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

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Abstract

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.

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Notes

  1. www.gfbio.org

  2. www.idessa.org

  3. modis.gsfc.nasa.gov

  4. www.r-project.org

  5. geos.osgeo.org

  6. www.qgis.org

  7. earthengine.google.org

  8. species.mol.org

  9. www.postgis.net

  10. www.taverna.org.uk

  11. www.biodiversitycatalogue.org

  12. www.kepler-project.org

  13. www.dataone.org

  14. www.opengeospatial.org

  15. www.khronos.org/opencl

  16. www.vividsolutions.com/jts

  17. www.catsg.org

  18. ec.europa.eu/jrc/en/scientific-tool/global-land-cover

  19. www.gbif.org

  20. grass.osgeo.org

  21. pywps.wald.intevation.org

  22. github.com/geotrellis/geotrellis

  23. accumulo.apache.org

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Acknowledgement

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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Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany

    Christian Authmann, Christian Beilschmidt, Johannes Drönner, Michael Mattig & Bernhard Seeger

Authors
  1. Christian Authmann
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  2. Christian Beilschmidt
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  3. Johannes Drönner
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  4. Michael Mattig
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  5. Bernhard Seeger
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Corresponding author

Correspondence to Michael Mattig.

Additional information

This is an extended version of the paper “Rethinking Spatial Processing in Data-Intensive Science” [3] selected for the special DASP issue Best Workshop Papers of BTW 2015.

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Authmann, C., Beilschmidt, C., Drönner, J. et al. VAT: A System for Visualizing, Analyzing and Transforming Spatial Data in Science. Datenbank Spektrum 15, 175–184 (2015). https://doi.org/10.1007/s13222-015-0197-y

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  • DOI: https://doi.org/10.1007/s13222-015-0197-y

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