Presentation on theme: "E-Science Data Information and Knowledge Transformation Thoughts on Education and Training for E-Science Based on edikt project experience Dr. Denise Ecklund."— Presentation transcript:
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
www.edikt.org Agenda Background – the edikt project Whats 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
e-Science Data Information and Knowledge Transformation The EDIKT Project E-Science Data, Information and Knowledge Transformation
www.edikt.org Edikt and its mission Research Interests RAE Study new CS theories in data management Study data mgmt problems in astronomy, physics, biology and geosciences Match?
e-Science Data Information and Knowledge Transformation A Model for an e-Science Research Project
www.edikt.org E-Science project staffing The team Principal Investigator Theoretical Scientist Computational Scientist Computing Engineer The goal is to do new application science. An important, but supporting role
www.edikt.org Computer SW engineering domain Application science domain Complimentary knowledge Conversational and shared understanding Education and training are required
e-Science Data Information and Knowledge Transformation Tasks of a Computing Engineer in an e-science research project working with people working with machines
www.edikt.org System development process Four phase process Gather requirements Investigate solutions Integrate components Deploy & maintain
www.edikt.org Working with people Phase 1 activities –Gather requirements Understand enough of the science application –Answer questions and exchange information Intelligibly Interact with team members having varying levels of computer expertise Gather requirements
www.edikt.org Working with machines Phase 2 - activities –Survey, identify and evaluate existing applicable software technologies Understand the requirements Effective search (where and how) Install and evaluate potential solutions Gather requirements Investigate solutions
www.edikt.org Working with machines Phase 3 - activities –Provide an integrated software solution Identify technology gaps Develop reliable software to fill the gaps Test and deploy full system Gather requirements Investigate solutions Integrate components
www.edikt.org Working with machines and people Phase 4 - activities –Maintain and evolve the integrated solution Basic systems support activities –Instruct team members on software usage Gather requirements Investigate solutions Integrate components Deploy & maintain
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 Systems work: operating systems networking compilers embedded systems Graphics Computational logic Programming skills SW engring methods Database programming Scripting languages Data structures Algorithms Artificial Intelligence work: language processing vision systems human-computer interaction robotics knowledge systems Algorithmic complexity HL systems work: middleware service-oriented architectures distributed & parallel systems database systems Basic Principles for everyone Specialisation Applicable skills for e-science?
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
e-Science Data Information and Knowledge Transformation Filling the Gaps My wish-list
www.edikt.org Technical knowledge gap Requirement –The projects 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 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 Bio-research Centre Project BProject A
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 Cant 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 Development Tools Methods and proven tools Spiral approach Extreme programming
www.edikt.org The making of an e-Science engineer CS + + + Domain knowledge (just one) Broad fundamentals Rigorous SW development methods Internship in a real e-science project = E-Science Computing Engineer
e-Science Data Information and Knowledge Transformation Thank you Thoughts and questions?