1. Introduction to e-Science
MIK 2.1 Databases and Networksystems
Guest lecture “e-science”
Silvia Delgado Olabarriaga
Bioinformatics Laboratory, KEBB

2. MIK 2.1 DBNS - introduction to e-science, 2013
HPC
workflow
cloud
… is coming to a theater
close to you!
analytics
grid
virtualization
HPC
…as service
Big data
hadoop
MIK 2.1 DBNS - introduction to e-science, 2013

3. MIK 2.1 DBNS - introduction to e-science, 2013
Example 1: Analytics
Analytics is the discovery and communication of meaningful patterns in data. It relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Courtesy of Wico Mulder, Alan Turing Institute, Almere
MIK 2.1 DBNS - introduction to e-science, 2013

4. MIK 2.1 DBNS - introduction to e-science, 2013
Example 2: Cloud
Network-based services which appear to be provided by real server hardware.
Several fundamental models: infrastructure as a service (IaaS), platform as a service (PaaS),
and software as a service (SaaS)
Medical Distributed Utilization of Services & Applications
Courtesy of Frank van der Linden, Philips
MIK 2.1 DBNS - introduction to e-science, 2013

5. Example 3: virtueel zorgplein
In 2016 staan de zorgverleners die een patiënt nodig heeft, aan een virtueel zorgplein: het AMC als tempel van topreferente en topklinische zorg, samen met collega-UMC’s, algemene ziekenhui- zen, huisartsen, thuiszorg, e-health, maar ook de orthopedische schoenmaker en de opticien. De agenda van de patiënt staat centraal.
Strategisch venster 2012 – 2016
een doorkijk op ICT in het AMC
MIK 2.1 DBNS - introduction to e-science, 2013

6. … but it is already here for
Background
HPC
workflow
… is coming to a theater
close to you!
cloud
analytics
grid
virtualization
HPC
… but it is already here for
scientific research!
…as service
Big data
hadoop
MIK 2.1 DBNS - introduction to e-science, 2013

7. MIK 2.1 DBNS - introduction to e-science, 2013
Goal
Introduce concepts of e-science and e-infrastructures
Raise awareness about new technologies used for development of distributed systems with large capacity
Get basic hands-on experience with a small set of such technologies
At the end of the day the audience will
Be familiar with terminology and concepts in e-science
Be familiar and have minimal experience with one workflow management system for distributed computing
Understand the relationship between ongoing developments in e-science and potential future developments in medical informatics.
MIK 2.1 DBNS - introduction to e-science, 2013

8. MIK 2.1 DBNS - introduction to e-science, 2013
Course Overview
Lectures
Introduction to e-Science
Practice
Introduction to WS-PGRADE
Exercises
Wrap-up
MIK 2.1 DBNS - introduction to e-science, 2013

9. Introduction to e-Science
Definition
Examples
Main concepts
Recap
MIK 2.1 DBNS - introduction to e-science, 2013

10. MIK 2.1 DBNS - introduction to e-science, 2013
Global collaborations in key areas of science and the next generation of infrastructure that will enable it
John Taylor, UK
2000
Enhanced
Enabled
e=?
MIK 2.1 DBNS - introduction to e-science, 2013

11. MIK 2.1 DBNS - introduction to e-science, 2013
Various “definitions..”
Science that uses immense data sets that require high performance computing, such as grids and supercomputers.
New methods based on the shared use of ICT tools and resources across different disciplines and technology domains.
Various initiatives
UK, Sweden, Netherlands,…
USA
Microsoft
“Big Science”
MIK 2.1 DBNS - introduction to e-science, 2013

12. Example 1: LHC Experiment
Large Hadron Collider, CERN
funded by and built in collaboration
with over 10,000 scientists and engineers,
over 100 countries, hundreds of universities and laboratories
The Higgs boson or Higgs particle is an elementary particle initially theorised in 1964, and tentatively confirmed to exist on 14 March 2013.
MIK 2.1 DBNS - introduction to e-science, 2013

