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September 28, 2011

EIM 2011 - Sensors and Workflows

Sensors and Workflows Session

Lifemapper, VisTrails and EML: Documented, Re-executable Species Distribution Models - CJ Grady et al
- archive of species distribution models
- opensource
- REST and OGC (web mapping) services.

- Use IPCC and GBIF data for inputs
- Process metadata -
- Use EML for describing models
- Two papers:

Repeatability and transparency in ecological research
Analytic webs support the synthesis of ecological data sets

Sensor lifecycle management using scientific workflows - Barseghian et al.

- Kepler software - schedule workflows, sensor data analysis
- Opensource, Java
- versioning and documentation tool

- 3 components
- Field (SPAN, Data logger), Server (Data Turbine, Kepler, MetaCat), Desktop (Kepler)
- Sensor configuration from desktop to logger/sensor

This was linked at the end but I'm not sure why:
- REAP (Realtime Environment for Analytical Processing) "is an NSF-funded cyberinfrastructure development project, focused on creating technology in which scientific workflows tools can be used to access, monitor, analyze and present information"

Archiving Sensor Data - Applied to Dam Safety Information - Barateiro et al.

SHAMAN project - information management system (workflow system)

Obligatory random website reference: TIMBUS - manage acquisition dependencies

Acronym checks
- OAIS reference model
- Business Process Execution Language (BPEL)

Coral sensor network at Racha Island, Thailand - Jaroensutasinee et al.

- Impetus was largescale bleaching in 2010
- CREON project
- Met Station, Conductivity, Under water camera -> Data Turbine
- Historical NOAA data for the area show water temperature surface temp showing extreme peaks
- No bleaching events post-monitoring

- Acronym check:
AIMS (Australian Institute for Marine Sciences)

Moving from Custom Scripts with Extensive Instructions to a Workflow System: Use of the Kepler Workflow Engine in Environmental Information Management - Gries and Porter

- Use of workflow system for basic information management application (i.e., data manipulation, QA/QC)

1. Scripting language (e.g., python, php)
2. Programs with scripting (.e.g, R)
3. Workflow systems: Kepler, Taverna, Triana, VisTrails, Pegasus, BPEL

Chose Kepler because of packaged code/functions, documentation
Workflow at NTL -
Data file -> Format conversions and QA/QC -> parse into database
Sensor Data -> Data Turbine -> QA/QC ->

- Efficiently link scripts from different sources
- Large learning curve, very large data sets

Provenance and Quality Control in Sensor Networks - Lerner et al

Problem - sensor data has time gaps so use modeled values, need to identify modeled data

Use Little JIL for provenance tracking
- Exception handling is strong point
- Stage vs workflow oriented - either better explanation or more intuitive
- Data Derivation Graph (DDG) - articulates different QC procedures embarked upon based on original data (i.e., in range, out of range, NA)

Stream gage case study
- 15 min averages of stream characteristics, taken off data logger manually
- Move towards wireless, telemetry, automated QA/QC

Posted by kkwaiser at September 28, 2011 11:26 AM

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