To cite package sos4R in publications use:

Nüst D, Stasch C, Pebesma EJ (2011). “Connecting R to the Sensor Web.” In Geertman S, Reinhardt W, Toppen F (eds.), Advancing Geoinformation Science for a Changing World, series Proceedings of AGILE, 227 - 246. doi: 10.1007/978-3-642-19789-5_12.

Corresponding BibTeX entry:

    author = {Daniel Nüst and Christoph Stasch and Edzer J. Pebesma},
    title = {Connecting R to the Sensor Web},
    booktitle = {Advancing Geoinformation Science for a Changing
    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
    doi = {10.1007/978-3-642-19789-5_12},
    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.},