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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...

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Detalles Bibliográficos
Autores principales: Ashish, Naveen, Toga, Arthur W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
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.
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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
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