Cyberinfrastructure Vision

for 21st Century Discovery

National Science Foundation

Cyberinfrastructure Council

March 2007
Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

About the Cover

The visualization on the cover depicts a single cycle of 

delay measurements made by a CAIDA Internet performance monitor. The graph was created using the Walrus 

graph visualization tool, designed for interactively visualizing large directed graphs in 3-Dimensional space. For 

more information: http://www.caida.org/tools/visualization/walrus/
Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

Dr. Arden L. Bement, Jr. , Director of National Science Foundation

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Dear Colleague:

I am pleased to present NSF’s Cyberinfrastructure 

Vision for 21st Century Discovery. This document, 

developed in consultation with the wider science, 

engineering, and education communities, lays out 

an evolving vision that will help to guide the Foundation’s future investments in cyberinfrastructure. 

At the heart of the cyberinfrastructure vision 

is the development of a cultural community that 

supports peer-to-peer collaboration and new modes 

of education based upon broad and open access to 

leadership computing; data and information resources; online instruments and observatories; and 

visualization and collaboration services. Cyberinfrastructure enables distributed knowledge communities that collaborate and communicate across disciplines, distances and cultures. These research and 

education communities extend beyond traditional 

brick-and-mortar facilities, becoming virtual organizations that transcend geographic and institutional 

boundaries. This vision is new, exciting and bold.

Realizing the cyberinfrastructure vision described in this document will require 

the broad participation and collaboration of individuals from all fields and institutions, and across the entire spectrum of education. It will require leveraging resources 

through multiple and diverse partnerships among academia, industry and government. 

An important challenge is to develop the leadership to move the vision forward in 

anticipation of a comprehensive cyberinfrastructure that will strengthen innovation, 

economic growth and education. 

 Sincerely,

 Arden L. Bement, Jr.

 Director

Letter From the Director
Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

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The National Science Foundation’s Cyberinfrastructure Council (CIC)1, based on extensive input from 

the research community, has developed a comprehensive vision to guide the Foundation’s future investments in cyberinfrastructure (CI). In 2005, four multi-disciplinary, cross-foundational teams were created 

and charged with drafting a vision for cyberinfrastructure in four overlapping and complementary areas: 

1) High Performance Computing, 2) Data, Data Analysis, and Visualization, 3) Cyber Services and Virtual Organizations, and 4) Learning and Workforce Development. Draft versions of the document were 

posted on the NSF website and public comments were solicited from the community. These drafts were 

also reviewed for comment by the National Science Board. The National Science Foundation thanks all 

of those who provided feedback on the Cyberinfrastructure Vision for 21st Century Discovery document. 

Your comments were carefully reviewed and considered during preparation of this version of the document, which is intended to be a living document, and will be updated periodically. 

We acknowledge the following NSF personnel who served on the strategic planning teams and whose 

efforts made this document possible. We especially acknowledge Deborah Crawford, who served as acting 

director for OCI from July 2005 to June 2006, and whose leadership was instrumental in the formulation 

of this document. 

High Performance Computing (HPC) CI Team: Deborah Crawford (Chair), Leland Jameson, Margaret 

Leinen (CIC Representative), José Muñoz, Stephen Meacham, Michael Plesniak

Data CI Team: Cheryl Eavey, James French, Christopher Greer, David Lightfoot (CIC Representative), 

Elizabeth Lyons, Fillia Makedon, Daniel Newlon, Nigel Sharp, Sylvia Spengler (Chair)

Virtual Organizations (VO) CI Team: Thomas Baerwald, Elizabeth Blood, Charles Boudin, Arthur 

Goldstein, Joy Pauschke (Co-Chair), Randal Ruchti, Bonnie Thompson, Kevin Thompson (Co-Chair), 

Michael Turner (CIC Representative)

Learning and Workforce Development (LWD) CI Team: James Collins (CIC Representative), Janice 

Cuny, Semahat Demir, Lloyd Douglas, Debasish Dutta (Chair), Miriam Heller, Sally O’Connor, Michael 

Smith, Harold Stolberg, Lee Zia

1

 Complete list of acronyms can be found in Appendix A. 

Acknowledgements

Preface
Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

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letter from the director . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Acknowledgements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

 Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1 Call to Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

	 Cyberinfrastructure Drivers and Opportunities . . . . . . . . . . . . . . . . . . . . . 5

	 Vision, Mission and Principles for Cyberinfrastructure. . . . . . . . . . . . . . . . . 6

	 Goals and Strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

	 Planning for Cyberinfrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2 High Performance Computing (2006-2010) . . . . . . . . . . . . . . . . . . 13

	 What Does High Performance Computing Offer Science and Engineering? . . . . . . 13

	 The Next Five Years: Creating a High Performance Computing Environment

	 	 for Petascale Science and Engineering. . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3 Data, Data Analysis, and Visualization (2006-2010). . . . . . . . . . . . . . 21

	 A Wealth of Scientific Opportunities Afforded by Digital Data. . . . . . . . . . . . . 21

	 	 Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

	 Developing a Coherent Data Cyberinfrastructure in a Complex Global Context. . . 23

	 The Next Five Years: Towards a National Digital Data Framework. . . . . . . . . . . . 24

4 Virtual Organizations for Distributed Communities (2006-2010) . . . . . 31

	 New Frontiers in Science and Engineering Through Networked Resources and

	 	 Virtual Organizations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

	 The Next Five Years: Establishing a Flexible, Open Cyberinfrastructure

	 	 Framework for Virtual Organizations. . . . . . . . . . . . . . . . . . . . . . . . . . 32

5 Learning and Workforce Development (2006-2010) . . . . . . . . . . . . . .37

	 Cyberinfrastructure and Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

	 Building Capacity for Creation and Use of Cyberinfrastructure . . . . . . . . . . . 37

	 Using Cyberinfrastructure to Enhance Learning . . . . . . . . . . . . . . . . . . . . . 39

	 The Next Five Years: Learning About and With Cyberinfrastructure. . . . . . . . . . 39

Appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43

	 	 Acronyms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

	 Representative Reports and Workshops. . . . . . . . . . . . . . . . . . . . . . . . . . . 45

	 Chronology of NSF Information Technology Investments. . . . . . . . . . . . . . . . 48

	 Management of Cyberinfrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

	 Representative Distributed Research Communities (Virtual Organizations). . . . . . 50

Image Credits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Table of Contents

I.

II.

III.

IV.

I.

II.

I.

II.

III.

IV.

I.

II.

I.

II.

III.

IV.

A.

B.

C.

D.

E.

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National Science Foundation Cyberinfrastructure Vision

for 21st Century Discovery March 2007

NSF’s Cyberinfrastructure Vision for 21st 

Century Discovery is presented in a set of interrelated chapters that describe the various challenges 

and opportunities in the complementary areas that 

make up cyberinfrastructure: computing systems, 

data, information resources, networking, digitally 

enabled-sensors, instruments, virtual organizations, and observatories, along with an interoperable suite of software services and tools. This 

technology is complemented by the interdisciplinary teams of professionals that are responsible for 

its development, deployment and its use in transformative approaches to scientific and engineering 

discovery and learning. The vision also includes 

attention to the educational and workforce initiatives necessary for both the creation and effective 

use of cyberinfrastructure.

The five chapters of this document set out 

NSF’s cyberinfrastructure vision. The first, A Call 

for Action, presents NSF’s vision and commitment to a cyberinfrastructure initiative. NSF will 

play a leadership role in the development and 

support of a comprehensive cyberinfrastructure 

essential to 21st century advances in science and 

engineering research and education. The vision focuses on a time frame of 2006-2010. The mission 

is for cyberinfrastructure to be human-centered, 

world-class, supportive of broadened participation in science and engineering, sustainable, and 

stable but extensible. The guiding principles are 

that investments will be science-driven, recognize 

the uniqueness of NSF’s role, provide for inclusive 

strategic planning, enable U.S. leadership in science and engineering, promote partnerships and 

integration with investments made by others in all 

sectors, both national and international, and rely 

on strong merit review and on-going assessment, 

and a collaborative governance culture. This chapter goes on to review a set of more specific goals 

and strategies for NSF’s cyberinfrastructure initiative along with brief descriptions of the strategy to 

achieve those goals.

High Performance Computing (HPC) in support of modeling, simulation, and extraction of 

knowledge from huge data collections is increasingly essential to a broad range of scientific and 

engineering disciplines, often multi-disciplinary 

(e.g. physics, biology, medicine, chemistry, cosmology, computer science, mathematics), as well 

as multi-scalar in dimensions of space (e.g., nanometers to light-years) time (e.g., picoseconds1

 to 

billions of years), and complexity. A vision for 

petascale2

 science and engineering for the academic community, enabled by high performance 

computing, is presented along with a series of 

principles that would be used to guide NSF science-driven HPC investments. This would result 

in a sustained petascale capable system deployed 

in the FY 2010 timeframe. The plan presented 

addresses HPC acquisition and deployment and 

various aspects of HPC software and tools, in 

addition to the necessary scalable applications that 

would execute on these HPC assets.

An effective computing environment designed 

to meet the computational needs of a range of 

science and engineering applications will include a 

variety of computing systems with complementary 

performance capabilities. NSF will invest in leadership class environments in the 0.5-10 petascale 

performance range. Strong partnerships involving other federal agencies, universities, industry 

and state government are also critical to success. 

NSF will also promote resource sharing between 

and among academic institutions to optimize the 

accessibility and use of HPC assets deployed and 

supported at the campus level. Supporting software services include the provision of intelligent 

development and problem-solving environments 

and tools. These tools are designed to provide improvements in ease of use, reusability of modules, 

and portable performance.

Executive Summary

1 A picosecond is 10-12 second 2 A petascale is 1015 operations per second with 

comparable storage and networking capacity

The image shows computed charge density for iron oxide (FeO) within the local density approximation, with 

spherical ions subtracted. The colors represent the spin density, showing the antiferromagnetic ordering.
Cyberinfrastructure Vision

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National Science Foundation March 2007

Researchers create cyberenvironments—secure, easy-to-use interfaces to instruments, data, computing systems, networks, 

applications, analysis and visualization tools, and services. 

Data, Data Analysis, and Visualization are 

vital for progress in the increasingly data-intensive 

realm of science and engineering research and 

education. Any cogent plan addressing cyberinfrastructure must address the phenomenal growth of 

data in all its various dimensions. Scientists and 

engineers are producing, accessing, analyzing, integrating, storing and retrieving massive amounts 

of data daily. Further, this is a trend that is 

expected to see significant growth in the very near 

future as advances in sensors and sensor networks, 

high-throughput technologies and instrumentation, automated data acquisition, computational 

modeling and simulation, and other methods and 

technologies materialize. The anticipated growth 

in both the production and repurposing of digital 

data raises complex issues not only of scale and 

heterogeneity, but also of stewardship, curation 

and long-term access.

Responding to the challenges and opportunities 

of a data-intensive world, NSF will pursue a vision in which science and engineering digital data 

are routinely deposited in well-documented form, 

are regularly and easily consulted and analyzed 

by specialist and non-specialist alike, are openly 

accessible while suitably protected, and are reliably 

preserved. To realize this vision, NSF’s goals for 

2006-2010 are twofold: to catalyze the development of a system of science and engineering data 

collections that is open, extensible, and evolvable; 

and to support development of a new generation 

of tools and services for data discovery, integration, visualization, analysis and preservation. The 

resulting national digital data framework will be 

an integral component in the national cyberinfrastructure framework. It will consist of a range 

of data collections and managing organizations, 

networked together in a flexible technical architecture using standard, open protocols and interfaces, 

and designed to contribute to the emerging global 

information commons. It will be simultaneously 

local, regional, national and global in nature, and 

will evolve as science and engineering research and 

education needs change and as new science and 

engineering opportunities arise. 

Virtual Organizations for Distributed Communities, built upon cyberinfrastructure, enable 

science and engineering communities to pursue 

their research and learning goals with dramatically 

relaxed constraints of time and distance. A virtual 

organization is created by a group of individuals 

whose members and resources may be dispersed 

geographically and/or temporally, yet who function as a coherent unit through the use of end-toend cyberinfrastructure systems. These CI systems 

provide shared access to centralized or distributed 
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National Science Foundation March 2007

resources and services, often in real-time. Such 

virtual organizations supporting distributed communities go by numerous names: collaboratory, 

co-laboratory, grid community, science gateway, 

science portal, and others. As such environments 

become more and more functionally complete 

they offer new organizations for discovery and 

learning and bold new opportunities for broadened participation in science and engineering.

Creating and sustaining effective virtual 

organizations, especially those spanning many 

traditional organizations, is a complex technical 

and social challenge. It requires an open technological framework consisting of, for example, 

applications, tools, middleware, remote access to 

experimental facilities, instruments and sensors, 

as well as monitoring and post-analysis capabilities. An operational framework from campus level 

to international scale is required, as well as a need 

for partnerships between the various cyberinfrastructure stakeholders. Overall effectiveness also 

depends upon the appropriate social, governance, 

legal, economic and incentive structures. Formative and longitudinal evaluation is also necessary both to inform iterative design as well as to 

develop understanding of the impact of virtual 

organizations on enhancing the effectiveness of 

discovery and learning.

Learning and Workforce Development opportunities and requirements recognize that the 

ubiquitous and interconnected nature of cyberinfrastructure will change not only how we teach but 

also how we learn. The future will see increasingly open access to online educational resources 

including courseware, knowledge repositories, 

laboratories, and collaboration tools. Collaboratories or science gateways (instances of virtual 

organizations) created by research communities 

will also offer participation in authentic inquirybased learning. These new modes and opportunities to learn and to teach, covering K-12, postsecondary, the workforce and the general public, 

come with their own set of opportunities and 

challenges. New assessment techniques will have 

to be developed and understood; undergraduate 

curricula must be reinvented to fully exploit the 

capabilities made possible by cyberinfrastructure; 

and the education of the professionals that are 

being relied upon to support, develop and deploy 

future generations of cyberinfrastructure must be 

addressed. In addition, cyberinfrastructure will 

have an impact on how business will be conducted 

and members of the workforce must have the 

capability to fully exploit the benefits afforded by 

these new technologies.

Cyberinfrastructure-enhanced discovery and 

learning is especially exciting because of the opportunities it affords for broadened participation 

and wider diversity along individual, geographical 

and institutional dimensions. To fully realize these 

opportunities NSF will identify and address the 

barriers to utilization of cyberinfrastructure tools, 

services, and resources; promote the training of 

faculty, educators, students, researchers and the 

public; and encourage programs that will explore 

and exploit cyberinfrastructure, including taking 

advantage of the international connectivity it 

provides - particularly important as we prepare a 

globally engaged workforce.

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National Science Foundation March 2007

I. Cyberinfrastructure Drivers and 

Opportunities

How does a protein fold? What happens to 

space-time when two black holes collide? What 

impact does species gene flow have on an ecological community? What are the key factors that 

drive climate change? Did one of the trillions of 

collisions at the Large Hadron Collider produce a 

Higgs boson, the dark matter particle, or a black 

hole? Can we create an individualized model of 

each human being for personalized health care 

delivery? How does major technological change 

affect human behavior and structure complex social relationships? What answers will we find – to 

questions we have yet to ask – in the very large 

data­sets that are being produced by telescopes, 

sensor networks, and other experimental facilities?

These questions – and many others – are only 

now coming within our ability to answer because 

of advances in computing and related information technology. Once used by a handful of elite 

researchers in a few research communities on 

select problems, advanced computing has become 

essential to future progress across the frontier of 

science and engineering. Coupled with continuing improvements in microprocessor speeds, 

converging advances in networking, software, visualization, data systems and collaboration platforms 

are changing the way research and education are 

accomplished. 

Today’s scientists and engineers need access to 

new information technology capabilities, such as 

distributed wired and wireless observing network 

complexes, and sophisticated simulation tools 

that permit exploration of phenomena that can 

never be observed or replicated by experiment. 

