Literature DB >> 12075666

Biological data integration: wrapping data and tools.

Zoé Lacroix1.   

Abstract

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web as well as data generated by software. We present an approach to wrapping web data sources, databases, flat files, or data generated by tools through a database view mechanism. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, second builds the expected output with respect to the virtual structure. Our wrappers are composed of a retrieval component based on an intermediate object view mechanism called search views mapping the source capabilities to attributes, and an eXtensible Markup Language (XML) engine, respectively, to perform these two tasks. The originality of the approach consists of: 1) a generic view mechanism to access seamlessly data sources with limited capabilities and 2) the ability to wrap data sources as well as the useful specific tools they may provide. Our approach has been developed and demonstrated as part of the multidatabase system supporting queries via uniform object protocol model (OPM) interfaces.

Mesh:

Year:  2002        PMID: 12075666     DOI: 10.1109/titb.2002.1006299

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  4 in total

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Journal:  J Hum Genet       Date:  2007-12-12       Impact factor: 3.172

2.  Dynamic integration of biological data sources using the data concierge.

Authors:  Peng Gong
Journal:  Health Inf Sci Syst       Date:  2013-02-04

3.  An XML standard for the dissemination of annotated 2D gel electrophoresis data complemented with mass spectrometry results.

Authors:  Romesh Stanislaus; Liu Hong Jiang; Martha Swartz; John Arthur; Jonas S Almeida
Journal:  BMC Bioinformatics       Date:  2004-01-29       Impact factor: 3.169

4.  A novel framework for horizontal and vertical data integration in cancer studies with application to survival time prediction models.

Authors:  Iliyan Mihaylov; Maciej Kańduła; Milko Krachunov; Dimitar Vassilev
Journal:  Biol Direct       Date:  2019-11-21       Impact factor: 4.540

  4 in total

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