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Transactions on Large-Scale Data- and Knowledge-Centered Systems IV pp 40–72Cite as

MEDCollector: Multisource Epidemic Data Collector

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Part of the book series: Lecture Notes in Computer Science ((TLDKS,volume 6990))

Abstract

We present a novel approach for epidemic data collection and integration based on the principles of interoperability and modularity. Accurate and timely epidemic models require large, fresh datasets. The World Wide Web, due to its explosion in data availability, represents a valuable source for epidemiological datasets. From an e-science perspective, collected data can be shared across multiple applications to enable the creation of dynamic platforms to extract knowledge from these datasets. Our approach, MEDCollector, addresses this problem by enabling data collection from multiple sources and its upload to the repository of an epidemic research information platform. Enabling the flexible use and configuration of services through workflow definition, MEDCollector is adaptable to multiple Web sources. Identified disease and location entities are mapped to ontologies, not only guaranteeing the consistency within gathered datasets but also allowing the exploration of relations between the mapped entities. MEDCollector retrieves data from the web and enables its packaging for later use in epidemic modeling tools.

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Author information

Authors and Affiliations

  1. LaSIGE, Faculty of Science, University of Lisbon, Portugal

    João Zamite, Francisco Couto & Mário J. Silva

  2. Information Technology Division, Army Technology Center, Rio de Janeiro, Brazil

    Fabrício A. B. Silva

Authors
  1. João Zamite
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  2. Fabrício A. B. Silva
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  3. Francisco Couto
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  4. Mário J. Silva
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Editor information

Editors and Affiliations

  1. Institut de Recherche en Informatique de Toulouse (IRIT), Paul Sabatier University, 118, route de Narbonne, 31062, Toulouse Cedex, France

    Abdelkader Hameurlain

  2. University of Linz, FAW, Altenbergerstraße 69, 4040, Linz, Austria

    Josef Küng  & Roland Wagner  & 

  3. Department of Computer Science, Ludwig-Maximilians-Universität, Oettingenstrasse 67, 80538, München, Germany

    Christian Böhm

  4. Institut für Informatik-Systeme, Alpen Adria Universität Klagenfurt, Universitätsstr. 65, 9020, Klagenfurt, Austria

    Johann Eder

  5. Department of Scientific Computing, Florida State University, 400 Dirac Science Library, 32306-4120, Tallahassee, FL, USA

    Claudia Plant

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© 2011 Springer-Verlag Berlin Heidelberg

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Zamite, J., Silva, F.A.B., Couto, F., Silva, M.J. (2011). MEDCollector: Multisource Epidemic Data Collector. In: Hameurlain, A., Küng, J., Wagner, R., Böhm, C., Eder, J., Plant, C. (eds) Transactions on Large-Scale Data- and Knowledge-Centered Systems IV. Lecture Notes in Computer Science, vol 6990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23740-9_3

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  • DOI: https://doi.org/10.1007/978-3-642-23740-9_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23739-3

  • Online ISBN: 978-3-642-23740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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