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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 transformation system...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335467/ https://www.ncbi.nlm.nih.gov/pubmed/25750622 http://dx.doi.org/10.3389/fninf.2015.00001 |
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author | Ashish, Naveen Toga, Arthur W. |
author_facet | Ashish, Naveen Toga, Arthur W. |
author_sort | Ashish, Naveen |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4335467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-43354672015-03-06 Medical data transformation using rewriting Ashish, Naveen Toga, Arthur W. Front Neuroinform Neuroscience 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. Frontiers Media S.A. 2015-02-20 /pmc/articles/PMC4335467/ /pubmed/25750622 http://dx.doi.org/10.3389/fninf.2015.00001 Text en Copyright © 2015 Ashish and Toga. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Ashish, Naveen Toga, Arthur W. Medical data transformation using rewriting |
title | Medical data transformation using rewriting |
title_full | Medical data transformation using rewriting |
title_fullStr | Medical data transformation using rewriting |
title_full_unstemmed | Medical data transformation using rewriting |
title_short | Medical data transformation using rewriting |
title_sort | medical data transformation using rewriting |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335467/ https://www.ncbi.nlm.nih.gov/pubmed/25750622 http://dx.doi.org/10.3389/fninf.2015.00001 |
work_keys_str_mv | AT ashishnaveen medicaldatatransformationusingrewriting AT togaarthurw medicaldatatransformationusingrewriting |