e-Science Data Information and Knowledge Transformation
Thoughts on Education and
Training for E-Science
Based on edikt project experience
Dr. Denise Ecklund
Technical Architect
Agenda
 Background – the edikt project
 What’s an “e-science research project”?
 Identify e-science engineering activities
 Derive educational requirements
– Hypothesise what is covered elsewhere
– Identify what is missing
 My wish-list for ‘gap fillers’
www.edikt.org
e-Science Data Information and Knowledge Transformation
The EDIKT Project
E-Science Data, Information
and Knowledge Transformation
Research Interests
RAE
Edikt and its mission
Study new
CS theories in
data management
Match?
Study data mgmt problems
in astronomy, physics,
biology and geosciences
www.edikt.org
e-Science Data Information and Knowledge Transformation
A Model for an e-Science
Research Project
E-Science project staffing
Principal
Investigator
Computational
Scientist
Computing
Engineer
Theoretical
Scientist
The team
The goal is to do new application science.
www.edikt.org
Complimentary knowledge
Application
science
domain
Conversational
and shared
understanding
Computer SW
engineering
domain
www.edikt.org
e-Science Data Information and Knowledge Transformation
Tasks of a Computing Engineer
in an e-science research project
working with people
working with machines
System development process
Gather
requirements
Investigate
solutions
Integrate
components
Deploy &
maintain
Four phase process
www.edikt.org
Working with people
 Phase 1 activities
– Gather requirements
Gather
requirements
 Understand ‘enough’ of the science application
– Answer questions and exchange information
 Intelligibly
Interact with team members
having varying levels
of computer expertise
www.edikt.org
Working with machines
 Phase 2 - activities
Gather
requirements
Investigate
solutions
– Survey, identify and evaluate existing
applicable software technologies
 Understand the requirements
 Effective search (where and how)
 Install and evaluate potential solutions
www.edikt.org
Working with machines
 Phase 3 - activities
Gather
requirements
Investigate
solutions
Integrate
components
– Provide an integrated software solution
 Identify technology gaps
 Develop reliable software to fill the gaps
 Test and deploy full system
www.edikt.org
Working with machines and people
Gather
requirements
Investigate
solutions
Integrate
components
Deploy &
maintain
 Phase 4 - activities
– Maintain and evolve the integrated solution
 Basic systems support activities
– Instruct team members on software usage
www.edikt.org
Job requirements for an
e-science computing engineer
 Technical capabilities
– Can work as the sole computer expert on the team
– Understand ‘enough’ vocabulary, concepts,
data use, structure of algorithms, and
domain-specific standards
– Capable of distributed systems analysis and design
– Knowledge and practice of rigorous software design
and development practices
 Then … the sociological factors
– Willingness to re-use existing technology
– Willingness to maintain and evolve the system
www.edikt.org
Structure of the CS curriculum
Basic Principles
for everyone
Computational logic
Programming skills
SW engring methods
Database programming
Scripting languages
Data structures
Algorithms
Specialisation
Systems work:
operating systems
networking
compilers
embedded systems
Graphics
HL systems work:
middleware
service-oriented architectures
distributed & parallel systems
database systems
Algorithmic complexity
Applicable skills
for e-science?
Artificial Intelligence work:
language processing
vision systems
human-computer interaction
robotics
knowledge systems
www.edikt.org
Assume a two part approach
 Leverage good Computer Science
curriculum
– Identify applicable areas of study
– Advise students to study across multiple
specialty areas
 Fill the gaps with e-science training
www.edikt.org
e-Science Data Information and Knowledge Transformation
Filling the Gaps
My wish-list
Technical knowledge gap
 Requirement
– The project’s primary expert on most
computer-related topics
 CS programme
– Teaches “independent work” and
“intra-project teamwork
 Teach ‘inter-project teamwork’
www.edikt.org
Inter-project teamwork
Bio-research Centre
Project A
Project B
 Share knowledge of similar tools and practices
– E.g., using same software development tools (CVS, JBuilder, Ant)
– A local person to talk with for a range of problems
www.edikt.org
Application domain gap
 Requirement
– Understands ‘enough’ vocabulary, concepts, data use,
structure of algorithms and domain-specific standards
 CS Programme
– Lab exercises are small examples in easy-to-grasp domains
 E-Science applications are not “easy-to-grasp”
– Advise students to study introductory domain-specific courses
– Develop lab exercises in e-science application domains
– Recommend a single domain focus
www.edikt.org
Domain focus
 Can’t wear all these hats and do it well – focus!
www.edikt.org
Search, identify and use gap
 Requirement
– Identify and re-use existing third party technologies
 CS Programme
– Traditional emphasis on building all new software
– Recently added exercises in “design re-use”
 Add lab exercises covering
– Re-use of pre-identified tools and components
– Find and select candidate technology for re-use
www.edikt.org
Software methodology gap
 Requirement
– Rigorous full life cycle software design and
development practices
 CS Programme
– Typically offer one course on software development
methodologies
– Students not required to ‘practice this’ after
software methodologies course
 Student interns in an active e-science project
– Mandatory use of software development
methodologies
www.edikt.org
Methods and proven tools
Spiral approach
Extreme programming
Development Tools
www.edikt.org
The making of an e-Science
engineer
+
CS
+
Broad
fundamentals
Rigorous SW
development
methods
+
Internship in a
real e-science project
=
E-Science Computing Engineer
Domain knowledge
(just one)
www.edikt.org
e-Science Data Information and Knowledge Transformation
Thank you
Thoughts and questions?