Computation offers new models of behavior and 

modes of scientific discovery that greatly extend 

the limited range of models that can be produced 

with mathematics alone – for example, chaotic 

behavior. Fewer and fewer researchers working 

at the frontiers of knowledge can carry out their 

work without cyberinfrastructure of one form or 

another.

While hardware performance has been growing 

exponentially – with gate density doubling every 

18 months, storage capacity every 12 months, 

and network capability every 9 months – it has 

become clear that increasingly capable hardware is 

not the only requirement for computation-enabled 

discovery. Sophisticated software, visualization 

tools, middleware and scientific applications created and used by interdisciplinary teams are critical to turning flops, bytes and bits into scientific 

breakthroughs. In addition to these technical 

needs, the exploration of new organizational models and the creation of enabling policies, processes, 

and economic frameworks are also essential. The 

combined power of these capabilities and approaches is necessary to advance the frontiers of 

science and engineering, make seemingly intractable problems solvable, and pose profound new 

scientific questions. 

The comprehensive infrastructure needed to 

capitalize on dramatic advances in information 

technology has been termed cyberinfrastructure 

(CI). Cyberinfrastructure integrates hardware for 

computing, data and networks, digitally-enabled 

sensors, observatories and experimental facilities, 

and an interoperable suite of software and middleware services and tools. Investments in interdisciplinary teams and cyberinfrastructure professionals 

with expertise in algorithm development, system 

operations, and applications development are 

also essential to exploit the full power of cyberinfrastructure to create, disseminate, and preserve 

scientific data, information and knowledge. 

For four decades, NSF has provided leadership in the scientific revolution made possible 

by information technology (Appendices B and 

C). Through investments ranging from supercomputing centers and the Internet to software 

and algorithm development, information techThe Terashake 2.1 simulation on the opposite page depicts a velocity wavefield as it propagates through the 3D 

velocity structure beneath Southern California. Red and yellow colors indicate regions of compression, while 

blue and green colors show regions of dilation. Faint yellow (faults), red (roads), and blue (coast-line) lines add 

geographical context.

CHAPTER 1 

Call to Action
Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

nology has stimulated scientific breakthroughs 

across all science and engineering fields. Most 

recently, NSF’s Information Technology Research 

(ITR) priority area sowed the seeds of broad and 

intensive collaboration among the computational, 

computer, and domain research communities that 

sets the stage for this “Call to Action.” 

NSF is the only agency within the U.S. government that funds research and education across all 

disciplines of science and engineering. Over the 

past five years, NSF has held community workshops, commissioned blue-ribbon panels, and carried out extensive internal planning (Appendix B). 

Thus, it is strategically placed to leverage, coordinate and transition cyberinfrastructure advances in 

one field to all fields of research. 

Other federal agencies, the administration, 

Congress, the private sector, and other nations are 

aware of the growing importance of cyberinfrastructure to progress in science and engineering. 

Other federal agencies have planned improved 

capabilities for specific disciplines, and in some 

cases to address interdisciplinary challenges. 

Other countries have also been making significant 

progress in scientific cyberinfrastructure. Thus, 

the U.S. must engage in and actively benefit from 

cyberinfrastructure developments around the 

world.

Not only is the time ripe for a coordinated 

investment in cyberinfrastructure, but progress at 

the science and engineering frontiers depends on 

it. Our communities are in place and are poised 

to respond to such an investment.

Working with the science and engineering research and education communities and partnering 

with other key stakeholders, NSF is ready to lead.

II. Vision, Mission and Principles for 

Cyberinfrastructure

 A. Vision

NSF will play a leadership role in the development and support of a comprehensive cyberinfrastructure essential to 21st century advances 

in science and engineering research and education.

B. Mission

NSF’s mission for cyberinfrastructure (CI) is to:

Develop a human-centered CI that is driven by 

science and engineering research and education 

opportunities;

Provide the science and engineering communities with access to world-class CI tools 

and services, including those focused on: high 

performance computing; data, data analysis 

and visualization; networked resources and virtual organizations; and learning and workforce 

development;

Promote a CI that serves as an agent for 

broadening participation and strengthening the 

nation’s workforce in all areas of science and 

engineering;

Provide a sustainable CI that is secure, efficient, 

reliable, accessible, usable, and interoperable, 

and that evolves as an essential national infrastructure for conducting science and engineering research and education; and

Create a stable but extensible CI environment 

that enables the research and education communities to contribute to the agency’s statutory 

mission.

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•

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Visualization of a molecular dynamics simulation of a double stranded 

DNA molecule as it enters a nanopore in a silicon nitride membrane.

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Cyberinfrastructure Vision

for 21st Century Discovery National Science Foundation March 2007

C. Principles

 The following principles will guide the agency’s 

FY 2006 through FY 2010 investments:

Science and engineering research and education are foundational drivers of CI.

NSF has a unique leadership role in formulating and implementing a national CI agenda 

focused on advancing science and engineering. 

Inclusive strategic planning is required to effectively address CI needs across a broad spectrum 

of organizations, institutions, communities and 

individuals, with input to the process provided 

through public comments, workshops, funded 

studies, advisory committees, merit review and 

open competitions.

Strategic investments in CI resources and 

services coupled with enabling policy and organizational framework are essential to continued 

U.S. leadership in science and engineering.

The integration and sharing of cyberinfrastructure assets deployed and supported at national, 

regional, local, community and campus levels 

represent the most effective way of constructing a comprehensive CI ecosystem suited to 

meeting future needs. 

Public and private national and international 

partnerships that integrate CI users and providers and benefit NSF’s research and education 

communities are also essential for enabling 

•

•

•

•

•

•

next-generation science and engineering.

Existing strengths, including research programs 

and CI facilities, serve as a foundation upon 

which to build a CI designed to meet the needs 

of the broad science and engineering community.

Merit review is essential for ensuring that the 

best ideas are pursued in all areas of CI funding.

Regular evaluation and assessment tailored to 

individual projects is essential for ensuring accountability to all stakeholders. 

A collaborative CI governance and coordination structure that includes representatives who 

contribute to basic CI research, development 

and deployment, as well as those who use CI, 

is essential to ensure that CI is responsive to 

community needs and empowers research at 

the frontier.

III. Goals and Strategies

NSF’s vision and mission statements on CI need 

well-defined goals and strategies to turn them into 

reality. The goals underlying these statements are 

provided below, with each goal followed by a brief 

description of the strategy to achieve the goal.

Across the CI landscape, NSF will:

Provide communities addressing the most 

computationally challenging problems with 

access to a world-class, high performance 

computing (HPC) environment through NSF 

acquisition and through exchange-of-service 

agreements with other entities, where possible.

NSF’s investment strategy for the provision of 

CI resources and services will be linked to careful 

requirements analyses of the computational needs 

of research and education communities. NSF 

investments will be coordinated with those of 

other agencies in order to maximize access to these 

capabilities and to provide a range of representative high performance architectures. 

Broaden access to state-of-the-art computing 

resources, focusing especially on institutions 

with less capability and communities where 

computational science is an emerging activity.

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Robert Patterson demonstrates NCSA’s 3D Visualization to Dr. 

Arden Bement, the Director of NSF, and others during the FY08 

NSF budget roll-out. 

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National Science Foundation March 2007

Building on the achievements of current CI 

service providers and other NSF investments, the 

agency will work to make necessary computing 

resources more broadly available, paying particular 

attention to emerging and underserved communities. 

Support the development and maintenance 

of robust systems software, programming 

tools, and applications needed to close the 

growing gap between peak performance and 

sustained performance on actual research 

codes, and to make the use of HPC systems, 

as well as novel architectures, easier and 

more accessible. 

NSF will build on research in computer science 

and other research areas to provide science and 

engineering applications and problem-solving environments that more effectively exploit innovative 

architectures and large-scale computing systems. 

NSF will continue and build on its existing collaborations with other agencies in support of the 

development of HPC software and tools.

Support the continued development, expansion, hardening and maintenance of endto-end software systems – user interfaces, 

workflow engines, science and engineering 

applications, data management, analysis 

and visualization tools, collaborative tools, 

and other software integrated into complete 

science and engineering systems via middleware – in order to bring the full power of a 

national cyberinfrastructure to communities 

of scientists and engineers. 

•

•

NCSA’s Cobalt computing system uses a 3D cylindrical configuration to model the sediment discharge of a river into the 

ocean and the initial stages of alluvial fan formation at the river’s mouth. 

Cyberinfrastructure will broaden access to state-of-the art resources for learning and discovery, creating new opportunities 

for participation by emerging and underserved communities.
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National Science Foundation March 2007

These investments will build on the software 

products of current and former programs, and will 

leverage work in core computer science research 

and development efforts supported by NSF and 

other federal agencies.

Support the development of the computing professionals, interdisciplinary teams, 

enabling policies and procedures, and new 

organizational structures such as virtual 

organizations, that are needed to achieve the 

scientific breakthroughs made possible by 

advanced CI, paying particular attention to 

opportunities to broaden the participation of 

underrepresented groups.

NSF will continue to improve its understanding of how participants in its research and 

education communities, as well as the scientific 

workforce, can use CI. For example, virtual 

organizations empower communities of users to 

interact, exchange information, and access and 

share resources through tailored interfaces. Some 

of NSF’s investments will focus on appropriate 

mechanisms or structures for use, while others will 

focus on how best to train future users of CI. NSF 

•

will take advantage of the emerging communities 

associated with CI that provide unique and special 

opportunities for broadening participation in the 

science and engineering enterprise. 

Support state-of-the-art innovation in data 

management and distribution systems, 

including digital libraries and educational 

environments that are expected to contribute 

to many of the scientific breakthroughs of the 

21st century.

NSF will foster communication among forefront data management and distribution systems, 

digital libraries, and other education environments 

sponsored in its various directorates. NSF will 

ensure that its efforts take advantage of innovation in large data management and distribution 

activities sponsored by other agencies and through 

international efforts. These developments will play 

a critical role in decisions that NSF makes about 

stewardship of long-lived data.

Support the design and development of the 

CI needed to realize the full scientific poten-

•

•

The DANSE project at CalTech integrates new materials theory with high-performance computing, using data from facilities such as DOE’s new Spallation Neutron Source in Oak Ridge, TN.
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tial of NSF’s investments in tools and large 

facilities, from observatories and accelerators to sensor networks and remote observing 

systems.

NSF’s investments in large facilities and other 

tools require new types of CI − such as wireless 

control of networks of sensors in hostile environments, rapid distribution and analysis of petascale 

data sets around the world, adaptive knowledgebased control and sampling systems, and innovative visualization systems for collaboration. NSF 

will ensure that these projects invest appropriately 

in CI capabilities, promoting the integrated and 

widespread use of the unique services provided by 

these and other facilities. In addition, NSF’s CI 

programs will be designed to serve the needs of 

these projects. 

Support the development and maintenance 

of the increasingly sophisticated applications needed to achieve the scientific goals of 

research and education communities. 

The applications needed to produce cut­tingedge science and engineering have become 

increasingly complex. They require teams, even 

communities, to develop and sustain wide and 

long-term applicability, and they leverage underlying software tools and increasingly common, 

persistent CI resources such as data repositories 

and authentication and authorization services. 

NSF’s investments in applications will involve its 

directorates and offices that support domain-specific science and engineering. Special attention will 

be paid to the cross-disciplinary nature of much of 

the work. 

Invest in the high-risk/high-gain basic research in computer science, computing and 

storage devices, mathematical algorithms, 

and the human/CI interfaces that are critical 

to powering the future exponential growth in 

all aspects of computing, including hardware 

speed, storage, connectivity and scientific 

productivity.

NSF’s investments in operational CI must be 

coupled with vigorous research programs in the 

directorates to ensure that operational capabilities continue to expand and extend in the future. 

Important among these programs are activities to 

understand how humans adopt and use CI. NSF 

is especially well-placed to foster collaborations 

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among computer scientists; social, behavioral and 

economic scientists; and other domain scientists 

and engineers to understand how humans can best 

use CI, in both research and education environments.

Provide a framework that will sustain 

reliable, stable resources and services while 

enabling the integration of new technologies 

and research developments with a minimum 

of disruption to users. 

NSF will minimize disruption to users by realizing a comprehensive CI with an architecture and 

framework that emphasizes interoperability and 

open standards, thus providing flexibility for upgrades, enhancements and evolutionary changes. 

Pre-planned arrangements for alternative CI availabilities during competitions, changeovers and 

upgrades to production operations and services 

will be made, including cooperative arrangements 

with other agencies. 

A strategy common to achieving all of these 

goals is partnering nationally and internationally, with other agencies, the private sector, and 

with universities to achieve a worldwide CI that 

is interoperable, flexible, efficient, evolving and 

broadly accessible. In particular, NSF will take 

a lead role in formulating and implementing a 

national CI strategy.

IV. Planning for Cyberinfrastructure 

To implement its cyberinfrastructure vision, 

NSF will develop interdependent plans for each 

of the following aspects of CI, with emphasis on 

their integration to create a balanced science- and 

engineering-driven national CI:

High Performance Computing

Data, Data Analysis, and Visualization

Virtual Organizations for Distributed 

Communities, and 

Learning and Workforce Development. 

Others may be added at a later date.

While these aspects are addressed separately as 

a means for organizing this document, the central 

goal is the development of a fully-integrated CI 

framework comprised of the balanced, seamless 

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Researchers upgrade the software of an automated weather station that transmits data to help track the 

iceberg’s position in the Antarctic and reports on the microclimate of the ice surface. 

blending of these components. This will require 

integrative management structures (such as the 

newly formed Office of Cyberinfrastructure, the 

NSF-wide Cyberinfrastructure Council, and the 

Cyberinfrastructure Coordinators’ Committee), as 

well as science-driven, community-based 

planning and implementation processes that 

span all the elements of a truly comprehensive CI 

framework.

These plans will be reviewed annually and will 

evolve over time, paced by the considerable rate 

of innovation in computing and communication, and by the growing needs of the science and 

engineering community for state-of-the-art CI 

capabilities. Through cycles of use-driven innovation, NSF’s vision will become reality. 

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I. What Does High Performance 

Computing Offer Science and 

Engineering?

What are the three-dimensional structures of all 

of the proteins encoded by the human genome, 

and how does structure influence their function in 

a human cell? What patterns of emergent behavior occur in models of very large societies? How 

do massive stars explode and produce the heaviest elements in the periodic table? What sort of 

abrupt transitions can occur in Earth’s climate and 

ecosystem structure? How do these transitions 

occur, and under what circumstances? If we could 

design catalysts atom-by-atom, could we transform industrial synthesis? What strategies might 

be developed to optimize management of complex 

infrastructure systems? What kind of language 

processing can occur in large assemblages of 

neurons? Can we enable integrated planning and 

response to natural and man-made disasters that 

prevent or minimize the loss of life and property? 

These are just some of the important questions 

that researchers wish to answer using contemporary tools in a state-of-the-art High Performance 

Computing (HPC) environment.

Using HPC-based applications, researchers 

study the properties of minerals at the extreme 

temperatures and pressures that occur deep within 

the Earth. They simulate the development of 

structure in the early Universe. They probe the 

structure of novel phases of matter such as the 

quark-gluon plasma. HPC capabilities enable the 

modeling of life cycles that capture interdependenThe visualization above, created from data generated by a tornado simulation calculated on the NCSA computing cluster, 

shows the tornado by spheres colored according to pressure. Orange and blue tubes represent the rising and falling 

airflow around the tornado. 

NCAR’s blueice supercomputer, shown on the opposite page, enables scientists to enhance the resolution and complexity 

of Earth system models, improve climate and weather research, and provide more accurate data to decision makers. 

