Environmental sensor networks are now commonly being deployed within environmental observatories and as components of smaller-scale ecological and environmental experiments. Effectively using data from these sensor networks presents technical challenges that are difficult for scientists to overcome, severely limiting the adoption of automated sensing technologies in environmental science. The Realtime Environment for Analytical Processing (REAP) is an NSF-funded project to address the technical challenges related to accessing and using heterogeneous sensor data from within the Kepler scientific workflow system. Using distinct use cases in terrestrial ecology and oceanography as motivating examples, we describe workflows and extensions to Kepler to stream and analyze data from observatory networks and archives. We focus on the use of two newly integrated data sources in Kepler: DataTurbine and OPeNDAP. Integrated access to both near real-time data streams and data archives from within Kepler facilitates both simple data exploration and sophisticated analysis and modeling with these data sources.
|Original language||English (US)|
|Number of pages||9|
|State||Published - Jan 2010|
Bibliographical noteFunding Information:
This material is based upon work supported by the National Science Foundation under award 0619060 for the REAP project, and by the National Center for Ecological Analysis and Synthesis , a Center funded by NSF (Grant # DEB-0553768 ), the University of California, Santa Barbara, and the State of California.
- Data analysis
- Near real-time data access
- Scientific workflows
- Terrestrial ecology