1. Perspectives on Cyberinfrastructure Daniel E. Atkins atkins@umich.edu Professor, University of Michigan School of Information & Dept. of EECS October 2002

2. (Cyber) infrastructure The term infrastructure has been used since the 1920’s to refer collectively to the roads, bridges, rail lines, and similar public works that are required for an industrial economy to function. The recent term cyberinfrastructure refers to an infrastructure based upon computer, information and communication technology (increasingly) required for discovery, dissemination, and preservation of knowledge. Traditional infrastructure is required for an industrial economy. Cyberinfrastructure is required for an information economy.

3. Cyberinfrastructure: the Middle Layer Base-technology: computation, storage, communication Cyberinfrastructure: hardware, software, personnel, services, institutions Applications in science and engineering research and education

4. 4 Trends & Issues Components  Circuit speed flattening in about 6 years, then most increase from improving chip density and massive parallelism. New technology curves?  Disk capacity increase 60-100% per year.  Networking: 1.6 Terabits/sec running in labs on a single fiber (40 channels at 40 gigabits/sec.). Ubiquitous wireless.

5. 5 Computational Diversity Capability not just capacity: technology, policy, tools. Still need some center-based leading- edge,super computers. On-demand supercomputing,not just batch.

6. 6 Content Digital everything; exponential growth; conversion and born-digital. S&E literature is digital. Microfilm-> digital for preservation. Digital libraries are real and getting better. Distributed (global scale), multi-media, multi- disciplinary observation. Huge volume. Need for large-scale, enduring, professionally managed/curated data repositories. New modes of scholarly communication emerging. IP, openness, ownership, privacy, security issues

7. Converging Streams of Activity GRIDS (broadly defined) E-science CI-enabled Science & Engineering Research & Education Science-driven pilots (not using above labels) ITFRU Scholarly communication in the digital age

9. National Petascale Systems National Petascale Systems Ubiquitous Sensor/actuator Networks Ubiquitous Sensor/actuator Networks Laboratory Terascale Systems Laboratory Terascale Systems Ubiquitous Infosphere Collaboratories Responsive Environments Responsive Environments Terabit Networks Contextual Awareness Contextual Awareness Smart Objects Smart Objects Building Out Building Up Science, Policy and Education Petabyte Archives Petabyte Archives Futures: The Computing Continuum

10. Components of CI-enabled science & engineering Collaboration Services Knowledge management institutions for collection building and curation of data, information, literature, digital objects High-performance computing for modeling, simulation, data processing/mining Individual & Group Interfaces & Visualization Physical World Humans Facilities for activation, manipulation and construction Instruments for observation and characterization. Global Connectivity A broad, systemic, strategic conceptualization

11. Community Planning Guidance Examples from Geosciences Consultation with environmental community leaders NSF - Nov. 19, 2001

12. Instruments Picture of digital sky Knowledge from Data Sensors Picture of earthquake and bridge Wireless networks Personalized Medicine More Diversity, New Devices, New Applications

13. Cyberinfrastructure is a First-Class Tool for Science

14. Network for Earthquake Engineering Simulation Field Equipment Laboratory Equipment Remote Users High- Performance Network(s) Instrumented Structures and Sites Leading Edge Computation Curated Data Repository Laboratory Equipment Global Connections

15. From Prime Minister Tony Blair’s Speech to the Royal Society (23 May 2002) What is particularly impressive is the way that scientists are now undaunted by important complex phenomena. Pulling together the massive power available from modern computers, the engineering capability to design and build enormously complex automated instruments to collect new data, with the weight of scientific understanding developed over the centuries, the frontiers of science have moved into a detailed understanding of complex phenomena ranging from the genome to our global climate. Predictive climate modelling covers the period to the end of this century and beyond, with our own Hadley Centre playing the leading role internationally. The emerging field of e-science should transform this kind of work. It's significant that the UK is the first country to develop a national e- science Grid, which intends to make access to computing power, scientific data repositories and experimental facilities as easy as the Web makes access to information. One of the pilot e-science projects is to develop a digital mammographic archive, together with an intelligent medical decision support system for breast cancer diagnosis and treatment. An individual hospital will not have supercomputing facilties, but through the Grid it could buy the time it needs. So the surgeon in the operating room will be able to pull up a high-resolution mammogram to identify exactly where the tumour can be found.