frontiers in Neuroinformatics. |
ISSN: | 1662-5196 1662-5196 |
DOI: | 10.3389/fninf.2015.00001 |