CHAPTER 2 

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cies across diverse disciplines and multiple scales 

to create globally competitive manufacturing 

enterprise systems. And they examine the way 

proteins fold and vibrate after they are synthesized 

inside an organism. In fact, sophisticated numerical simulations permit scientists and engineers to 

perform a wide range of in silico experiments that 

would otherwise be too difficult, too expensive, or 

impossible to perform in the laboratory. 

HPC systems and services are also essential to 

the success of research conducted with sophisticated experimental tools. Without the waveforms 

produced by the numerical simulation of black 

hole collisions and other astrophysical events, 

gravitational wave signals cannot be extracted 

from the data produced by the Laser Interferometer Gravitational Wave Observatory. High-resolution seismic inversions from the higher density 

of broad-band seismic observations furnished by 

the Earthscope project are necessary to determine 

shallow and deep Earth structure. Simultaneous 

integrated computational and experimental testing is conducted on the Network for Earthquake 

Engineering Simulation to improve seismic design 

of buildings and bridges. HPC is essential to 

extracting the signature of the Higgs boson and 

supersymmetric particles – two of the scientific 

drivers of the Large Hadron Collider – from the 

petabytes of data produced in the trillions of 

particle collisions. 

Science and engineering research and education enabled by state-of-the-art HPC tools have 

a direct bearing on the nation’s competitiveness. 

If investments in HPC are to have a long-term 

impact on problems of national need, such as 

bioengineering, critical infrastructure protection 

(for example, the electric power grid), health care, 

manufacturing, nanotechnology, energy, and 

transportation, then HPC tools must deliver high 

performance capability for a wide range of science 

and engineering applications. 

A functioning ribosome, a complex of three large RNA molecules and fifty proteins with three million atoms, is 

simulated on the Texas Advanced Computing Center computer. 
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Results from the Parallel Climate Model, prepared from 

data in the Earth System Grid, depict wind vectors, 

surface pressure, seas surface temperature and sea ice 

concentration.

II. The Next Five Years: Creating 

a High Performance Computing 

Environment for Petascale Science 

and Engineering

NSF’s five-year HPC goal is to enable petascale 

science and engineering through the deployment 

and support of a world-class HPC environment 

comprising the most capable combination of HPC 

assets available to the academic community. The 

petascale HPC environment will enable investigations of computationally challenging problems 

that require computers operating at sustained 

speeds on actual research codes of 1015 floating 

point operations per second (petaflops) or that 

work with extremely large data sets on the order of 

1015 bytes (petabytes). 

Petascale HPC capabilities will permit researchers to perform simulations that are intrinsically 

multi-scale or that involve multiple simultaneous 

reactions, such as modeling the interplay among 

genes, microbes, and microbial communities and 

simulating the interactions among the ocean, 

atmosphere, cryosphere and biosphere in Earth 

systems models. In addition to addressing the 

most computationally challenging demands of 

science and engineering, new and improved 

HPC software services will make supercomputing 

platforms supported by NSF and other partner 

organizations more efficient, more accessible, and 

easier to use.

NSF will support the deployment of a well-engineered, scalable, HPC infrastructure designed to 

evolve as science and engineering research needs 

change. It will include a sufficient level of diversity, both in architecture and scale of deployed HPC 

systems, to realize the research and education goals 

of the broad science and engineering community. 

NSF’s HPC investments will be complemented 

by its simultaneous investments in data analysis 

and visualization facilities essential to the effective 

transformation of data products into information 

and knowledge.

The following principles will guide the agency’s 

FY 2006 through FY 2010 investments:

Science and engineering research and education priorities will drive HPC investments.

Collaborative activities involving science and 

engineering researchers and private sector 

organizations are needed to ensure that HPC 

systems and services are optimally configured 

to support petascale scientific computing.

Researchers and educators require access to 

reliable, robust, production-quality HPC 

resources and services.

HPC-related research and development 

advances generated in the public and private 

sectors, both domestic and foreign, must be 

leveraged to enrich HPC capabilities. 

The development, implementation and annual 

update of an effective multi-year HPC strategy 

is crucial to the timely introduction of research 

and development outcomes and innovations in 

HPC systems, software and services.

NSF’s implementation plan to create a petascale 

environment includes the following three interrelated components: 

1). Specification, Acquisition, Deployment 

and Operation of Science-Driven HPC Systems 

Architectures

An effective computing environment designed 

to meet the computational needs of a range of 

science and engineering applications will include a 

variety of computing systems with complementary 

performance capabilities. By 2010, the petascale 

computing environment available to the academic 

science and engineering community is likely to 

consist of: (i) a significant number of systems with 

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This numerical simulation, created on the NCSA Itanium Linux Cluster by international researchers, shows 

the merger of two black holes and the ripples in space time that are born of the merger. 

peak performance in the 50-500 teraflops range, 

deployed and supported at the local level by individual campuses and other research organizations; 

(ii) multiple systems with peak performance of 

500+ teraflops that support the work of thousands 

of researchers nationally; and, (iii) at least one 

system capable of delivering sustained performance approaching 1015 floating point operations 

per second on real applications that consume large 

amounts of memory, and/or that work with very 

large data sets projects that demand the highest 

levels of computing performance. All NSF-deployed systems will be appropriately balanced and 

will include core computational hardware, local 

storage of sufficient capacity, and appropriate data 

analysis and visualization capabilities.

Over the FY 2006-2010 period, NSF will focus 

on HPC system acquisitions in the 100 teraflops 

to 10 petaflops range, where strategic investments 

on a national scale are necessary to ensure international leadership in science and engineering. 

Since different science and engineering codes may 

achieve optimal performance on different HPC 

architectures, it is likely that by 2010 the NSFsupported HPC environment will include both 

loosely coupled and tightly coupled systems, with 

several different memory models. 

To address the challenge of providing the 

research community with access to a range of 

HPC architectures within a constrained budget, 

a key element of NSF’s strategy is to participate 

in resource-sharing with other federal agencies. A 
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Massachusetts Institute of Technology researchers are developing 

computational tools to analyze the structure of any protein, such 

as the human ubiquitin hydrolase (shown), for knots. 

strengthened interagency partnership will focus, to 

the extent practicable, on ensuring shared access 

to federal leadership-class resources with different 

architectures, and on the coordination of investments in HPC system acquisition and operation. 

The Department of Energy’s Office of Science 

and National Nuclear Security Administration 

have very active programs in leadership computing. The Department of Defense’s (DOD) High 

Performance Computing Modernization Office 

(HPCMOD) provides HPC resources and services 

for the DOD science and engineering community, 

while NASA is deploying significant computing systems that are also of interest to NSF PIs. 

NSF will explore enhanced coordination mechanisms with other appropriate federal agencies to 

capitalize on their common interests. It will seek 

opportunities to make coordinated and collaborative investments in science-driven hardware 

architectures in order to increase the diversity of 

architectures of leadership class systems available 

to researchers and educators around the country, 

to promote sharing of lessons learned, and to 

provide a richer HPC environment for the user 

communities supported by each agency. 

Strong partnerships involving universities, industry and government are also critical to success. 

NSF will also promote resource sharing between 

and among academic institutions to optimize the 

accessibility and use of HPC assets deployed and 

supported at the campus level. 

In addition to leveraging the promise of Phase 

III of the Defense Advanced Research Projects 

Agency (DARPA)-sponsored High Productivity 

Computing Systems (HPCS) program, the agency 

will establish a discussion and collaboration forum 

for scientists and engineers—including computational and computer scientists and engineers—and 

HPC system vendors, in order to ensure that HPC 

systems are optimally configured to support stateof-the-art scientific computing. On the one hand, 

these discussions will keep NSF and the academic 

community informed about new products, product roadmap and technology challenges at various 

vendor organizations. On the other, they will provide HPC system vendors with insights into the 

major concerns and needs of the academic science 

and engineering community. These activities will 

lead to better alignment between applications and 

hardware both by influencing algorithm design 

and by influencing system integration. 

2). Development and Maintenance of Supporting Software: New Design Tools, Performance Modeling Tools, Systems Software, and 

Fundamental Algorithms.

Many of the HPC software and service building 

blocks in scientific computing are common to a 

number of science and engineering applications. 

A supporting software and service infrastructure 

will accelerate the development of the scientific 

application codes needed to solve challenging 

scientific problems, and will help insulate these 

codes from the evolution of future generations of 

HPC hardware. 

Supporting software services include the 

provision of intelligent development and problem-solving environments and tools. These tools 

are designed to provide improvements in ease of 

use, reusability of modules, and portable performance. Tools and services that take advantage of 

commonly-supported software tools can deliver 

similar work environments across different HPC 

platforms, greatly reducing the time-to-solution 

of computationally-intensive research problems 

by permitting local development of research 

codes that can then be rapidly transferred to, or 

incorporate services provided by, larger production 
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environments. These tools, and workflows built 

from collections of such tools, can also be packaged for more general use. Applications scientists 

and engineers will also benefit from the development of new tools and approaches to debugging, 

performance analysis, and performance optimization. 

Specific applications depend on a broad class 

of numerical and non-numerical algorithms that 

are widely used by many applications, including 

linear algebra, fast spectral transforms, optimization algorithms, multi-grid methods, adaptive 

mesh refinement, symplectic integrators, and 

sorting and indexing routines. To date, improved 

or new algorithms have been important contributors to performance improvements in science and 

engineering applications, the development of 

multi-grid solvers for elliptic partial differential 

equations being a prime example. Innovations 

in algorithms will have a significant impact on 

the performance of applications software. The 

development of algorithms for different architectural environments is an essential component of 

the effort to develop portable, scalable, applications software. Other important software services 

include libraries for communications services, such 

as MPI and OpenMP.

The development and deployment of operating 

systems and compilers that scale to hundreds of 

thousands of processors are also necessary. They 

must provide effective fault-tolerance and effectively insulate users from parallelization, as well as 

provide protection from latency management and 

thread management issues. To test new developments at large scales, operating systems and kernel 

researchers and developers must have access to the 

infrastructure necessary to test their developments 

at scale. 

The software provider community will be a 

source for: applied research and development 

of supporting technologies; harvesting promising supporting software technologies from the 

research communities; performing scalability/reliability tests to explore software viability; 

developing, hardening and maintaining software 

where necessary; and facilitating the transition of 

commercially viable software into the private sector. It is anticipated that this community will also 

support general software engineering consulting 

services for science and engineering applications, 

and will provide software engineering consulting 

support to individual researchers and research and 

education teams as necessary. 

The software provider community will be 

expected to promote software interoperability 

among the various components of the cyberinfrastructure software stack, such as those generated 

to provide modeling and simulation data, data 

analysis and visualization services, and networked 

resources and virtual organization capabilities. (See 

Chapters 3 and 4 in this document.) This will be 

accomplished through the creation and utilization of appropriate software test harnesses and will 

ensure that sufficient configuration controls are 

in place to support the range of HPC platforms 

used by the research and education community. 

The applications community will identify needed 

improvements in supporting software and will 

provide input and feedback on the quality of 

services provided. 

NSF will seek guidance on the evolution of 

software support from representatives of academia, 

federal agencies and private sector organizations, 

including third party and system vendors. They 

will provide input on the strengths, weaknesses, 

opportunities and gaps in the software services 

currently available to the science and engineering 

research and education communities. 

To minimize duplication of effort and optimize 

the value of HPC services provided to the science 

and engineering community, NSF’s investments 

will be coordinated with those of other agencies. 

DOE currently invests in software infrastructure 

centers through the Scientific Discovery through 

Advanced Computing (SciDAC) program, while 

DARPA’s investments in the HPCS program contribute significant systems software and hardware 

innovations. NSF will seek to leverage and add 

value to ongoing DOE and DARPA efforts in this 

area. 
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Two skulls of separate species of pterosaurs were scanned at the High-Resolution X-ray Computed Tomography Facility at The University of Texas at Austin and the data was then fed to DigiMorph digital library 

to produce 2-D and 3-D structural visualizations.

3). Development and Maintenance of Portable, Scalable Applications Software

Today’s microprocessor-based terascale computers place considerable demands on our ability to 

manage parallelism, and to deliver large fractions 

of peak performance. As the agency seeks to 

create a petascale computing environment, it will 

embrace the challenge of developing or converting 

key application codes to run effectively on new 

and evolving system architectures. 

Over the FY 2006 through 2010 period, NSF 

will make significant new investments in the development, hardening, enhancement and maintenance of scalable applications software, including 

community models, to exploit the full potential of 

current terascale and future petascale systems architectures. The creation of well-engineered, easyto-use software will reduce the complexity and 

time-to-solution of today’s challenging scientific 

applications. NSF will promote the incorporation of sound software engineering approaches 

in existing widely-used research codes and in the 

development of new research codes. Multidisciplinary teams of researchers will work together 

to create, modify and optimize applications for 

current and future systems using performance 

modeling tools and simulators. 

Since the nature and genesis of science and 

engineering codes varies across the research landscape, a successful programmatic effort in this area 

will weave together several strands. A new activity 

will be designed to take applications that have the 

potential to be widely used within a community or 

communities, to harden these applications based 

on modern software engineering practices, to 

develop versions for the range of architectures that 

scientists wish to use them on, to optimize them 

for modern HPC architectures, and to provide 

user support. 

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An artist’s conception (above) depicts fundamental NEON observatory instrumentation and systems as well as 

potential spatial organization of the environmental measurements made by these instruments and systems. 

The image on the opposite page shows the action of the enzyme cellulase on cellulose using the CHARMM 

community code in a simulation carried out at SDSC. NREL will use the simulation to help develop strategies for 

efficient large-scale conversion of biomass into ethanol.

I. A Wealth of Scientific 

Opportunities Afforded by 

Digital Data

Science and engineering research and education 

have become increasingly data-intensive as a result 

of the proliferation of digital technologies, instrumentation, and pervasive networks through which 

data are collected, generated, shared and analyzed. 

Worldwide, scientists and engineers are producing, accessing, analyzing, integrating and storing 

terabytes of digital data daily through experimentation, observation and simulation. Moreover, the dynamic integration of data generated 

through observation and simulation is enabling 

the development of new scientific methods that 

adapt intelligently to evolving conditions to reveal 

new understanding. The enormous growth in the 

availability and utility of scientific data is increasing scholarly research productivity, accelerating the 

transformation of research outcomes into products 

and services, and enhancing the effectiveness of 

learning across the spectrum of human endeavor. 

New scientific opportunities are emerging from 

increasingly effective data organization, access and 

usage. Together with the growing availability and 

capability of tools to mine, analyze and visualize data, the emerging data cyberinfrastructure 

is revealing new knowledge and fundamental 

insights. For example, analyses of DNA sequence 

data are providing remarkable insights into the 

origins of man, revolutionizing our understanding of the major kingdoms of life, and revealing 

stunning and previously unknown complexity in 

microbial communities. Sky surveys are changing 

our understanding of the earliest conditions of the 

universe and providing comprehensive views of 

phenomena ranging from black holes to supernovae. Researchers are monitoring socioeconomic 

dynamics over space and time to advance our 

CHAPTER 3

DATA, DATA ANALYSIS, AND VISUALIZATION 

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The National Virtual Observatory’s Sky Statistics Survey allows astronomers to get a fast inventory of astronomical objects from various catalogs.

Cyberinfrastructure Vision

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understanding of individual and group behavior and its relationship to social, economic and 

political structures. Using combinatorial methods, 

scientists and engineers are generating libraries 

of new materials and compounds for health and 

engineering, and environmental scientists and 

engineers are acquiring and analyzing streaming 

data from massive sensor networks to understand 

the dynamics of complex ecosystems. 

In this dynamic research and education 

environment, science and engineering data are 

constantly being collected, created, deposited, 

accessed, analyzed and expanded in the pursuit of 

new knowledge. In the future, U.S. international 

leadership in science and engineering will increasingly depend upon our ability to leverage this 

reservoir of scientific data captured in digital form, 

and to transform these data into information and 

knowledge aided by sophisticated data mining, 

integration, analysis and visualization tools. 

