Connecting R to the Sensor Web

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.

[1]  Gary N. Geller,et al.  Looking forward: Applying an ecological model web to assess impacts of climate change , 2008 .

[2]  Edzer Pebesma,et al.  Applied Spatial Data Analysis with R. Springer , 2008 .

[3]  Sean R. Davis,et al.  GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor , 2007, Bioinform..

[4]  Ashlee Vance,et al.  Data Analysts Captivated by R's Power , 2009 .

[5]  George Percivall,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007 .

[6]  Sergey Fomel,et al.  Guest Editors' Introduction: Reproducible Research , 2009, Comput. Sci. Eng..

[7]  Ricardo Quirós,et al.  gvSOS: A New Client for the OGC® Sensor Observation Service Interface Standard , 2009 .

[8]  GeoCENS: Geospatial Cyberinfrastructure for Environmental Sensing , 2010 .

[9]  Donald E. Knuth,et al.  Literate Programming , 1984, Comput. J..

[10]  John Davidson,et al.  Ogc® sensor web enablement:overview and high level achhitecture. , 2007, 2007 IEEE Autotestcon.

[11]  Friedrich Leisch,et al.  Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis , 2002, COMPSTAT.

[12]  Edzer J. Pebesma,et al.  Applied Spatial Data Analysis with R - Second Edition , 2008, Use R!.

[13]  Duncan Temple Lang.  The Omegahat Environment: New Possibilities for Statistical Computing , 2000 .

[14]  Christoph Stasch,et al.  Discovery Mechanisms for the Sensor Web , 2009, Sensors.

[15]  Roger D. Peng,et al.  Caching and Distributing Statistical Analyses in R , 2008 .