1. Cyberinfrastructure for e-Education and e-Research (e-Science)
Cyberinfrastructure Days
New Mexico Highlands University
Las Vegas NM
March
Geoffrey Fox
Computer Science, Informatics, Physics
Pervasive Technology Laboratories
Indiana University Bloomington IN 47401

2. e-moreorlessanything
‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’ from inventor of term John Taylor Director General of Research Councils UK, Office of Science and Technology
e-Science is about developing tools and technologies that allow scientists to do ‘faster, better or different’ research
Similarly e-Business captures an emerging view of corporations as dynamic virtual organizations linking employees, customers and stakeholders across the world.
This generalizes to e-moreorlessanything including e-DigitalLibrary, e-NationalSecurity, e-HavingFun and e-Education
A deluge of data of unprecedented and inevitable size must be managed and understood.
People (virtual organizations), computers, data (including sensors and instruments) must be linked via hardware and software networks 2 2

3. Applications, Infrastructure, Technologies
This field is confused by inconsistent use of terminology; I define
Web Services, Grids and (aspects of) Web 2.0 (Enterprise 2.0) are technologies
Grids could be everything (Broad Grids implementing some sort of managed web) or reserved for specific architectures like OGSA or Web Services (Narrow Grids)
These technologies combine and compete to build electronic infrastructures termed e-infrastructure or Cyberinfrastructure
e-moreorlessanything is an emerging application area of broad importance that is hosted on the infrastructures e-infrastructure or Cyberinfrastructure
e-Science or perhaps better e-Research is a special case of e-moreorlessanything

4. What is Cyberinfrastructure
Cyberinfrastructure is (from NSF) infrastructure that supports distributed science (e-Science)– data, people, computers
Clearly core concept more general than Science
Exploits Internet technology (Web2.0) adding (via Grid technology) management, security, supercomputers etc.
It has two aspects: parallel – low latency (microseconds) between nodes and distributed – highish latency (milliseconds) between nodes
Parallel needed to get high performance on individual large simulations, data analysis etc.; must decompose problem
New Mexico Encanto supercomputer excellent parallel resource
Distributed aspect integrates already distinct components – especially natural for data 4 4

5. Underpinnings of Cyberinfrastructure
Distributed software systems are being “revolutionized” by developments from e-commerce, e-Science and the consumer Internet. There is rapid progress in technology families termed “Web services”, “Grids” and “Web 2.0”
The emerging distributed system picture is of distributed services with advertised interfaces but opaque implementations communicating by streams of messages over a variety of protocols
Complete systems are built by combining either services or predefined/pre-existing collections of services together to achieve new capabilities
As well as Internet/Communication revolutions (distributed systems), multicore chips will likely be hugely important (parallel systems)

6. Virtual Observatory Astronomy Grid Integrate Experiments
Radio
Far-Infrared
Visible
Dust Map
Visible + X-ray
Galaxy Density Map

7. Example: Setting up a Polar CI-Grid
The North and South poles are melting with potential huge environmental impact
As a result of MSI meetings, I am working with MSI ECSU in North Carolina and Kansas University to design and set up a Polar Grid (Cyberinfrastructure)
This is a network of computers, sensors (on robots and satellites), data and people aimed at understanding science of ice-sheets and impact of global warming
We have changed the 100,000 year Glacier cycle into a ~50 year cycle; the field has increased dramatically in importance and interest
Good area to get involved in as not so much established work

9. Computing and Cyberinfrastructure: TeraGrid
TeraGrid resources include more than 250 teraflops of computing capability and more than 30 petabytes of online and archival data storage, with rapid access and retrieval over high-performance networks. TeraGrid is coordinated at the University of Chicago, working with the Resource Provider sites: Indiana University, Oak Ridge National Laboratory, National Center for Supercomputing Applications, Pittsburgh Supercomputing Center, Purdue University, San Diego Supercomputer Center, Texas Advanced Computing Center, University of Chicago/Argonne National Laboratory, and the National Center for Atmospheric Research.
Grid Infrastructure Group (UChicago) UW
UC/ANL
PSC
NCAR PU
NCSA IU
UNC/RENCI
Caltech
ORNL
USC/ISI
SDSC
TACC
Resource Provider (RP)
Software Integration Partner
Computing and Cyberinfrastructure: TeraGrid

10. Large Hadron Collider CERN, Geneva: 2008 Start
pp s =14 TeV L=1034 cm-2 s-1
27 km Tunnel in Switzerland & France
CMS
TOTEM
pp, general purpose; HI
Physicists
250+ Institutes
60+ Countries
Atlas
ALICE : HI
LHCb: B-physics
Higgs, SUSY, Extra Dimensions, CP Violation, QG Plasma, … the Unexpected
Challenges: Analyze petabytes of complex data cooperatively Harness global computing, data & network resources