This chapter sets forth a framework in which 

NSF will work with its partners in science and 

engineering – public and private sector organizations both foreign and domestic representing data 

producers, scientists, engineers, managers and 

users alike – to address data acquisition, access, 

usage, stewardship and management challenges in 

a comprehensive way.

II. Definitions

A. Data, Metadata and Ontologies

In this document, “data” and “digital data” are 

used interchangeably to refer to data and information stored in digital form and accessed electronically. 

Data. For the purposes of this document, data 

are any and all complex data entities from observations, experiments, simulations, models, 

and higher order assemblies, along with the 

associated documentation needed to describe 

and interpret the data.

Metadata. Metadata are a subset of data, and 

are data about data. Metadata summarize data 

content, context, structure, interrelationships, 

and provenance (information on history and 

origins). They add relevance and purpose to 

data, and enable the identification of similar 

data in different data collections. 

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Ontology. An ontology is the systematic 

description of a given phenomenon. It often 

includes a controlled vocabulary and relationships, captures nuances in meaning and enables 

knowledge sharing and reuse. 

B. Data Collections

This document adopts the definition of data 

collection types provided in the NSB report on 

Long-Lived Digital Data Collections, where data 

collections are characterized as being one of three 

functional types:

Research Collections. Authors are individual 

investigators and investigator teams. Research 

collections are usually maintained to serve immediate group participants only for the life of 

a project, and are typically subjected to limited 

processing or curation. Data may not conform 

to any data standards.

Resource Collections. Resource collections 

are authored by a community of investigators, 

often within a domain of science or engineering, and are often developed with communitylevel standards. Budgets are often intermediate 

in size. Lifetime is between the mid- and 

long-term.

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The GLORIAD network, an optical network ring around 

the northern hemisphere, promotes new opportunities for 

cooperation and understanding for scientists, educators and 

students.

Reference Collections. Reference collections 

are authored by and serve large segments 

of the science and engineering community 

and conform to robust, well-established and 

comprehensive standards, which often lead to 

a universal standard. Budgets are large and are 

often derived from diverse sources with a view 

to indefinite support. 

 

Boundaries between the types are not rigid, and 

collections originally established as research collections may evolve over time to become resource 

and/or reference collections. In this document, 

the term data collection is construed to include 

one or more databases and their relevant technological implementation. Data collections are 

managed by organizations and individuals with 

the necessary expertise to structure them and to 

support their effective use. 

III. Developing a Coherent Data 

Cyberinfrastructure in a Complex 

Global Context

Since data and data collections are owned or 

managed by a wide range of communities, organizations and individuals around the world, NSF 

must work in an evolving environment constantly 

being shaped by developing international and 

national policies and treaties, community-specific policies and approaches, institutional-level 

programs and initiatives, individual practices, and 

continually advancing technological capabilities. 

At the international level, a number of nations 

and international organizations have already recognized the broad societal, economic, and scientific 

benefits that result from open access to science 

and engineering digital data. In 2004, more than 

30 nations, including the United States, declared 

their joint commitment to work toward the establishment of common access regimes for digital 

research data generated through public funding. 

Since the international exchange of scientific data, 

information and knowledge promises to significantly increase the scope and scale of research 

and its corresponding impact, these nations are 

working together to define the implementation 

steps necessary to enable the global science and 

engineering system. 

The U.S. community is engaged through the 

Committee on Data for Science and Technology 

•

(CODATA). The U.S. National Committee for 

CODATA (USNC/CODATA) is working with 

international CODATA partners, including the 

International Council for Science (ICSU), the 

International Council for Scientific and Technical Information (ICSTI), the World Data Centers 

(WDCs) and others, to accelerate the development of a global open-access scientific data and 

information resource, through the construction of 

an online “open access knowledge environment,” 

as well as through targeted projects. The Global 

Information Commons for Science is a multistakeholder initiative arising out of the second 

phase of the World Summit on the Information 

Society that can provide important opportunities 

for international coordination and cooperation. 

The goals of this initiative include improving 

understanding of the benefits of access to scientific 

data and information, promoting successful institutional and legal models for providing sustainable 

access, and enhancing coordination among the 

many science and engineering stakeholders around 

the world.

A number of international science and engineering communities have also been developing data 

management and curation approaches for reference and resource collections. For example, the 

international Consultative Committee for Space 

Data Standards (CCSDS) defined an archive 

reference model and service categories for the inter-
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Images produced by Montage on SDSC TeraGrid from 

the 2MASS all-sky survey, provide astronomers with new 

insights into the large-scale structure of the Milky Way.

mediate and long-term storage of digital data relevant to space missions. This effort produced the 

Open Archival Information System (OAIS), now 

adopted as the “de facto” standard for building 

digital archives, and provided evidence that a community-focused activity can have much broader 

impact than originally intended. In another 

example, the Inter-University Consortium for 

Political and Social Research (ICPSR) - a membership-based organization with over 500 member 

colleges and universities around the world - maintains and provides access to a vast archive of social 

science data. ICPSR serves as a content management organization, preserving relevant social 

science data and migrating them to new storage 

media as technology changes, and also provides 

user support services. ICPSR recently announced 

plans to establish an international standard for 

social science documentation. Similar activities 

in other communities are also underway. Clearly, 

NSF must maintain a presence in, support, and 

add value to these ongoing international discussions and activities.

Activities on an international scale are complemented by activities within nation states. In the 

United States, a number of organizations and 

communities of practice are exploring mechanisms 

to establish common approaches to digital data access, management and curation. For example, the 

Research Library Group (RLG – a not-for-profit 

membership organization representing libraries, 

archives and museums) and the U.S. National 

Archives and Records Administration (NARA – a 

sister agency whose mission is to provide direction 

and assistance to federal agencies on records management) are producing certification requirements 

for establishing and selecting reliable digital information repositories. RLG and NARA intend their 

results to be standardized via the International 

Organization of Standardization (ISO) Archiving 

Series, and may impact all data collections types. 

The National Institutes of Health (NIH) National 

Center for Biotechnology Information plays an 

important role in the management of genome data 

at the national level, supporting public databases, 

developing software tools for analyzing data, and 

disseminating biomedical information. 

At the institutional level, colleges and universities are developing approaches to digital 

data archiving, curation and analysis. They are 

sharing best practices to develop digital libraries 

that collect, preserve, index and share research 

and education material produced by faculty and 

other individuals within their organizations. The 

technological implementations of these systems 

are often open-source and support interoperability 

among their adopters. University-based research 

libraries and research librarians are positioned to 

make significant contributions in this area, where 

standard mechanisms for access and maintenance 

of scientific digital data may be derived from existing library standards developed for print material. 

These efforts are particularly important to NSF 

as the agency considers the implications of not 

only making all data generated with NSF funding broadly accessible, but of also promoting the 

responsible organization and management of these 

data so that they are widely usable.

IV. The Next Five Years: Towards a 

National Digital Data Framework

Motivated by a vision in which science and 

engineering digital data are routinely deposited 

in well-documented form, are regularly and easily 

consulted and analyzed by specialists and non-specialists alike, are openly accessible while suitably 

protected, and are reliably preserved, NSF’s fiveyear goal is twofold: 

To catalyze the development of a system of 

science and engineering data collections that is 

open, extensible and evolvable; and

To support development of a new generation 

of tools and services facilitating data mining, 

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The IRIS Seismic Monitor System allows scientists and others to monitor 

global earthquakes in near real-time, visit seismic stations world-wide, 

and search the web for earthquake information.

integration, analysis, and visualization essential to turning data into new knowledge and 

understanding. 

The resulting national digital data framework 

will be an integral component in the national 

cyberinfrastructure framework described in this 

document. It will consist of a range of data collections and managing organizations, networked 

together in a flexible technical architecture using 

standard, open protocols and interfaces, and 

designed to contribute to the emerging global 

information commons. It will be simultaneously 

local, regional, national and global in nature, and 

will evolve as science and engineering research and 

education needs change and as new science and 

engineering opportunities arise. Widely accessible tools and services will permit scientists and 

engineers to access and manipulate these data to 

advance the science and engineering frontier. 

In print form, the preservation process is 

handled through a system of libraries and other 

repositories throughout the country and around 

the globe. Two features of this print-based system 

make it robust. First, the diversity of business 

models deriving support from a variety of sources 

means that no single entity bears sole responsibility for preservation, and the system is resilient to 

changes in any particular sector. Second, there 

is overlap in the collections, and redundancy of 

content reduces the potential for catastrophic loss 

of information. 

The national data framework is envisioned 

to provide an equally robust and diverse system 

for digital data management and access. It will 

promote interoperability between data collections 

supported and managed by a range of organizations and organization types; provide for appropriate protection and reliable long-term preservation 

of digital data; deliver computational performance, 

data reliability and movement through shared 

tools, technologies and services; and accommodate individual community preferences. NSF will 

also develop a suite of coherent data policies that 

emphasize open access and effective organization 

and management of digital data, while respecting 

the data needs and requirements within science 

and engineering domains.

The following principles will guide the agency’s 

FY 2006 through FY 2010 investments:

Science and engineering research and education opportunities and priorities will motivate 

NSF investments in data cyberinfrastructure.

Science and engineering data generated with 

NSF funding will be readily accessible and easily usable, and will be appropriately, responsibly and reliably preserved.

Broad community engagement is essential to 

the prioritization and evaluation of the utility 

of scientific data collections, including the possible evolution from research to resource and 

reference collection types.

Continual exploitation of data in the creation 

of new knowledge requires that investigators 

have access to the tools and services necessary 

to locate and access relevant data, and understand its structure sufficiently to be able to 

interpret and (re)analyze what they find. 

The establishment of strong, reciprocal, 

international, interagency and public-private 

partnerships is essential to ensure all stakeholders are engaged in the stewardship of valuable 

data assets. Transition plans, addressing issues 

such as media, stewardship and standards, will 

be developed for valuable data assets, to protect 

data and assure minimal disruption to the 

community during transition periods.

Mechanisms will be created to share data 

stewardship best practices between nations, 

communities, organizations and individuals.

In light of legal, ethical and national security 

concerns associated with certain types of data, 

mechanisms essential to the development of 

both statistical and technical ways to protect 

privacy and confidentiality will be supported. 

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•

•

•

•

•
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Researchers check functionality and performance of the Compact Muon Solenoid detector at CERN before its closure. 

Built on the Large Hadron Collider, it provides a magnetic field of 4T.

To date, challenges associated with effective 

stewardship and preservation of scientific data 

have been more tractable when addressed through 

communities of practice that may derive support 

from a range of sources. For example, NSF supports the Incorporated Research Institutions for 

Seismology (IRIS) consortium to manage seismology data. Jointly with NIH and DOE, the agency 

supports the Protein Data Bank to manage data 

on the three-dimensional structures of proteins 

and nucleic acids. Multiple agencies support the 

University Consortium for Atmospheric Research, 

an organization that has provided access to atmospheric and oceanographic data sets, simulations, and outcomes extending back to the 1930s 

through the National Center for Atmospheric 

Research. 

Existing collections and managing organization 

models reflect differences in culture and practice 

within the science and engineering community. 

As community proxies, data collections and their 

managing organizations can provide a focus for 

the development and dissemination of appropriate standards for data and metadata content and 

format, guided by an appropriate communitydefined governance approach. This is not a static 

process, as new disciplinary fields and approaches, 

data types, organizational models and information 

strategies inexorably emerge. This is discussed in 

detail in the Long-Lived Digital Data Collections 

report of the National Science Board. 

Since data are held by many federal agencies, commercial and non-profit organizations, 

and international entities, NSF will foster the 

establishment of interagency, public-private and 

international consortia charged with providing 

stewardship for digital data collections to promote interoperability across data collections. The 

agency will work with the broad community of 

science and engineering producers, managers, 

scientists and users to develop a common conceptual framework. A full range of mechanisms 

will be used to identify and build upon common 

ground across domain communities and managing 

organizations, engaging all stakeholders. Activities 

will include: the support of new projects; development and implementation of evaluation and 

assessment criteria that, among other things, reveal 

lessons learned across communities; support of 

A. A Coherent Organizational Framework - 

Data Collections and Managing Organizations
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A simulated event of the collision of two protons in the ATLAS experiment. The colors of the tracks emanating from the center show the 

different types of particles emerging from the collision.

community and intercommunity workshops; and 

the development of strong partnerships with other 

stakeholder organizations. Stakeholders in these 

activities include data authors, data managers, data 

scientists and engineers, and data users representing a diverse range of communities and organizations, including universities and research libraries, government agencies, content management 

organizations and data centers, and industry. 

To identify and promote lessons learned across 

managing organizations, NSF will continue to 

promote the coalescence of appropriate collections with overlapping interests, approaches and 

services. This reduces data-driven fragmentation 

of science and engineering domains. Progress is 

already being made in some areas. For example, 

NSF has been working with the environmental 

science and engineering community to promote 

collaboration across disciplines ranging from ecology and hydrology to environmental engineering. 

This has resulted in the emergence of common 

cyberinfrastructure elements and new interdisciplinary science and engineering opportunities. 

B. Developing A Flexible Technological Architecture

From a technological perspective, the national 

data framework must provide for reliable preservation, access, analysis, interoperability, and data 

movement, possibly using a web or grid services 

distributed environment. The architecture must 

use standard open protocols and interfaces to 

enable the broadest use by multiple communities. 

It must facilitate user access, analysis and visualization of data, addressing issues such as authentication, authorization and other security concerns, 

and data acquisition, mining, integration, analysis 

and visualization. It must also support complex 

workflows enabling data discovery. Such an architecture can be visualized as a number of layers providing different capabilities to the user, including 

data management, analysis, collaboration tools, 

and community portals. The connections among 

these layers must be transparent to the end user, 

and services must be available as modular units 

responsive to individual or community needs. The 

system is likely to be implemented as a series of 

distributed applications and operations supported 

by a number of organizations and institutions distributed throughout the country. It must provide 

for the replication of data resources to reduce the 

potential for catastrophic loss of digital information through repeated cycles of systems migration 

and all other causes since, unlike printed records, 

the media on which digital data are stored and the 

structures of the data are relatively fragile. 

High quality metadata, which summarize data 

content, context, structure, interrelationships, and 

provenance (information on history and origins), 

are critical to successful information management, 

annotation, integration and analysis. Metadata 

take on an increasingly important role when addressing issues associated with the combination of 

data from experiments, observations and simulations. In these cases, product data sets require 

metadata that describe, for example, relevant 

collection techniques, simulation codes or pointers to archived copies of simulation codes, and 

codes used to process, aggregate or transform data. 

These metadata are essential to create new knowledge and to meet the reproducibility imperative 

of modern science. Metadata are often associated 

with data via markup languages, representing 

a consensus around a controlled vocabulary to 

describe phenomena of interest to the community, and allowing detailed annotations of data to 

be embedded within a data set. Because there is 

often little awareness of markup language development activities within science and engineering 

communities, effort is expended reinventing what 

could be adopted or adapted from elsewhere. Scientists and engineers therefore need access to tools 

and services that help ensure that metadata are 

automatically captured or created in real-time. 
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Effective data analysis tools apply computational techniques to extract new knowledge through 

a better understanding of the data and its redundancies and relationships by filtering extraneous 

information and by revealing previously unseen 

patterns. For example, the Large Hadron Collider at CERN generates such massive data sets 

that the detection of both expected events, such 

as the Higgs boson, and unexpected phenomena 

require the development of new algorithms, both 

to manage data and to analyze it. Algorithms 

and their implementations must be developed for 

statistical sampling, for visualization, to enable the 

storage, movement and preservation of enormous 

quantities of data, and to address other unforeseen 

problems certain to arise.

Scientific visualization, including not just static 

images but also animation and interaction, leads 

to better analysis and enhanced understanding. 

