, Volume 15, Issue 3, pp 175–184 | Cite as

VAT: A System for Visualizing, Analyzing and Transforming Spatial Data in Science

  • Christian Authmann
  • Christian Beilschmidt
  • Johannes Drönner
  • Michael Mattig
  • Bernhard Seeger


The amount of available data changes the style of research in geo-scientific domains, and thus influences the requirements for spatial processing systems. To support data-driven research and exploratory workflows, we propose the Visualization, Analysis & Transformation system (VAT). We first identify ten fundamental requirements, which span from supporting spatial data types over low latency computations to visualization techniques. Based on these we evaluate state-of-the-art systems from the domains of spatial frameworks, GIS, workflow systems, scientific databases and Big Data solutions. The goal of the VAT system is to overcome the identified limitations by a holistic approach to raster and vector data, demand-driven and tiled processing, and the efficient usage of heterogeneous hardware architectures. A first comparison with other systems shows the validity of our approach.


Geographic Information System Coordinate Reference System Raster Data Geographic Information System Application Resilient Distribute Dataset 
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.



This work has been supported by the Deutsche Forschungsgemeinschaft (DFG) under grant no. SE 553/7-1 (GFBio) and by the Bundesministerium für Bildung und Forschung (BMBF) under grant no. 01LL1301 (IDESSA).


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Christian Authmann
    • 1
  • Christian Beilschmidt
    • 1
  • Johannes Drönner
    • 1
  • Michael Mattig
    • 1
  • Bernhard Seeger
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of MarburgMarburgGermany

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