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Perspectives on Cyberinfrastructure

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

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Perspectives on Cyberinfrastructure

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

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

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

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

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

  11. Picture ofearthquakeand bridge Sensors More Diversity, New Devices, New Applications Personalized Medicine Picture ofdigital sky Wireless networks Knowledge from Data Instruments

  12. Cyberinfrastructure is a First-Class Tool for Science

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

  14. 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.

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