Currently, many visualization systems are domain or application-specific and require a certain 

commitment to understanding or learning to 

use them. Making visualization services more 

transparent to the user lowers the threshold of usability and accessibility, and makes it possible for 

a wider range of users to explore a data collection. 

Analysis of data streams also introduces problems 

in data visualization and may require new approaches for representing massive, heterogeneous 

data streams. 

Deriving knowledge from large data sets 

presents specific scaling problems due to the sheer 

number of items, dimensions, sources, users, and 

disparate user communities. The human ability to 

process visual information can augment analysis, 

especially when analytic results are presented in 

iterative and interactive ways. Visual analytics, the 

science of analytical reasoning enabled by interactive visual interfaces, can be used to synthesize the 

information content and derive insight from massive, dynamic, ambiguous, and even conflicting 

data. Suitable fully interactive visualizations help 

absorb vast amounts of data directly, to enhance 

one’s ability to interpret and analyze otherwise 

overwhelming data. Researchers can thus detect 

the expected and discover the unexpected, uncovering hidden associations and deriving knowledge 

from information. As an added benefit, their 

insights are more easily and effectively communicated to others. 

Creating and deploying visualization services 

requires new frameworks for distributed applications. In common with other cyberinfrastructure 

components, visualization requires easy-to-use, 

modular, extensible applications that capitalize on 

the reuse of existing technology. Today’s successful 

analysis and visualization applications use a pipeline, component-based system on a single machine 

or across a small number of machines. Extending 

to the broader distributed, heterogeneous cyberinfrastructure system will require new interfaces 

and work in fundamental graphics and visualization algorithms that can be run across remote and 

distributed settings.

To address this range of needs for data tools and 

services, NSF will work with the broad community to identify and prioritize needs. In making 

investments, NSF will complement private sector 

efforts, for example, those producing sophisticated 

indexing and search tools and packaging them as 

data services. NSF will support projects to conduct applied research and development of promising, interoperable data tools and services; perform 

scalability/reliability tests to explore tool viability; 

develop, harden and maintain software tools and 

services where necessary; and harvest promising 

research outcomes to facilitate the transition of 

commercially-viable software into the private sector. Data tools created and distributed through 

these projects will include not only access and 

ease-of-use tools, but also tools to assist with data 

input, tools that maintain or enforce formatting 

standards, and tools that make it easy to include or 

create metadata in real time. Clearinghouses and 

registries from which all metadata, ontology, and 

CAVE software, released by RCSB PDB and CalIT2, provides a new way 

of visualizing 3D macromolecular structures in an immersive, virtual reality environment. The CAVE allows users to move through and around a 

structure projected in the CAVE.
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markup language standards are provided, publicized, and disseminated must be developed and 

supported, together with the tools for their implementation. Data accessibility and usability will 

also be improved with the support of means for 

automating cross-ontology translation. Collectively, these projects will be responsible for ensuring 

software interoperability with other components 

of the cyberinfrastructure, such as those generated 

to provide High Performance Computing capabilities and to enable the creation of Networked 

Resources and Virtual Organizations. 

 The user community will work with tool 

providers as active collaborators to determine 

requirements and to serve as early users. Scientists, educators, students and other end users think 

of ways to use data and tools that the developers 

did not consider, finding problems and testing 

recovery paths by triggering unanticipated behavior. Most important, an engaged set of users and 

testers will also demonstrate the scientific value 

of data collections. The value of repositories and 

their standards-based input and output tools arises 

from the way in which they enable discoveries. 

Testing and feedback are necessary to meet the 

challenges presented by current datasets that will 

only increase in size, often by orders of magnitude, 

in the future. 

Finally, in addition to promoting the use of 

standards, tool and service developers will also 

promote the stability of standards. Continual 

changes to structure, access methods, and user 

interfaces mitigate against ease of use and against 

interoperability. Instead of altering a standard for 

a current need, developers will adjust their implementation of that need to fit within the standard. 

This is especially important for resource-limited 

research and education communities. 

C. Developing and Implementing Coherent 

Data Policies 

In setting priorities and making funding decisions, NSF is in a powerful position to influence data policy and management at research 

institutions. NSF’s policy position on data is 

straightforward: all science and engineering data 

generated with NSF funding must be made 

broadly accessible and usable, while being suitably 

protected and preserved. Through a suite of coherent policies designed to recognize different data 

needs and requirements within communities, NSF 

will promote open access to well-managed data, 

recognizing that this is essential to continued U.S. 

leadership in science and engineering.

In addition to addressing the technological challenges inherent in the creation of a national data 

framework, NSF’s data policies will be redesigned 

as necessary to mitigate existing sociological and 

cultural barriers to data sharing and access, and 

to bring them into accord across programs and 

ensure coherence. This will lead to the development of a suite of harmonized policy statements 

supporting data open access and usability. NSF’s 

actions will promote a change in culture such that 

the collection and deposition of all appropriate 

digital data and associated metadata become a 

matter of routine for investigators in all fields. This 

change will be encouraged through an NSF-wide 

requirement for data management plans in all 

proposals. These plans will be considered in the 

merit review process and will be actively monitored post-award.

Policy and management issues in data handling 

occur at every level, and there is an urgent need 

for rational agency, national and international 

strategies for sustainable access, organization and 

use. Discussions at the interagency level on issues 

associated with data policies and practices will be 

supported by a new interagency working group 

on digital data formed under the auspices of the 

Committee on Science of the National Science 

and Technology Council. This group will consider not only data challenges and opportunities 

discussed throughout this chapter, but especially 

the issues of cross-agency funding and access, the 

provision and preservation of data to and for other 

agencies, and monitoring agreements as agency 

imperatives change with time. Formal policies 

must be developed to address data quality and 

security, ethical and legal requirements, and technical and semantic interoperability issues that will 

arise throughout the complete process from collection and generation to analysis and dissemination. 

As already noted, many large science and engineering projects are international in scope, and 

thus national laws and international agreements 

directly affect data access and sharing practices. 

Differences arise over privacy and confidentiality, 

from cultural attitudes to ownership and use, in 

attitudes to intellectual property protection and its 

limits and exceptions, and because of national security concerns. Means by which to find common 

ground within the international community must 

continue to be explored. 

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I. New Frontiers in Science and 

Engineering Through Networked 

Resources and Virtual Organizations

With access to state-of-the-art cyberinfrastructure services, many researchers and indeed entire 

fields of science and engineering now share access 

to world-class resources spanning experimental 

facilities and field equipment, distributed instrumentation, sensor networks and arrays, mobile 

research platforms, HPC systems, data collections, 

sophisticated analysis and visualization facilities, 

and advanced simulation tools. The convergence 

of information, grid, and networking technologies 

with contemporary communications now enables 

science and engineering communities to pursue 

their research and learning goals in real-time and 

without regard to geography. In fact, the creation of end-to-end cyberinfrastructure systems 

– comprehensive networked resources – by groups 

of individuals with common interests is permitting 

the establishment of Virtual Organizations (VOs) 

that are revolutionizing the conduct of science and 

engineering research and education. A VO is created by a group of individuals whose members and 

resources may be dispersed geographically and/or 

temporally, yet who function as a coherent unit 

through the use of end-to-end cyberinfrastructure 

systems. These CI systems provide shared access 

to centralized or distributed resources and services, 

often in real-time. Such virtual organizations supporting distributed communities go by numerous 

names: collaboratory, co-laboratory, grid community, science gateway, science portal, and others.

During the past decade, NSF funding has 

catalyzed the creation of VOs across a broad 

spectrum of science and engineering fields, creating powerful and broadly accessible pathways to 

accelerate the transformation of research outcomes 

into knowledge, products, services, and new learning opportunities. With access to enabling tools 

and services, self-organizing communities can 

create end-to-end systems to: facilitate scientific 

workflows; collaborate on experimental designs; 

share information and knowledge; remotely operate instrumentation; run numerical simulations 

using computing resources ranging from desktop 

computers to HPC systems; archive, e-publish, 

access, mine, analyze, and visualize data; develop 

new computational models; and deliver unique 

learning and workforce development activities. 

Through VOs, researchers are exploring science 

and engineering phenomena in unprecedented 

ways. Scientists are now defining the structure of 

the North American lithosphere with an extraordinary level of detail through EarthScope, which 

integrates observational, analytical, telecommunications, and instrumentation technologies to investigate the structure and evolution of the North 

American continent and the physical processes 

controlling earthquakes and volcanic eruptions. 

The Integrated Primate Biomaterials and Information Resource assembles, characterizes, and 

distributes high-quality DNA samples of known 

provenance with accompanying demographic, 

geographic, and behavioral information to advance 

understanding of human origins, the biological 

basis of cognitive processes, evolutionary history and relationships, and social structure, and 

provides critical scientific information needed to 

facilitate conservation of biological diversity. The 

Time-sharing Experiments for the Social Sciences 

(TESS) allows researchers to run their own studies 

on random samples of the population that are 

interviewed via the Internet. By allowing social 

scientists to collect original data tailored to their 

own hypotheses, TESS increases the precision 

with which social science advances can be made. 

Through the Network for Earthquake Engineering 

Simulation (NEES), the coupling of high performance networks, advanced data management, 

distributed coordination and computational tools, 

and 15 experimental facilities enables engineering 

The GPS station shown on the opposite page monitors transform plate movement in California as part of 

EarthScope. The data collected will be compared with data from other GPS stations to better understand the 

interplay of faults in the region.

CHAPTER 4

VIRTUAL ORGANIZATIONS FOR DISTRIBUTED 

COMMUNITIES (2006-2010)
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The NEES@buffalo shake table recreates movements of the forces generated by an actual earthquake. NEES allows earthquake engineers and 

students located at different institutions to share resources, collaborate on testing, and exploit new computational technologies.

researchers to test larger scale and more comprehensive structural and geomaterial systems to 

create new design methodologies and technologies for reducing losses during earthquakes and 

tsunamis. 

This chapter describes the establishment of a 

national cyberinfrastructure framework into which 

the HPC environment described in Chapter 2 and 

the national data framework described in Chapter 3 are integrated, enabling the development, 

deployment, evolution, and sustainable support of 

end-to-end cyberinfrastructure systems that will 

serve as transformative agents for 21st century 

science and engineering discovery and learning, 

promoting shared use and interoperability across 

all fields. 

II. The Next Five Years: Establishing 

a Flexible, Open Cyberinfrastructure 

Framework for Virtual Organizations

NSF’s five-year goals are as follows:

To catalyze the development, implementation 

and evolution of a functionally complete national cyberinfrastructure that integrates both 

physical and cyberinfrastructure assets and 

services to support VOs.

To promote and support the establishment 

of world-class VOs that are secure, efficient, 

•

•

reliable, accessible, usable, pervasive, persistent 

and interoperable, and that are able to exploit 

the full range of research and education tools 

available at any given time.

To support the development of common 

cyberinfrastructure resources, services, and 

tools enabling the effective, efficient creation 

and operation of end-to-end cyberinfrastructure systems for and across all science and engineering fields, nationally and internationally.

The following principles will guide the agency’s 

FY 2006 through FY 2010 investments:

 

NSF’s investments in end-to-end cyberinfrastructure systems are driven by science and 

engineering opportunities and challenges. 

Common needs and opportunities are identified to improve the cost-effectiveness of NSF 

investments and to enhance interoperability.

NSF investments promote equitable provision 

of and access to all types of physical, digital, 

and human resources to ensure the broadest 

participation of individuals with interest in science and engineering inquiry and learning. 

Existing projects and programs inform future 

investments, serving as a resource and knowledge base.

End-to-end cyberinfrastructure systems are ap-

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•

•

•

•
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A digital optical module is lowered into a hole over 1,450 meters deep 

in the ice at South Pole station. These sensors are deployed as part of 

the IceCube international collaboration to further understanding of the 

Universe by finding evidence of high energy subatomic particles.

propriately reliable, robust, and persistent such 

that end users can depend on them to achieve 

their research and education goals.

NSF partners with relevant stakeholders, 

including academe, industry, other federal 

agencies, and other public and private sector 

organizations, both foreign and domestic.

Tools and services are networked together in 

a flexible architecture using standard, open 

protocols and interfaces, designed to support 

the creation and operation of robust networked 

resources and VOs across the scientific and 

engineering disciplines supported by NSF.

The cyberinfrastructure framework developed 

will integrate widely accessible, common cyberinfrastructure resources, services, and tools, such as 

those described in other chapters in this document, enabling individuals, groups and communities to efficiently design, develop, deploy, and 

operate flexible, customizable networked resources 

and VOs to advance science and engineering. 

In facilitating the creation and support of effective virtual organizations, NSF will focus on 

three essential elements: the creation of a common 

technological framework that promotes seamless, 

secure integration across a wide range of shared, 

geographically-distributed resources; the establishment of an operational framework built on productive and accountable partnerships developed 

among system architects, developers, providers, 

•

•

operators, and end users who span multiple communities; and the establishment of an effective 

assessment and evaluation plan that will inform 

the agency’s ongoing investments in cyberinfrastructure for the foreseeable future. 

A. Open Technological Framework

To facilitate the development of an open technological framework, NSF will support cyberinfrastructure software service providers to develop, 

integrate, deploy, and support reliable, robust, and 

interoperable software. Software essential to the 

creation of networked resources and VOs encompasses a broad range of functionalities and services, 

including enabling middleware; domain-specific 

software and application codes; teleobservation 

and teleoperation tools to enable remote access to 

experimental facilities, instruments, and sensors; 

collaborative tools for experimental planning, 

execution, and post-analysis; workflow tools and 

processes; system monitoring and management; 

user support; web portals to simulation software 

and domain-specific community code repositories; 

and flexible user interfaces to enable discovery and 

learning. 

Many of the projects listed in Appendix E 

have produced fundamental software and/or new 

integrated environments to support interdisciplinary research and education. NSF’s strategy 

leverages this body of work, harvesting promising 

tools and technologies that have been developed 

to a research prototype stage, and further hardening, generalizing, and making them available for 

use by multiple individuals and/or communities. 

For example, many communities require access to 

services that build scientific workflows and rich 

orchestration tools, and to integrate the intensive 

computing and data capabilities described in 

Chapters 2 and 3, respectively, into collaborative 

and productive working environments. While 

work has already been done to develop and deploy 

components and packages of needed software 

through NSF and other support, existing software 

needs to be hardened, maintained and evolved. 

New software and enhancements to existing software must be developed as new uses and new user 

requirements continue to emerge. 

Cybersecurity pervades all aspects of end-to-end 

cyberinfrastructure systems and Virtual Organizations, and includes human, data, software and 

facilities elements. Security requires coordination, 

the development of trust, and rule setting through 
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community governance. NSF will require 

awardees developing, deploying and supporting 

networked resources and virtual organizations to 

develop and apply robust cybersecurity policies 

and procedures, thereby promoting a conscientious and consistent approach to cybersecurity. 

The agency will support development of strong 

authentication and authorization technologies and 

procedures for individuals, groups, VOs, and other 

role-based identities. In so doing, the agency will 

leverage research prototypes and new technologies 

produced in the Cyber Trust program, the U.S. 

government’s flagship program in cybersecurity 

research and development. 

Interoperable, open technology standards will 

be used as the primary mechanism to support 

the further development of interoperable, open, 

extensible networked resources and VOs. Ideally, 

standards for data representation and communication, connection of computing resources, authentication, authorization, and access should be 

open, internationally employed, and accepted by 

multiple research and education communities. 

Where appropriate, conventions that are employed internationally should be favored. The use 

of standards creates economies of scale and scope 

for developing and deploying common resources, 

tools, software, and services that enhance the use 

of cyberinfrastructure in multiple science and 

engineering communities. This approach allows 

maximum interoperability and sharing of best 

practices. A standards-based approach will ensure 

that access to cyberinfrastructure will be independent of operating systems; ubiquitous, and open 

to large and small institutions. Together, web services and service-oriented architectures are emerging as a standard framework for interoperability 

among various software applications on different 

platforms. They provide important characteristics 

such as standardized and well-defined interfaces 

and protocols, ease of development, and reuse of 

services and components, making them potential 

central facets of the cyberinfrastructure software 

ecosystem.