11. Environmental Monitoring Sensor Grid at Clemson

12. Sensor Grids Can be Fun
Note sensors are any time dependent source of information and a fixed source of information is just a broken sensor
SAR Satellites
Environmental Monitors
Nokia N800 pocket computers
RFID tags and readers
GPS Sensors
Lego Robots
RSS Feeds
Audio/video: web-cams
Presentation of teacher in distance education
Text chats of students

13. The Sensors on the Fun Grid
Laptop for PowerPoint
2 Robots used
Lego Robot GPS Nokia N RFID Tag RFID Reader

14. Data from the Robot RFID Sensors
Data from GPS geolocates other sensors
Sensor Data from Lego Light
sensor plus videocams from N800 carried as payload on Lego
RFID Reader sees many tags

15. BIRN Bioinformatics Research Network

16. The People in Cyberinfrastructure
Web 2.0 can enhance scientific collaboration, i.e. effectively support virtual organizations, in different ways from grids
I expect more resources like MyExperiment from UK, SciVee from SDSC and Connotea from Nature that offer Flickr, YouTube, Facebook, Second Life type capabilities optimized for science
The usability and participatory nature of Web 2.0 can bring science and its informatics to a broader audience
In particular distance collaborative aspects of such Cyberinfrastructure can level playing field; you do not have to be at Harvard etc. to succeed
e.g. ECSU in CReSIS NSF Science and Technology Center
Navajo Tech can access TeraGrid Science Gateways

17. SciVee: Share videos etc.
Connotea: Share links/comments
All have tags

18. MSI-CIEC Web 2.0 Research Matching Portal
Portal supporting tagging and linkage of Cyberinfrastructure Resources
NSF (soon other agencies) Solicitations and Awards
MSI-CIEC Portal Homepage
Feeds such as SciVee and NSF
Researchers on NSF Awards
User and Friends
TeraGrid Allocations
Search Results
Search for linked people, grants etc.
Could also be used to support matching of students and faculty for REUs etc.
MSI-CIEC Portal Homepage
Search Results

20. The social process of science 2.0
Virtual Learning Environment
Undergraduate Students
Digital Libraries
scientists
Graduate Students
Technical Reports
Reprints
Peer-Reviewed Journal & Conference Papers
Preprints & Metadata
experimentation
Local Web
Repositories
Certified Experimental Results & Analyses
Data, Metadata Provenance Workflows Ontologies

21. Data and Cyberinfrastructure
DIKW: Data  Information  Knowledge  Wisdom transformation
Applies to e-Science, Distributed Business Enterprise (including outsourcing), Military Command and Control and general decision support
(SOAP or just RSS) messages transport information expressed in a semantically rich fashion between sources and services that enhance and transform information so that complete system provides
Semantic Web technologies like RDF and OWL might help us to have rich expressivity but they might be too complicated
We are meant to build application specific information management/transformation systems for each domain
Each domain has Specific Services/Standards (for API’s and Information such as KML and GML for Geographical Information Systems)
and will use Generic Services (like R for datamining) and
Generic Standards (such as RDF, WSDL)
Standards made before consensus or not observant of technology progress are dubious

22. Information and Cyberinfrastructure
Raw Data  Data  Information  Knowledge  Wisdom  Decisions
Another Grid
Another Grid SS SS SS SS SS
Filter
Service fs
Discovery Cloud
Portal
Filter Cloud
Filter Cloud
Inter-Service Messages
Another Service
Filter
Service fs
Filter Cloud
Filter
Service fs
Discovery Cloud
Filter
Service fs
Filter Cloud
Traditional Grid with exposed services
Filter Cloud
Filter Cloud
Another Grid SS SS SS SS
Sensor or Data
Interchange
Service SS SS SS SS SS SS SS
Compute Cloud
Storage Cloud
Database

23. APEC Cooperation for Earthquake Simulation
ACES is a eight year-long collaboration among scientists interested in earthquake and tsunami predication
iSERVO is Infrastructure to support work of ACES
SERVOGrid is (completed) US Grid that is a prototype of iSERVO
Chartered under APEC – the Asia Pacific Economic Cooperation of 21 economies

24. Repositories Federated Databases
Sensors
Streaming Data
Field Trip Data
Database
Database
Sensor Grid
Database Grid
Research
Education
SERVOGrid ?
Discovery
Services
GIS Grid
Compute Grid
Customization
Services
From Research to Education
Data Filter Services
Research Simulations
Analysis and Visualization Portal
Education Grid
Computer
Farm
Grid of Grids: Research Grid and Education Grid

25. Grid Workflow Datamining in Earth Science
Work with Scripps Institute
Grid services controlled by workflow process real time data from ~70 GPS Sensors in Southern California
Streaming Data
Support
Transformations
Data Checking
Hidden Markov Datamining (JPL)
Display (GIS)
NASA GPS
Real Time
Archival
Earthquake 25 25

26. Grid Workflow Data Assimilation in Earth Science
Grid services triggered by abnormal events and controlled by workflow process real time data from radar and high resolution simulations for tornado forecasts
Typical graphical interface to service composition