Transcript Fire Scenario, E-Science and Workflows

Scientific Workflows
for the Sensor Web
ICT for Earth Observation
Anwar Vahed
Topics
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The Sensor Web
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Scientific workflows
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Managing knowledge: The need for SW4SW
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SW4SW issues
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Representation & structure
 Frameworks & tools
Open questions
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September 2008 / 2
The promise of the
Sensor Web
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Data democracy: Improved ease of (controlled)
access to sensor data resources
Leverage sensor assets and integrate EO data with
domain data
Provide near real-time EO information, Alerts for
dynamic (transcient) phenomena
But will researchers use it?
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September 2008 / 4
Scientific Workflows
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“Traditional” workflows:
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Scientific workflows: (A cyber
research environment)
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Stateful and acyclic
Record and share knowledge
Stateless and cyclic
Generate knowledge
Learn
APIs and toolkits

Kepler, Taverna, Gridbus,...

Bioinformatics, Cheminformatics
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Build &
refine
Scientists
&
workflows
Record
& share
Run
September 2008 / 5
The Sensor Web Case
Bring the sensor web to the scientist:
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The Empirical Sensor Web: Open, distributed
environment for scientific exploration, knowledge
generation and management
An enabling environment that focus on science
questions, not data plumbing
Simplify complex processes for the domain scientist,
Automate repetitive tasks
Knowledge management: Public/private spaces for
knowledge storing, sharing
Adaptive architectures: Processing/Service & Data
Grids, self-organisation, learning workflows
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September 2008 / 6
A Scenario
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September 2008 / 7
Cholera research case
Research team of:

Microbiologists, Computer scientists, Statisticians, Mathematical
modellers, Remote sensing & GIS experts, Oceanographers,
Biochemists, Climatologists, Water & environmental ecologists
Wants to access data of:

Daily meteorological data (temp, rainfall and relative humidity)
from weather stations, satellite, sea surface temperature, insitu water temp, salinity, pH, nitrogen,… for sampling points
And use it in:

Statistical software, signal processing software, Mathematical
and computational intelligence software
To undertake:

Analysis, Data Mining, Monitoring, Modelling and simulation
To understand cholera better
www.meraka.org.za
September 2008 / 8
Cholera research
requirements
Integrated “debugging” environment (IDE) to
construct, automate/run/trace, reuse, nest,
parameterised workflows
Services and resources to support:
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(Standardized) access to sensory data of various forms
across internet
Tasking of sensors, steering of observations
Data provenance
Continuous monitoring and increased preparedness
Preprocessing and visualisation
Integration with non-EO data
These are not very different for other domains!
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September 2008 / 9
Questions (1/2)
How can we understand the needs of scientists when
working with Sensor Web resources, and how can these be
enabled by scientific workflows?
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What are appropriate formal representations for scientific
workflows for the purposes of their machine and human
manipulation in the Sensor Web?
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How can data and service (“soft”) resources be discovered
and acquired for utilisation in scientific workflows?
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How can computational and communication (“hard”)
resources be discovered and leveraged during execution of
a scientific workflow?

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September 2008 / 10
Questions (2/2)
To what extent can the quality of existing soft and hard
resources be determined and how can this information be
used to modify a workflow (a) before execution, (i.e.,
during composition), during execution (dynamically), and
after execution (workflow refinement)?
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How can scientific workflows be managed (stored, shared
and manipulated) to permit flexible levels of security (e.g.,
read, modify, execute) and accessibility (e.g., individual,
private, group, community, public spaces) in the Sensor
Web?
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How can scientific workflows be executed robustly in a
Sensor Web environment, where resource access and
quality are uncertain?
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September 2008 / 11
Inputs?
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September 2008 / 12