Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis
Document Type
Article
Date of Original Version
1-1-2010
Abstract
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. © 2009 Elsevier B.V. All rights reserved.
Publication Title, e.g., Journal
Ecological Informatics
Volume
5
Issue
1
Citation/Publisher Attribution
Barseghian, Derik, Ilkay Altintas, Matthew B. Jones, Daniel Crawl, Nathan Potter, James Gallagher, Peter Cornillon, Mark Schildhauer, Elizabeth T. Borer, Eric W. Seabloom, and Parviez R. Hosseini. "Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis." Ecological Informatics 5, 1 (2010). doi: 10.1016/j.ecoinf.2009.08.008.