13. Example 2: Human Genome Project
13 years ( )
3 billion DNA subunits (bases)
Data analysis continues today…
Nobel prize in
physiology or medicine for 2002:
Sydney Brenner,
John Sulston,
Robert Horvitz
MIK 2.1 DBNS - introduction to e-science, 2013

14. MIK 2.1 DBNS - introduction to e-science, 2013
e-Science exists in NL
MIK 2.1 DBNS - introduction to e-science, 2013

15. MIK 2.1 DBNS - introduction to e-science, 2013
Medical e-Science
MIK 2.1 DBNS - introduction to e-science, 2013

16. Common themes in translational research projects
Share the same basic design
Suffer from similar problems
Amount of data
No standard language
Islands of information
IT systems do not interoperate
Share infrastructure!
Thanks to slides by JW Boiten, TraIT
MIK 2.1 DBNS - introduction to e-science, 2013

17. The TraIT Data Infrastructure
Hospital (IT)
Translational Research (IT)
TTP
data domains
HIS
clinical
integrated data
translational research workspace
Open
Clinica
PACS
imaging
LIS
NBIA
e.g.
tranSMART
biobanking
Research (IT)
e.g. R
e.g. caTissue
LIMS
experiment
Public Data
Various
solutions …
Thanks to slides by JW Boiten, TraIT

18. e-Science is a research field
MIK 2.1 DBNS - introduction to e-science, 2013

19. e-Science Research Topics
Infrastructure
Management of data
Processing
User interfaces
Collaboration
MIK 2.1 DBNS - introduction to e-science, 2013

20. e-Science Topics: e-Infrastructure
Data
Processing
Network
Services
MIK 2.1 DBNS - introduction to e-science, 2013

21. MIK 2.1 DBNS - introduction to e-science, 2013
56 countries
347 resource centers
333,000 cores
235 PB disk
176 PB tape
1,565 million jobs/day
5.3 million CPU hours/day
MIK 2.1 DBNS - introduction to e-science, 2013

22. e-Science Topics: Data Management
Metadata
Data integration
Data lifecycle (archival, permanent referencing)
Semantic web
Provenance
MIK 2.1 DBNS - introduction to e-science, 2013

23. Databases integration
Nature Reviews Genetics 8, (March 2007)
MIK 2.1 DBNS - introduction to e-science, 2013

24. MIK 2.1 DBNS - introduction to e-science, 2013
Semantic Web
mesh of information linked up in such a way as to be easily processable by machines
LOD=linking Open Data
Status Sept 2011
MIK 2.1 DBNS - introduction to e-science, 2013

25. MIK 2.1 DBNS - introduction to e-science, 2013
Provenance
Traceability of the origin of data and findings
MIK 2.1 DBNS - introduction to e-science, 2013

26. e-Science Topics: Scientific Workflows
MIK 2.1 DBNS - introduction to e-science, 2013

27. e-science topics: User interfaces
Visualization
Science gateways or portals
MIK 2.1 DBNS - introduction to e-science, 2013

28. e-science topics: Collaboration
Development of eScience methods for drug discovery
MIK 2.1 DBNS - introduction to e-science, 2013

29. e-Science Research Topics
Infrastructure
Management of data
Processing
User interfaces
Collaboration
Mixture of
Informatics
Computational science
Bioinformatics
Medical informatics
And many other fields!
“e-science is the journey,
the destination is simply called “science”
David de Roure, UK
MIK 2.1 DBNS - introduction to e-science, 2013

30. MIK 2.1 DBNS - introduction to e-science, 2013
e-Science topics
MIK 2.1 DBNS - introduction to e-science, 2013

31. MIK 2.1 DBNS - introduction to e-science, 2013
Recap
New IT is coming closer to medical practice
New IT is already used in “Big science” e-Science
e-Science approach used for medical research
e-Science research topics
infrastructure
data management
distributed processing
user interfaces
collaboration
MIK 2.1 DBNS - introduction to e-science, 2013

32. Questions?