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spatial@linkedscience – Exploring the Research Field of GIScience with Linked Da...

 3 years ago
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spatial@linkedscience – Exploring the Research Field of GIScience with Linked Data

  • Carsten Keßler
  • Krzysztof Janowicz
  • Tomi Kauppinen
  • Carsten Keßler
  • Krzysztof Janowicz
  • Tomi Kauppinen
  1. 1.Institute for GeoinformaticsUniversity of MünsterGermany
  2. 2.Department of GeographyUniversity of CaliforniaSanta BarbaraUSA
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7478)

Abstract

Metadata for scientific publications contain various explicit and implicit spatio-temporal references. Data on conference locations as well as author and editor affiliations – both changing over time – enable insights into the geographic distribution of scientific fields and particular specializations. At the same time, these byproducts of scientific bibliographies offer a great opportunity to integrate data across different bibliographies to get a more complete picture of a domain. In this paper, we demonstrate how the Linked Data paradigm can assist in enriching and integrating such collections. Starting from the bibliographies of the GIScience, COSIT, ACM GIS, and AGILE conference series, we show how to convert the data to Linked Data and integrate the previously separate datasets. We focus on the spatio-temporal aspects and discuss how they help in matching and disambiguating entities such as authors or universities. We introduce a novel user interface to explore the integrated dataset, demonstrating the potential of Linked Data for innovative applications using spatio-temporal information, and discuss how more complex queries can be addressed. While we focus on bibliographies, the presented work is part of the broader vision of a Linked Science infrastructure for e-Science.

Keywords

Resource Description Framework Link Data Latent Dirichlet Allocation Conference Series Complex Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

About this paper

Cite this paper as: Keßler C., Janowicz K., Kauppinen T. (2012) spatial@linkedscience – Exploring the Research Field of GIScience with Linked Data. In: Xiao N., Kwan MP., Goodchild M.F., Shekhar S. (eds) Geographic Information Science. GIScience 2012. Lecture Notes in Computer Science, vol 7478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33024-7_8
  • DOI https://doi.org/10.1007/978-3-642-33024-7_8
  • Publisher Name Springer, Berlin, Heidelberg
  • Print ISBN 978-3-642-33023-0
  • Online ISBN 978-3-642-33024-7
  • eBook Packages Computer Science Computer Science (R0)

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