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Web technologies for environmental big data

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Claudia Vitolo
  • Yehia Elkhatib
  • Dominik Reusser
  • Christopher J.A. Macleod
  • Wouter Buytaert
<mark>Journal publication date</mark>01/2015
<mark>Journal</mark>Environmental Modelling and Software
Number of pages14
Pages (from-to)185-198
Publication StatusPublished
Early online date31/10/14
<mark>Original language</mark>English


Recent evolutions in computing science and web technology provide the environmental community with continuously expanding resources for data collection and analysis that pose unprecedented challenges to the design of analysis methods, workflows, and interaction with data sets. In the light of the recent UK Research Council funded Environmental Virtual Observatory pilot project, this paper gives an overview of currently available implementations related to web-based technologies for processing large and heterogeneous datasets and discuss their relevance within the context of environmental data processing, simulation and prediction. We found that, the processing of the simple datasets used in the pilot proved to be relatively straightforward using a combination of R, RPy2, PyWPS and PostgreSQL. However, the use of NoSQL databases and more versatile frameworks such as OGC standard based implementations may provide a wider and more flexible set of features that particularly facilitate working with larger volumes and more heterogeneous data sources.

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Under a Creative Commons license