Protein data sources management using semantics

Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need t...

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Main Authors: Sidhu, Amandeep, Dillon, Tharam S., Chang, Elizabeth
Format: Conference Paper
Published: Springer-Verlag 2006
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/18761
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author Sidhu, Amandeep
Dillon, Tharam S.
Chang, Elizabeth
author_facet Sidhu, Amandeep
Dillon, Tharam S.
Chang, Elizabeth
author_sort Sidhu, Amandeep
building Curtin Institutional Repository
collection Online Access
description Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need to be vigilant in monitoring the state of competitiveness of their platforms. In the technology post-adoption period, healthcare organizations use multiple data sources to search for technology-related information to maintain technology parity with, or dominance over their competitors. Firstly this study seeks to answer the following research question: what approaches do healthcare organizations employ with regard to managing diverse sources of data and information in order to sustain their technology competitiveness. Then as an initial step in this direction, in this paper we discuss the conceptual foundation for the phenomenon of data and information sources management capability for the proteomics domain. This is done by discussing the case of Protein Data Source Integration by Protein Ontology.
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institution Curtin University Malaysia
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publishDate 2006
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spelling curtin-20.500.11937-187612018-10-01T04:29:35Z Protein data sources management using semantics Sidhu, Amandeep Dillon, Tharam S. Chang, Elizabeth Data Semantics ontologird Data Integration Knowledge Management Information Retrieval Protein Ontology Biomedical Ontologies Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need to be vigilant in monitoring the state of competitiveness of their platforms. In the technology post-adoption period, healthcare organizations use multiple data sources to search for technology-related information to maintain technology parity with, or dominance over their competitors. Firstly this study seeks to answer the following research question: what approaches do healthcare organizations employ with regard to managing diverse sources of data and information in order to sustain their technology competitiveness. Then as an initial step in this direction, in this paper we discuss the conceptual foundation for the phenomenon of data and information sources management capability for the proteomics domain. This is done by discussing the case of Protein Data Source Integration by Protein Ontology. 2006 Conference Paper http://hdl.handle.net/20.500.11937/18761 10.1007/11836025_57 Springer-Verlag restricted
spellingShingle Data Semantics
ontologird
Data Integration
Knowledge Management
Information Retrieval
Protein Ontology
Biomedical Ontologies
Sidhu, Amandeep
Dillon, Tharam S.
Chang, Elizabeth
Protein data sources management using semantics
title Protein data sources management using semantics
title_full Protein data sources management using semantics
title_fullStr Protein data sources management using semantics
title_full_unstemmed Protein data sources management using semantics
title_short Protein data sources management using semantics
title_sort protein data sources management using semantics
topic Data Semantics
ontologird
Data Integration
Knowledge Management
Information Retrieval
Protein Ontology
Biomedical Ontologies
url http://hdl.handle.net/20.500.11937/18761