The Ocean Observatories Initiative promises to provide the ocean sciences research community sustained, 

long-term and adaptive measurements in the oceans via a fully operational research observatory system.
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HPWREN, a high performance wireless research network, expands 

the reach of cyberinfrastructure into remote environments in and surrounding San Diego County to support a range of science, engineering, 

education, and emergency response initiatives.

B. Operational Framework 

NSF will promote the development of partnerships to facilitate the sharing and integration of 

distributed technological components deployed 

and supported at national, international, regional, 

local, community, and campus levels. Significant 

resources already exist at the academic institution 

level. It is important to integrate such resources 

into the national cyberinfrastructure fabric.

In addition, NSF will encourage partnerships 

with industry to develop, maintain and share 

robust, production-quality software tools and 

services and to leverage commercially available 

software. NSF will engage commercial software 

providers to identify value propositions, to identify software needs specific to the research and 

education community, and to facilitate technology 

transfer to industry, where appropriate. Efforts to 

ensure that NSF cyberinfrastructure investments 

complement those of other federal agencies will be 

intensified. 

With the increasing globalization of science and 

engineering and its attendant cyberinfrastructure, 

NSF supports international efforts of strategic interest. NSF will endeavor to: (i) facilitate U.S. researchers’ collaboration with international partners 

through cyberinfrastructure; (ii) identify exemplars 

of international collaboration and partnerships, 

utilizing cyberinfrastructure, that offer efficient 

and beneficial relationships and build on these; 

and (iii) encourage international collaboration in 

the development of cyberinfrastructure.

The cost-effective penetration of cyberinfrastructure into all aspects of research and education 

will require the full engagement of the broad science and engineering community. Incorporating 

the contributions from multiple communities and 

reconciling their interests is one of the major challenges ahead. Community proxies must be identified and empowered to find common interests to 

avoid duplication of effort and to minimize the 

balkanization of science and engineering.

C. Evaluation and Assessment 

Cyberinfrastructure is dramatically altering the 

conduct of science and engineering research and 

education. Accordingly, studying the evolution 

and impact of cyberinfrastructure on the culture 

and conduct of research and education within and 

across communities of practice is essential. NSF 

will also support projects that study how ongoing 

and future cyberinfrastructure efforts might be 

informed by lessons learned and by the identification of promising practices. Among other things, 

NSF seeks to build a stronger foundation in our 

understanding of how individuals, teams and communities most effectively interact with cyberinfrastructure; how to design the critical governance 

and management structures for the new types of 

organizations arising; and, how to improve the 

allocation of Cyberinfrastructure resources and 

design incentives for its optimal use. These types 

of activities will be essential to the agency’s overall 

success. NSF will support studies of the evolution 

and impact of cyberinfrastructure on the culture 

and conduct of research and education within and 

across different research and education communities. It will also encourage systemic design of 

virtual organizations with embedded evaluation to 

better address the complex interaction of technological and social issues with the user community.

The rapidly evolving nature of cyberinfrastructure requires ongoing assessment of current and 

future user requirements. Comprehensive user 

assessments will be conducted and will include 

identification and evaluation of how the physical 

infrastructure, networking needs and capabilities, collaborative tools, software requirements, 

and data resources affect the ability of scientists 

and engineers to conduct transformative research 

and provide rich learning and workforce development environments. Other issues to be addressed 

include the degree to which cyberinfrastructure 

facilitates federated inquiry, interoperability, and 

the development of common standards and new 

social norms. 

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I. Cyberinfrastructure and Learning

Cyberinfrastructure moves us beyond the oldschool model of teachers/students and classrooms/

labs. Ubiquitous learning environments now 

will encompass classrooms, laboratories, libraries, 

galleries, museums, zoos, workplaces, homes and 

many other locations. Under this transformation, 

well-established components of education—preschool, K-12 and post-secondary—become 

highly leveraged elements of a more open learning 

world where people learn as a routine part of life, 

throughout their lives. 

Cyberinfrastructure is enabling powerful opportunities: i) to collaborate, ii) to model and 

visualize complex scientific and engineering 

concepts, iii) to create and discover scientific and 

educational resources for use in a variety of settings, both formal and informal, iv) to assess learning gains, and v) to personalize learning environments. These changes both demand and support 

a new level of technical competence in the science 

and engineering workforce and in our citizenry 

at large. Imagine an interdisciplinary course in 

the design and construction of large public works 

projects, attracting student-faculty teams from 

different engineering disciplines, urban planning, 

environmental science, and economics; and from 

around the globe. To develop their understanding, the students combine relatively small selfcontained digital simulations that capture both 

simple behavior and geometry to model more 

complex scientific and engineering phenomena. 

Modules share inputs and outputs and otherwise 

interoperate. These “building blocks” maintain 

sensitivity across multiple scales of phenomena. 

For example, component models of transportation 

subsystems from one site combine with structural 

and geotechnical models from other collections 

to simulate dynamic loading within a complex 

bridge and tunnel environment. Computational 

models from faculty research efforts are used to 

generate numerical data sets for comparison with 

data from physical observations of real transportation systems obtained from various (international) 

locations via access to remote instrumentation. 

Furthermore, learners explore influences on air 

quality and tap into the expertise of practicing 

environmental scientists through either real-time 

or asynchronous communication. This networked 

learning environment increases the impact and 

accessibility of all resources by allowing students 

to search for and discover content, to assemble 

curricular and learning modules from component 

pieces in a flexible manner, and to communicate 

and collaborate with others, leading to a deep 

change in the relationship between students 

and knowledge. Indeed, students experience the 

profound changes in the practice of science and 

engineering and the nature of inquiry that cyberinfrastructure provokes. 

II. Building Capacity for Creation and 

Use of Cyberinfrastructure

To realize these radical changes in the processes 

of learning and discovery, networked resources also 

demand a new level of technical competence from 

the nation’s workforce and citizenry. Indeed, NSF 

envisions a spectrum of new learning needs and 

activities demanded by individuals, from future 

researchers, to members of the technical cyberinfrastructure workforce, to the citizen at large.

As cyberinfrastructure tools grow more accessible, students at the secondary school and 

undergraduate levels increasingly use them in their 

learning endeavors, in many cases serving as early 

adopters of emergent cyberinfrastructure. Already, these tools facilitate communication across 

disciplinary, organizational, and international and 

cultural barriers, and their use is characteristic of 

the new globally-engaged researcher. Moreover, 

the new tools and functionality of cyberinfrastrucWeather recording equipment used in Jornada Range studies is part of the LTER Network, involving more than 

1800 scientists and students at 26 different sites investigating ecological processes over long temporal and 

broad spatial scales. These researchers in southern New Mexico are studying the causes and consequences of 

desertification.

CHAPTER 5 

Learning and Workforce Development 

(2006-2010)
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

Undergraduate students participate in research projects in 

solar and space physics using remote and local facilities such 

as the Prairie View Solar Observatory.

ture are transforming the very nature of scientific 

inquiry and scholarship. New methods to observe 

and to acquire data, manipulate it, and represent 

it, challenge the traditional discipline-based graduate curricula. Increasingly the tools of cyberinfrastructure must be incorporated within the context 

of interdisciplinary research. Indeed, these tools 

and approaches are helping to make possible new 

methods of inquiry that allow understanding in 

one area of science to promote insight in another, thus defining new interdisciplinary areas of 

research reflecting the complex nature of modern 

science and engineering problems. Furthermore, as 

data are increasingly “born digital,” the ephemeral nature of data sources themselves raises new 

dimensions on the issues of preservation and 

stewardship. 

To employ the tools and capabilities of cyberinfrastructure-enabled learning environments 

effectively, teachers and faculty must also have 

continued professional development opportunities. For example, teachers and faculty must learn 

to use new assessment techniques and practices enabled by cyberinfrastructure, including the tailoring of feedback to the individual, and the creation 

of personalized portfolios of student learning 

that capture a record of conceptual learning gains 

over time. Undergraduate curricula must also be 

reinvented to exploit emerging cyberinfrastructure 

capabilities. The full engagement of students is 

vitally important since they are in a special position to inspire future students with the excitement 

and understanding of cyberinfrastructure-enabled 

scientific inquiry and learning. 

Ongoing attention must be paid to the education of the professionals who will support, deploy, 

develop, and design current and emerging cyberinfrastructure. For example, the increased emphasis 

on “data rich” scientific inquiry has revealed serious needs for “digital data management” or data 

curation professionals. Such careers may involve 

the development of new, hybrid degree programs 

that marry the study of library science with a 

scientific discipline. Similarly, the power that visualization and other presentation technologies bring 

to the interpretation of data may call for specialized career opportunities that pair the graphic arts 

with a science or engineering discipline.

Cyberinfrastucture’s impact on the conduct of 

business demands that members of the workforce 

have the capability at least to refresh if not also 

retool their skills. In some cases the maintenance 

of formal professional certifications to practice is 

a driver, and in other cases the need for continual workplace learning is driven by pressures to 

remain competitive and/or relevant to a sector’s 

needs. Adequate cyberinfrastructure must be 

present to support such intentional workforce 

development.

Cyberinfrastructure extends the impact of 

science to citizens at large by enhancing communication about scientific inquiry and outcomes to 

the lay public. Such informal learning opportunities answer numerous needs, including those of 

parents involved with their children’s schooling 

and adults involved with community development 

needs that have scientific dimensions. Moreover, 

cyberinfrastructure enables lifelong learning opportunities as it supports the direct involvement 

by citizens in distributed scientific inquiry such as 

contributing to the digital sky survey.
Cyberinfrastructure Vision

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National Science Foundation March 2007

The JASON Project uses cyberinfrastructure to connect middle 

school students with great explorers and great events to inspire 

and motivate them to learn science.

- 39 -

III. Using Cyberinfrastructure to 

Enhance Learning

Just as cyberinfrastructure changes the needs 

and roles of the individual learner, NSF also envisions it changing the organizational enterprise of 

learning. Two intertwined assumptions underlie 

this vision. First, “online” will be the dominant 

operating mode for individuals, characterizing how individuals interact with educational 

resources and complementing how they interact 

with each other. Second, ubiquitous (or pervasive) 

CI will extend awareness of our physical and social 

environment, with embedded smart sensors and 

“device to device” communication becoming the 

norm. Moreover, the shift from wired to wireless will untether the learner from fixed formal 

educational settings and enable “on demand/on 

location” learning whether at home, in the field, in 

the laboratory, or at the worksite, locally or across 

the globe. 

These conditions permit new learning organizations to form, raising in turn new research questions about the creation, operation, and persistence of communities of practice and learning. In 

such cyberlearning networks people will connect 

to learn with each other, even as they learn to connect with each other, to exploit increasingly shared 

knowledge and engage in participatory inquiry. 

Cyberinfrastructure is also a driving movement to 

more open educational resources, for example, the 

growing Open Courseware project now includes 

over a hundred international universities.

To support this vision of (massively) networked 

learning, cyberinfrastructure must be adaptive and 

agile − in short, a dynamic ecosystem that supports interactive, participatory modes of learning 

and inquiry, and that can respond flexibly to the 

infusion of new technology. 

IV. The Next Five Years: Learning 

About and With Cyberinfrastructure

NSF’s five-year goals are as follows:

To foster the broad deployment and utilization 

of Cyberinfrastructure-enabled learning and 

research environments.

To support the development of new skills and 

professions needed for full realization of CIenabled opportunities.

To promote broad participation of underserved 

groups, communities and institutions, both as 

creators and users of CI. 

To stimulate new developments and continual 

improvements of cyberinfrastructure-enabled 

learning and research environments.

To facilitate cyberinfrastructure-enabled 

lifelong learning opportunities ranging from 

the enhancement of public understanding of 

science to meeting the needs of the workforce 

seeking continuing professional development.

The following principles will guide the agency’s 

FY 2006 through FY 2010 investments:

Equitable and broad access to state-of-the-art 

networked resources is essential.

To achieve widespread use of cyberinfrastructure by science and engineering researchers, 

educators, and learners, efficient methods must 

exist to find, access and use cyberinfrastructure 

resources, tools, and services as well as the educational materials associated with them. 

The privacy, social, cultural, ethical and ownership issues associated with increasing use of 

cyberinfrastructure for learning, research and 

scholarship must be addressed.

Learning and workforce development opportunities contribute to cyberinfrastructure 

developments.

Cyberinfrastructure developments will lead 

to new learning models necessary for lifelong 

•

•

•

•

•

•

•

•

•

•
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

Georgia Institute of Technology and NRL researchers have developed improved methods for directly writing nanometerscale patterns onto a variety of surfaces. Atomic force microscopy generated images are used to analyze nanometer-scale 

structures.

learning in the distributed and networked 

learning environment.

Leveraging cyberinfrastructure LWD activities and investments within NSF and by other 

agencies – national and international – are 

essential for enabling 21st century science and 

engineering. 

Scientists and engineers must be prepared to 

collaborate across disciplinary, institutional, 

geopolitical and cultural boundaries using 

cyberinfrastructure-mediated tools.

Current and future generations of scientists, 

engineers and educators will utilize cyberinfrastructure-enabled learning and research environments for their formal and informal educational 

training, research projects, career development and 

lifelong learning. Therefore, NSF will develop and 

implement strategies for their deployment and 

utilization. To do so, NSF will stimulate awareness of cyberinfrastructure-enabled learning and 

research environments for scientists, engineers and 

educators; enhance usability and adaptability of 

cyberinfrastructure-enabled learning and research 

environments for current and future generations 

of scientists, engineers and educators both nationally and internationally; promote new approaches 

to and integration of cyberinfrastructure-enabled 

learning and research environments for educational and research usage nationally and inter-

•

•

nationally; and foster incorporation of solutions 

for addressing privacy, ethical and social issues in 

cyberinfrastructure-enabled learning and research 

environments.

It is very likely that new disciplines will develop 

as a natural outgrowth of the advances in cyberinfrastructure. NSF will be an enabler in developing 

the workforce in these newly-formed disciplines. 

These disciplines could be as important as the 

relatively new disciplines of computer science, 

mathematical biology, genomics, environmental 

sciences and astrophysics are today. NSF will 

support mechanisms for development of new 

cyberinfrastructure-related curricula at all levels; 

stimulate partnerships – domestic and international – between and among academic institutions and 

industrial cyberinfrastructure-professionals, and 

support the wide dissemination of “best practices” 

in cyberinfrastructure workforce development.

Cyberinfrastructure has the potential to enable 

a larger and more diverse set of individuals and 

institutions to participate in science and engineering education, research and innovation. To realize 

this potential, NSF will strategically design and 

implement programs that recognize the needs of 

those who might not have the means to utilize CI 

in science and engineering research and education. 

To do so, NSF will identify and address barriers to 

utilization of cyberinfrastructure tools and 
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

A visualization of the changing structure of the satellite tobacco mosaic virus is produced 

on the NCSA Cobalt System by calculating how each of the one million atoms interacted 

with each other every femtosecond.

resources; promote the training of faculty, particularly those in minority-serving institutions, 

predominantly undergraduate institutions and 

community colleges; and encourage programs 

to integrate innovative methods of teaching and 

learning using cybertools (particularly in innercity, rural and remote classrooms), including taking advantage of international networked resources 

to prepare a globally engaged workforce.

