Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis

Derik Barseghian, Ilkay Altintas, Matthew B. Jones, Daniel Crawl, Nathan Potter, James Gallagher, Peter Cornillon, Mark Schildhauer, Elizabeth T. Borer, Eric W. Seabloom, Parviez R. Hosseini

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)42-50
Number of pages9
JournalEcological Informatics
Volume5
Issue number1
DOIs
StatePublished - Jan 2010

Bibliographical note

Funding 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.

Keywords

  • Data analysis
  • Near real-time data access
  • Oceanography
  • Scientific workflows
  • Sensors
  • Terrestrial ecology

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