To cite package sos4R in publications use:

Nüst, D. 2010. sos4R: An R client for the OGC Sensor Observation Service. http://www.nordholmen.net/sos4r/.
Nüst, D., Stasch, C. and Pebesma, E. J. Connecting R to the Sensor Web in Geertman, S.; Reinhardt, W. and Toppen, F. (Eds.) Advancing Geoinformation Science for a Changing World, Springer Lecture Notes in Geoinformation and Cartography, 2011, 227 - 246

Corresponding BibTeX entries:

  @Misc{,
    author = {Daniel Nüst},
    title = {{sos4R: An R client for the OGC Sensor Observation
      Service}},
    year = {2010},
    url = {http://www.nordholmen.net/sos4r/},
  }
  @InProceedings{,
    author = {Daniel Nüst and Christoph Stasch and Edzer J. Pebesma},
    title = {Connecting R to the Sensor Web},
    booktitle = {Advancing Geoinformation Science for a Changing
      World},
    year = {2011},
    editor = {Stan Geertman and Wolfgang Reinhardt and Fred Toppen},
    series = {Proceedings of AGILE},
    pages = {227 - 246},
    publisher = {Springer Lecture Notes in Geoinformation and
      Cartography},
    abstract = {Interoperable 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.},
  }