In the dynamic environment of cyberinfrastructure-enabled learning and research, NSF will 

facilitate new developments as well as continuous improvements of the currently available tools 

and services, including those for education and 

training. NSF will support research that increases 

understanding of how students, teachers, scientists 

and engineers work and learn in a cyberinfrastructure rich environment, for example, interactive 

gaming, simulation and modeling (as opposed to 

conventional instruction methods). The agency 

will support the development of methods to embed relevant data collection and analysis tools in 

cyberinfrastructure-based environments in order 

to assess, for example, satisfaction, usability, utility, 

productivity, etc., as well as the development of 

specific means for tracking student progress in 

content-based cyberinfrastructure learning; 

promote the development of technological solutions for addressing privacy, ethical and social 

issues in cyberinfrastructure-enabled learning and 

research environments; and stimulate both domestic and international partnerships to identify best 

practices in cyberinfrastructure enabled learning 

and research environments.

Lifelong learning, through both formal and 

informal mechanisms, will be an essential part of 

the workforce of a cyberinfrastructure-enabled 

society. NSF can play a crucial role by promoting and sustaining programs that exploit existing 

resources and encourage creation of new resources 

in order to continually improve the science literacy of society in general and of the science and 

engineering workforce in particular. NSF will 

support mechanisms for professionals to continuously update their cyberinfrastructure skills and 

competencies; catalyze the development of new 

lifelong learning networked resources; promote 

new knowledge communities and networks that 

take advantage of cyberinfrastructure to provide 

new learning experiences; support programs that 

bridge pre- and post-professional (lifelong) learning; and encourage programs that promote public 

awareness of, and literacy in, cyberinfrastructure.

Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

The simulation on the opposite page, run by Louisiana State University astrophysicists on the NCSA Tungsten system, 

shows two stars in a binary system during a late phase of their evolution. The more massive star (top) has transferred 

a significant fraction of its mass to its companion and the two stars are undergoing a catastrophic merger. 

Appendix A: ACRONYMS

2MASS Two Micron All Sky Survey

CAIDA Cooperative Association for Internet Data Analysis

CALIT2 California Institute for Telecommunications and Information Technology

CAVE Cave Automatic Virtual Environment

CCSDS Consultative Committee for Space Data Standards

CHARMM Chemistry at Harvard Macromolecular Mechanics

CI Cyberinfrastructure

CIC Cyberinfrastructure Council

CIO Chief Information Officer

CMS Compact Muon Solenoid

CODATA Committee on Data for Science and Technology

CPU Central Processing Unit

CSNET Computer Science Network

CT Computed Tomography

DANSE Data Analysis for Neutron Scattering Experiments

DARPA Defense Advanced Research Projects Agency

DNA Deoxyribonucleic Acid

DOD Department of Defense

DOE Department of Energy

ETF Extensible Terascale Facility

FLOPS Floating point operations/sec

GPS Global Positioning System

HBCU Historically Black Colleges and Universities

HPC High Performance Computing

HPCMOD DOD’s High-Performance Computing Modernization program

HPCS DARPA’s High Productivity Computing Systems program

HPCC High-Performance Computing and Communications

HPWREN High Performance Wireless Research and Education Network

GEON Geosciences Network

GLORIAD Global Ring Network for Advanced Applications Development

GriPhyN Grid Physics Network

ICPSR Inter-university Consortium for Political and Social Research

ICSU International Council for Science

ICSTI International Council for Scientific and Technical Information

IRIS Incorporated Research Institutions for Seismology

ISO International Organization of Standardization

IT Information Technology

ITR Information Technology Research

IVDGL International Virtual Data Grid Laboratory

LIGO Laser Interferometer Gravitational Wave Observatory

LTER Long Term Ecological Research

LWD Learning and Workforce Development

MPI Message Passing Interface

MREFC Major Research Equipment and Facilities Construction

NARA National Archives and Records Administration

NASA National Aeronautics and Space Administration

NCAR National Center for Atmospheric Research
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

NCSA National Center for Supercomputing Applications

NEES Network for Earthquake Engineering Simulation

NEON National Ecological Observatory Network

NIH National Institutes of Health

NITRD Networking and Information Technology Research and Development

NNSA National Nuclear Security Administration

NREL National Renewable Energy Laboratory

NRL Naval Research Laboratory

NSFNET NSF Network

NRC National Research Council

NSB National Science Board

NSF National Science Foundation

OAIS Open Archival Information System

OOI Ocean Observatories Initiative

OS Operating System

PACI Partnership for Advanced Computational Infrastructure

PDB Protein Data Bank

PITAC President’s Information Technology Advisory Committee

RCSB Research Collaboratory for Structural Bioinformatics

RLG Research Library Group

RNA Ribonucleic Acid

SciDAC Scientific Discovery through Advanced Computing

SDSC San Diego Supercomputer Center

SNS Spallation Neutron Source

SSP Software Services Provider

TESS Time-sharing Experiments for the Social Sciences

TFLOPS Teraflops: Trillion floating point operations/sec

USNC/ U.S. National Committee for CODATA

CODATA

vBNS very high speed Backbone Network Service

VO Virtual Organization

WDC World Data Center
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

Building a Cyberinfrastructure for the Biological Sciences; workshop held July 14-15, 2003; 

information available at http://research.calit2.

net/cibio/archived/CIBIO_FINAL.pdf and http://

research.calit2.net/cibio/report.htm 

CHE Cyber Chemistry Workshop; workshop 

held October 3-5, 2004; information available at 

http://bioeng.berkeley.edu/faculty/cyber_workshop/ 

Commission on Cyberinfrastructure for the 

Humanities and Social Sciences; sponsored by 

the American Council of Learned Societies; seven 

public information-gathering events held in 2004; 

report in preparation; information available at 

http://www.acls.org/cyberinfrastructure/cyber.htm

Community Climate System Model Strategic 

Business Plan (2003), June 2003, 28 pp; information available at http://www.ccsm.ucar.edu/management/busplan2004-2008.pdf

Community Climate System Model Science 

Plan 2004-2008 (2003), June 2003, 76 pp; 

information available at http://www.ccsm.ucar.

edu/management/sciplan2004-2008.pdf

Computation as a Tool for Discovery in Physics; 

report by the Steering Committee on Computational Physics: information available at http://

www.nsf.gov/pubs/2002/nsf02176/start.htm 

Cyberinfrastructure for the Atmospheric Sciences in the 21st Century; workshop held June 

2004; information available at http://gladiator.

ncsa.uiuc.edu/PDFs/nsf/cyrdas_report_final.pdf 

Cyberinfrastructure for Engineering Research 

and Education; workshop held June 5 – 6, 2003; 

information available at http://www.nsf.gov/eng/

general/Workshop/cyberinfrastructure/index.jsp

Cyberinfrastructure for Environmental Research 

and Education (2003); workshop held October 

30 – November 1, 2002; information available at 

http://www.ncar.ucar.edu/cyber/cyberreport.pdf

Cyberinfrastructure (CI) for the Integrated 

Solid Earth Sciences (ISES) (June 2003); workshop held on March 28-29, 2003;, June 2003; 

information available at http://www.paleostrat.

org/Documents/ises-ci%202003.pdf 

Cyberinfrastructure and the Next Wave of 

Collaboration; D.E. Atkins, Keynote for EDUCAUSE, held April 2005; information available at 

http://www.educause2005.auckland.ac.nz/interactive/presentations/Atkins.pdf

Cyberinfrastructure needs for environmental 

observatories; information available at http://www.

orionprogram.org/office/NSFCyberWkshp.html

Cyberinfrastructure Research for Homeland 

Security; February 26-27, 2003; information available at web.calit2.net/RiskReduction/crhsdraft.pdf 

Cyberlearning Workshop Series; workshops 

held Fall 2004 – Spring 2005 by the Computing 

Research Association (CRA) and the International 

Society of the Learning Sciences (ISLS); information available at http://www.cra.org/Activities/

workshops/cyberlearning

Data Management for Marine Geology and 

Geophysics: Tools for Archiving, Analysis, and 

Visualization (2001); information available at 

http://humm.whoi.edu/DBMWorkshop/data_

mgt_report.hi.pdf 

Environmental Cyberinfrastructure Needs For 

Distributed Sensor Networks; workshop held 

August 12-14, 2003; information available at 

http://www.lternet.edu/sensor_report

Establishing a Petascale Collaboratory for the 

Geosciences: Scientific Frontiers Report, July 

2005, information available at http://www.geoprose.com/projects/petascale_science.html 

EXchanging CyberInfrastructure Themes in 

Engineering Design; Report for NSF EXCITED 

workshop, held February 28 – March 1, 2005; 

information available at http://www.mne.psu.

edu/simpson/NSF/EXCITED/

Federal Plan for High-End Computing (2004); 

72 pp; information available at http://www.ostp.

gov/nstc/html/HECRTF-FINAL_051004.pdf

APPENDIX B: 

REPRESENTATIVE REPORTS AND WORKSHOPS
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

Final Report: NSF SBE-CISE Workshop on 

Cyberinfrastructure and the Social Sciences, F. 

Berman and H. Brady, held May 12, 2005; information available at http://vis.sdsc.edu/sbe/reports/

SBE-CISE-FINAL.pdf

From Cyberinfrastructure to Cyberdiscovery in 

Materials Science: Enhancing outcomes in materials research, education and outreach, August 3-5, 

2006; information available at http://www.mcc.

uiuc.edu/nsf/ciw_2006/

Geoinformatics: Building Cyberinfrastructure 

for the Earth Sciences (2004); workshop held May 

14 – 15, 2003; Kansas Geological Survey Report 

2004-48; information available at http://www.

geoinformatics.info 

Geoscience Education and Cyberinfrastructure, Digital Library for Earth System Education, 

(2004); workshop held April 19-20, 2004; information available at http://www.dlese.org/documents/reports/GeoEd-CI.pdf

Getting Up to Speed: The Future of Supercomputing (2004). 308 pp; information available at 

http://www.nap.edu/books/0309095026/html/ or 

http://www7.nationalacademies.org/cstb/pub_supercomp.html 

High-Performance Computing Requirements 

for the Computational Solid Earth Sciences 

(2005); 96 pp; information available at http://

www.geo-prose.com/computational_SES.html 

High-Performance Computing in the Geosciences Workshop Report. September 25-27, 2006, 

information available at http://www.ncar.ucar.

edu/Director/dcworkshop/HPCGEO_workshop_

report_FINAL.pdf

Identifying Major Scientific Challenges in the 

Mathematical and Physical Sciences and their 

CyberInfrastructure Needs, workshop held April 

21, 2004; information available at http://www.nsf.

gov/attachments/100811/public/CyberscienceFinal4.pdf

Improving the effectiveness of U.S. Climate 

modeling, Commission on Geosciences, Environment and Resources (2001). National 

Academy Press, Washington, D.C., 144 pp; 

information available at http://www.nap.edu/

books/0309072573/html/

GEON: Developing the Cyberinfrastructure for 

the Earth Sciences A Workshop Report on Intrusive Igneous Rocks, Wilson Cycle and Concept 

Spaces; information available at http://geon.geol.

vt.edu/geon/pubreps/workshop.pdf

An Information Technology Infrastructure 

Plan to Advance Ocean Sciences (2002). 80 pp; 

information available at http://www.geo-prose.

com/oiti/index.html 

Materials Research Cyberscience enabled by 

Cyberinfrastructure; workshop held June 17 – 19, 

2004; information available at http://www.nsf.

gov/mps/dmr/csci.pdf

Multi-disciplinary Workshop at the Interface 

of Cyberinfrastructure, and Operations Research, 

with “Grand Challenges” in Enterprise-wide Applications in Design, Manufacturing and Services; 

workshop held August 31 - September 1, 2004; 

information available at https://engineering.purdue.edu/PRECISE/CI-OR/index.html 

Multiscale Mathematics Initiative: A Roadmap; 

workshops held May 3-5, July 20-22, September 

21-23, 2004; information available at http://www.

si.umich.edu/InfrastructureWorkshop/documents/

NSF_2004_CIMultiscaleMath.pdf

NIH/NSF Spring 2005 Workshop on Visualization Research Challenges; workshop held on May 

2-3, 2005; information available at http://www.

sci.utah.edu/vrc2005/index.html

NSF Conceptual Design Review Panel for the 

Ocean Observatories Initiative, August 14-17, 

2006; information available at http://www.orionprogram.org/capabilities/cdr/default.html

NSF EPSCoR Cyberinfrastructure Workshop, 

May 10-12, 2006; information available at http://

ciworkshop.utsi.edu/NSF_CI_WkshpReport_Final.pdf 

NSF Workshop for a Plant Cyberinfrastructure 

Center, October 17-18, 2005; information available at http://www.arabidopsis.org/portals/masc/

masc_docs/masc_wk_rep.jsp 
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

An Operations Cyberinfrastructure: Using 

Cyberinfrastructure and Operations Research to 

Improve Productivity in American Enterprises; 

workshop held August 30 – 31, 2004; information 

available at http://www.optimization-online.org/

OCI/OCI.doc; http://www.optimization-online.

org/OCI/OCI.pdf 

Petascale Computing in the Biological Sciences, 

Workshop Report, Edited by: Allan Snavely, Gwen 

Jacobs, and David A. Bader, August 29-30, 2006: 

information available at http://www.sdsc.edu/

PMaC/BioScience_Workshop/Publications/PetascaleBIOworkshopreport.pdf

Planning for Cyberinfrastructure Software 

(2005); workshop held October 5 – 6, 2004; information available at http://www.nsf.gov/od/oci/

ci_workshop/workshopreport_final_rev2a.pdf 

 Preparing for the Revolution: Information 

Technology and the Future of the Research University (2002); NRC Policy and Global Affairs, 

80 pp; information available at http://www.nap.

edu/catalog/10545.html

Polar Science and Advanced Networking: workshop held on April 24 - 26, 2003; sponsored by 

OPP/CISE; information available at http://www.

polar.umcs.maine.edu

Recurring Surveys: Issues and Opportunities: 

workshop held March 28-29, 2003; information 

available at www.nsf.gov/sbe/ses/mms/nsf04_

211a.pdf (2004)

Report of the High Performance Computing 

Town Hall Meeting: Science, Requirements, and 

Benchmarks; October 17, 2005; information 

available at http://www.mcc.uiuc.edu/nsfhpc/ 

Report on the NSF Workshop on Cyber-Based 

Combustion Science, April 19-20, 2006; information available at http://www.nsf-combustion.umd.

edu/final_report.php

Research Opportunities in CyberEngineering/

CyberInfrastructure; workshop held April 22 - 23, 

2004; information available at http://thor.cae.

drexel.edu/~workshop/

Revolutionizing Science and Engineering 

Through Cyberinfrastructure: report of the National Science Foundation Blue-Ribbon Advisory 

Panel on Cyberinfrastructure; Daniel E. Atkins 

(Chair), January 2003; information available at 

http://www.nsf.gov/cise/sci/reports/atkins.pdf

Roadmap for the Revitalization of High-End 

Computing (June 16-18, 2003); information 

available at http://www.cra.org/reports/supercomputing.pdf 

Science-Based Case for Large-Scale Simulation; 

workshop held June 24-25, 2003; information 

available at http://www.pnl.gov/scales/docs/volume1_72dpi.pdf; http://www.pnl.gov/scales/docs/

SCaLeS_v2_draft_toc.pdf 

Summit on Digital Tools for the Humanities 

Report; workshop held September 28-30, 2005; 

information available at http://www.iath.virginia.

edu/dtsummit/SummitText.pdf 

Supplement to the President’s Budget for FY 

2007; Report by the Subcommittee on Networking and Information Technology Research and 

Development (NITRD), February 2006; information available at http://www.nitrd.gov/pubs/

2007supplement/ 

Trends in IT Infrastructure in the Ocean Sciences (2004); workshop held May 21-23, 2003; 

information available at http://www.geo-prose.

com/oceans_iti_trends/oceans_iti_trends_rpt.pdf 

Understanding Infrastructure: Dynamics, Tensions, and Design, Report of An NSF Workshop 

on History and Theory of Infrastructure: Lessons 

for New Scientific Cyberinfrastructure, held September 2006; information available at http://www.

si.umich.edu/cyber-infrastructure/UnderstandingInfrastructure_FinalReport25jan07.pdf 

Workshop on Challenges of Scientific Workflows; held May 1-2, 2006; information available 

at http://vtcpc.isi.edu/wiki/index.php/Main_Page 

Workshop on Cyberinfrastructure in Chemical 

and Biological Process Systems: Impact and Directions; workshop held September 25-26, 2006; 

information available at http://www.oit.ucla.

edu/nsfci/NSFCIFullReport.pdf
Cyberinfrastructure Vision

for 21st Century Discovery

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National Science Foundation March 2007

NSF’s early investments in what has now become 

known as cyberinfrastructure date back almost to 

the agency’s inception. In the 1960s and 1970s, 

the agency supported a number of campus-based 

computing facilities. As computational methodologies became increasingly essential to the 

research endeavor, the science and engineering 

community began to call for NSF investments in 

specialized, higher capability computing facilities 

that would meet the computational needs of the 

broad national community. As a consequence, 

NSF’s Supercomputer Centers program was initiated in 1985 through the agency’s support of five 

academic-based supercomputer centers. 

