Connecting R to the Sensor Web

  • Daniel NüstEmail author
  • Christoph Stasch
  • Edzer Pebesma
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC, volume 1)


data exchange and reproducibility are increasingly important for modern scientific research. This paper shows how three open source projects work together to realize this: (i) the R project, providing the lingua franca for statistical analysis, (ii) the Open Geospatial Consortium's Sensor Observation Service (SOS), a standardized data warehouse service for storing and retrieving sensor measurements, and (iii) sos4R, a new project that connects the former two. We show how sos4R can bridge the gap between two communities in science: spatial statistical analysis and visualization on one side and the Sensor Web community on the other. sos4R enables R users to integrate (near real-time) sensor observations directly into R. Finally, we evaluate the functionality of sos4R. The software encapsulates the service's complexity with typical R function calls in a common analysis workflow, but still gives users full flexibility to handle interoperability issues. We conclude that it is able to close the gap between R and the sensor web.


Open Source Project Open Geospatial Consortium Sensor Observation Geography Markup Language Core Operation 
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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  1. 52°North - Initiative for Geospatial Open Source Software (2010) https://-, Last date accessed 2010-10-20.Google Scholar
  2. Arel-Bundock, V. (2010) WDI: Search and download data from the World Bank’s World Development Indicators’,
  3. Bivand, R. S. Pebesma, E. J. (2008), Applied spatial data analysis with R, Springer, NY,
  4. Botts, M. (2007) OGC Implementation Specification 07-000: OpenGIS Sensor Model Language (SensorML), Technical Report, Open Geospatial Consortium.Google Scholar
  5. Botts, M., Percivall, G., Reed, C. and Davidson, J. (2008) OGC Sensor Web Enablement: Overview and High Level Architecture, in S. Nittel, A. Labrinidis and A. Stefanidis (Eds.), GeoSensor Networks, Vol. 4540 of Lecture Notes in Computer Science, Springer Berlin / Heidelberg, pp. 175–190. 10.1007/978-3-540-79996-2_10.
  6. Cox, S. (2007a) OGC Implementation Specification 07-022r1: Observations and Measurements - Part 1 - Observation schema, Technical Report, Open Geospatial Consortium.Google Scholar
  7. Cox, S. (2007b) OGC Implementation Specification 07-022r3: Observations and Measurements - Part 2 - Sampling Features, Technical Report, Open Geospatial Consortium.Google Scholar
  8. Davis, S. and Meltzer, P. S. (2007) GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor, Bioinformatics 23(14), pp. 1846–1847, 10.1093/bioinformatics/btm254.
  9. Fomel, S. and Claerbout, J. F. (2009) Guest editors’ introduction: Reproducible Research, Computing in Science and Engineering 11, pp. 5–7.Google Scholar
  10. Freeman, E., Freeman, E., Bates, B. and Sierra, K. (2004) Head First Design Patterns, O’Reilly Media,
  11. Geller, Gary N., M. F. (2008) Looking Forward: Applying an Ecological ModelWeb to assess impacts of climate change, Biodiversity 9(3&4).Google Scholar
  12. Genolini, C. (2008), A (Not So) Short Introduction to S4’,
  13. Jirka, S., Bröring, A. and Stasch, C. (2009), Discovery Mechanisms for the Sensor Web, Sensors 9, 2661–2681,
  14. Keitt, T. H., Bivand, R., Pebesma, E. and Rowlingson, B. (2010) rgdal: Bindings for the Geospatial Data Abstraction Library,
  15. Knuth, D. E. (1984) Literate Programming, The Computer Journal 27, pp. 97–111.Google Scholar
  16. Leisch, F. (2005) Sweave: Dynamic Generation of Statistical Reports Using Liter-GeoCENS: Geospatial Cyberinfrastructure for Environmental Sensing, Extended Abstracts for Presentation at GIScience 2010.
  17. Na, A., Priest, M., Niedzwiadek, H. and Davidson, J. (2007) OGC Implementation Specification 06-009r6: Sensor Observation Service, Technical Report, Open Geospatial Consortium.Google Scholar
  18. Peng, R. D. (2008), Caching and Distributing Statistical Analyses in R, Journal of Statistical Software 26(7),
  19. Portele, C. (2003), OpenGIS Geography Markup Language (GML) Encoding Standard 07-036, Open Geospatial Consortium.Google Scholar
  20. R Development Core Team (2010), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0,
  21. Reproducible Research Planet (2010)., Last date accessed 2011-01-03.
  22. Ryan, J. A. (2008), Quantitative Financial Modelling & Trading Framework for R,, Last date accessed 2011-01-01.
  23. Tamayo, A., Huerta, J., Granell, C., Diaz, L. and Quiros, R. (2009), ‘gvSOS: A New Client for the OGC Sensor Observation Service Interface Standard, Transactions in GIS 13, pp. 47–61. Google Scholar
  24. Temple Lang, D. (2000) The Omegahat Environment: New Possibilities for Statistical Computing, Journal of Computational and Graphical Statistics 9, pp. 423–451,
  25. Temple Lang, D. (2007), R as a Web Client – the RCurl package, Journal of Statistical Software,
  26. Lang, D. (2010) XML: Tools for parsing and generating XML within R and Splus’,
  27. Vance, A. (2009) Data Analysts Captivated by R’s Power, http://www.nytimes. com/2009/01/07/technology/business-computing/07program.html, Last date accessed 2010-10-20.
  28. Vretanos, P. A. (2005) OpenGIS Filter Encoding Implementation Specification 04-095, Technical Report, Open Geospatial Consortium.Google Scholar
  29. Whiteside, A. (2007), OGC Implementation Specification 06-121r3: OGC Web Services Common Specification, Technical Report, Open Geospatial Consortium. for the Geospatial Data Abstraction Library, http://CRAN.R

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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Institute for GeoinformaticsUniversity of MuensterMuensterGermany

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