During the 1980s, academic-based networking 

activities also flourished. Networking technologies 

were expected to improve the effectiveness and 

efficiency of researchers and educators, providing 

enhanced, easy access to computer resources and 

more effective transfer and sharing of information 

and knowledge. After demonstrating the potential 

of Computer Science Network (CSNET) in linking computer science departments, NSF moved on 

to develop the high-speed backbone, called NSF 

Network (NSFNET), with the five supercomputer centers supported under the Supercomputer 

Centers program and the National Center for 

Atmospheric Research becoming the first nodes 

on the backbone. NSF support also encouraged 

the development of regional networks to connect 

with the backbone NSFNET, thereby speeding the 

adoption of networking technologies on campuses 

around the country. In 1995, in partnership 

with MCI, NSF catalyzed support of the very 

high speed Backbone Network Service (vBNS), 

permitting advanced networking research and the 

development of novel scientific applications. A 

few years later, NSF established the NSF Middleware Initiative, focused on the development of 

advanced networking services to serve the evolving 

needs of the science and engineering community.

In the early to mid-1990s, informed by both the 

Branscomb and the Hayes Reports, NSF consolidated its support of national computing facilities in the establishment of the Partnerships for 

Advanced Computational Infrastructure (PACI) 

program. Two partnerships were established in 

1997, together involving nearly 100 partner institutions across the country in efforts to make more 

efficient use of high-end computing in all areas of 

science and engineering. The partnerships have 

been instrumental in fostering the maturation of 

cyberinfrastructure and its widespread adoption by 

the academic research and education community, 

and by industry.

Also in the early 1990s, NSF, as part of the 

U.S. High Performance Computing and Communications (HPCC) program, began to support larger-scale research and education-focused 

projects pursuing what became known as “grand 

challenges.” These HPCC projects joined scientists 

and engineers, computer scientists and state-ofthe-art cyberinfrastructure technologies to tackle 

important problems in science and engineering 

whose solution could be advanced by applying 

cyberinfrastructure techniques and resources. First 

coined by the HPCC program, the term “grand 

challenge” has been widely adopted in many science and engineering fields to signify an overarching goal that requires a large-scale, concerted 

effort.

During the 1990s, the penetration of increasingly affordable computing and networking 

technologies on campuses was also leading to the 

creation of what would become mission-critical, 

domain-specific cyberinfrastructure. For example, 

in the mid 1990s the earthquake engineering 

community began to define what would become 

the Network for Earthquake Engineering Simulation, one of many significant cyberinfrastructure 

projects in NSF’s portfolio today.

In 1999, the President’s Information Technology Advisory Committee (PITAC) released the 

seminal report Information Technology Research 

(ITR)-Investing in our Future, prompting new 

and complementary NSF investments in CI projects, such the Grid Physics Network (GriPhyN) 

and international Virtual Data Grid Laboratory 

(iVDGL) and the Geosciences Network, known as 

GEON. Informed by the PITAC report, NSF also 

created a Major Research Equipment and Facilities 

APPENDIX C: 

CHRONOLOGY OF NSF Information 

technology INVESTMENTS
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Construction (MREFC) project entitled Terascale 

Computing Systems that began its construction 

phase in FY 2000 and ultimately created the Extensible Terascale Facility – now popularly known 

as the Teragrid. Teragrid entered its production 

phase in October 2004 and represents one of the 

largest, fastest, most comprehensive distributed 

cyberinfrastructures for science and engineering 

research and education. 

In 2001, NSF charged an Advisory Committee 

for Cyberinfrastructure, under the leadership of 

Dr. Dan Atkins, to evaluate the effectiveness of 

PACI and to make recommendations for future 

NSF investments in cyberinfrastructure. The 

Atkins Committee, as it became popularly known, 

recommended support for the two Partnership 

lead sites through the end of their original PACI 

cooperative agreements. In October 2004, following merit review, the National Science Board 

(NSB) endorsed funding of those sites through the 

end of FY 2007. 

Through 2005, in addition to the groups 

already cited, a number of prestigious groups have 

made recommendations that continue to inform 

the agency’s cyberinfrastructure planning including the High-End Computing Revitalization Task 

Force, the PITAC Subcommittee on Computational Science, and the NRC Committee on the 

Future of Supercomputing.

NSF has nurtured the growth of what is now 

called cyberinfrastructure for a number of decades. 

In recent years, the Directorate for Computer 

and Information Science and Engineering (CISE) 

has been responsible for the provision of national 

supercomputing infrastructure for the academic 

community. In addition, the Directorate was 

instrumental in the creation of what ultimately 

became known as the Internet. During this 

incubation period, the management of CI was best 

provided by those also responsible for the research 

and development of related CI technologies. 

Over the years, the penetration and impact 

of computing and networking on campuses has 

been extensive, and has led to the creation of 

many disciplinary-specific or community-specific 

CI projects and activities. Today, CI projects are 

supported by all NSF Directorates and Offices. 

Because of the growing scope of investment and 

variability in needs among users in the broad science and engineering community, it has become 

clear that effective CI development and deployment now requires the collective leadership of 

NSF senior management. This leadership will be 

provided by the CIC chaired by the NSF Director and comprised of the NSF Deputy Director, 

the Assistant Directors of NSF’s Research Directorates and the Heads of the Office of International Science and Engineering, Office of Polar 

Programs, and the recently established Office of 

Cyberinfrastructure (OCI). The CIC has been 

meeting regularly since May 2005, and OCI was 

established in the Office of the Director on July 

22, 2005. In January 2007, the CIC authorized a 

standing CI Coordinators Committee (CICC) to 

augment its activities with representatives from all 

NSF Directorates and Offices and chaired by the 

Director of OCI. A foundation-wide external Advisory Committee for Cyberinfrastructure (ACCI) 

has also been established and is now active.

CISE will continue to be responsible for a broad 

range of programs that address the administration’s 

priorities for fundamental research and education 

in computing, representing more than 85% of the 

overall federal investment in university-based basic 

research.

APPENDIX D: 

MANAGEMENT OF CYBERINFRASTRUCTURE
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Collaboratories:

CoSMIC: Combinatorial Sciences and Materials 

Informatics Collaboratory http://mse.iastate.edu/

cosmic/ An international research and education 

center promoting the use of informatics and combinatorial experimentation for materials discovery 

and design. Based at Iowa State University with 

domestic partners at Florida International University and the University of Maryland, CoSMIC 

is composed of an international consortium of 

universities and laboratories. 

DANSE: The Data Analysis for Neutron Scattering Experiments http://wiki.cacr.caltech.edu/

danse/index.php/Main_Page Prompted by the 

development of the Spallation Neutron Source 

(http://www.sns.gov) (SNS), under construction in Oak Ridge, Tennessee, DANSE goals are 

to build a software system that 1) enables new 

and more sophisticated science to be performed 

with neutron scattering experiments, 2) makes 

the analysis of data easier for all scientists, and 3) 

provides a robust software infrastructure that can 

be maintained in the future. 

DISUN: Data Intensive Scientific University 

Network http://www.disun.org/ A grid-based 

facility of computational clusters and disk storage 

arrays distributed across four institutions each of 

which serves as a High Energy Physics Tier-2 site. 

The Compact Muon Solenoid (CMS) experiment 

is primarily supported by DISUN. 

Ecoinformatics.org http://www.ecoinformatics.

org/ A community of ecologists and informatics 

specialists operating on the principles of opensource software communities. Collaborative projects such as software and standards development 

that cross institutional and funding boundaries 

are managed through contributed personnel in an 

open and democratic process. Ecological Metadata Language is a product of this community. 

GriPhyN: Grid Physics Network http://www.

griphyn.org/ A large ITR project focused on 

computer science and grid research applied to the 

distributed computing and storage requirements 

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of the high energy physics community. GriPhyN 

is a foundational element of the Open Science 

Grid (OSG). 

ICPSRC: Inter - University Consortium for 

Political and Social Research http://www.icpsr.

umich.edu/ Maintains and provides access to a 

vast archive of social science data for research and 

instruction, and offers training in quantitative 

methods to facilitate effective data use. ICPSR 

preserves data, migrating them to new storage 

media as changes in technology warrant. ICPSR 

also provides user support to assist researchers in 

conducting their projects and identifying relevant 

data for analysis. 

iVDGL: International Virtual Data Grid Laboratory http://www.ivdgl.org/ A global data and 

compute grid serving physics and astronomy, 

funded as a large ITR project by MPS. While its 

sister project, GriPhyN, funded the grid research, 

iVDGL supports the operational grid and associated services supporting projects like CMS, 

ATLAS, and LIGO. 

LHC: Large Hadron Collider and LCG: Large 

Hadron Collider Computing Grid The Large 

Hadron Collider, http://lhc.web.cern.ch/lhc/ 

being built at CERN near Geneva, is the largest 

scientific instrument on the planet. The mission 

of the LHC Computing Project (LCG) is to 

build and maintain a data storage and analysis 

infrastructure for the entire high-energy physics 

community that will use the LHC. See also the 

World LHC Computing Grid (WLCG) http://

lcg.web.cern.ch/LCG/ , a distributed production 

environment for physics data processing. 

LTER: Long-Term Ecological Research Network 

http://lternet.edu/ A networked collaboratory 

of 26 field sites and network office focused on 

answering questions about the long-term dynamics of ecosystems, ranging from near pristine to 

highly engineered sites. In addition to site-based 

science, education and outreach, five common 

research themes ensure that multi-site projects 

and synthesis are integral to the program.

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APPENDIX E: 

REPRESENTATIVE DISTRIBUTED RESEARCH

COMMUNITIES (VIRTUAL ORGANIZATIONS)
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NCEAS: National Center for Ecological 

Analysis and Synthesis http://www.nceas.ucsb.

edu/fmt/doc?/frames.html NCEAS and the National Evolutionary Synthesis Center (NESCent) 

http://www.nescent.org/ serve as data centers and 

collaboratories for the ecology and evolutionary 

biology communities. Both are involved in the 

development of software, house databases, and 

sponsor collaborative activities aimed as synthesizing research. 

NEES: George E. Brown, Jr. Network for Earthquake Engineering Simulation http://www.nees.

org/ A shared national network of 15 experimental facilities, collaborative tools, a centralized data 

repository, and earthquake simulation software, 

all linked by the ultra-high-speed Internet2 connections of NEESgrid. These resources provide 

the means for advanced collaborative research 

based on experimentation and computational 

simulations of the ways buildings, bridges, utility 

systems, coastal regions, and geomaterials perform during seismic events. 

NNIN: National Nanotechnology Infrastructure 

Network http://www.nnin.org/ Integrated networked partnership of 13 user facilities that serves 

the resource needs of nanoscale science, engineering and technology. NNIN provides users with 

shared open access, on-site and remotely, to leading-edge tools, instrumentation, and capabilities 

for fabrication, synthesis, characterization, design, 

simulation and integration for the purpose of 

building structures, devices, and systems from 

atomic to complex large-scales. 

OSG: Open Science Grid http://www.opensciencegrid.org/ The national physics grid arising 

from the GriPhyN, iVDGL, and DOE’s PPDG 

projects. As an operational grid spread across 

dozens of institutions and DOE sites, OSG 

primarily supports high energy physics grid applications and some non-physics applications in 

an opportunistic grid dominated by commodity 

clusters whose CPU counts total into the thousands. The OSG Consortium builds and operates 

the OSG, bringing resources and researchers from 

universities and national laboratories together and 

cooperating with other national and international 

infrastructures to give scientists from many fields 

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QuarkNet Cosmic Ray eLAB Project http://

www11.i2u2.org:8080/elab/cosmic/project.jsp 

A distributed learning lab for collaborating high 

school physics students and teachers who collect 

and analyze cosmic ray data. The e-LAB participants work with computer scientists to provide 

cutting edge tools that use grid techniques to 

share data, graphs, and posters and to encourage 

collaboration among students nationwide. 

SCEC CME : Southern California Earthquake 

Center Community Modeling Environment 

http://epicenter.usc.edu/cmeportal/ A recent 

geophysics and IT collaboratory targeted at 

seismic hazard analysis and geophysical modeling. 

The computational test-bed under development 

will allow users to assemble and run highly complex seismological and geophysical simulations 

utilizing Teragrid with the goal of forecasting 

earthquakes in Southern California. 

UltraLight http://ultralight.caltech.edu/web-site/

ultralight/html/index.html A collaboration of 

experimental physicists and network engineers to 

enable petabyte-scale analysis of globally distributed data. Goals include: 1) developing network 

services that broaden existing Grid computing 

systems by promoting the network as actively 

managed component; 2) testing UltraLight in 

Grid-based physics production and analysis 

systems; and 3) engineering a trans- and intercontinental optical network testbed, including highspeed data caches and computing clusters. 

Veconlab: The Virginia Economics Laboratory 

http://veconlab.econ.virginia.edu/admin.htm/ 

Focuses on game theory and social interactions in 

economics and related fields. The Veconlab server 

provides a set of about 40 web-based programs 

that can be used to run interactive, social science experiments for either teaching or research 

purposes. 

Vlab: The Virtual Laboratory for Earth and Planetary Materials http://www.vlab.msi.umn.edu/, 

An interdisciplinary consortium for development 

and promotion of the theory of planetary materials. Computational determination of geophysically important materials properties at extreme 

conditions provides accurate information to a) 

interpret seismic data in the context of likely 

geophysical processes and b) be used as input 

for more sophisticated and reliable modeling of 

planets. 

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Observatories: 

CHESS: Cornell High Energy Synchrotron 

Source http://www.chess.cornell.edu Provides 

users with state-of-the-art synchrotron radiation facilities for research in Physics, Chemistry, 

Biology, and Environmental and Materials Sciences. A special NIH Research Resource, called 

MacCHESS, http://www.macchess.cornell.edu/ 

supports special facilities for protein crystallographic studies. 

CHRNS: Center for High Resolution Neutron 

Scattering http://www.ncnr.nist.gov/programs/

CHRNS/ Develops and operates state-of-the-art 

neutron scattering instrumentation with broad 

applications in materials research for use by 

the general scientific community. Combined, 

CHRNS instruments provide structural information on a length scale of 1 nm to ~10 microns, 

and dynamical information on energy scales 

from ~30 neV to ~100 meV, the widest ranges 

accessible at any neutron research center in North 

America. 

EarthScope http://www.earthscope.org/ Applies 

modern observational, analytical and telecommunications technologies to investigate the structure 

and evolution of the North American continent 

and the physical processes controlling earthquakes and volcanic eruptions. Efforts involve 

data transmission from numerous seismographs 

and GPS receivers to two data centers, serving 

the raw data in real time and making available 

derived data products via a web portal. 

IceCube http://www.icecube.wisc.edu/ A one-cubic-kilometer international high-energy neutrino 

observatory being built and installed in the clear 

deep ice below the South Pole Station. IceCube 

will open unexplored bands for astronomy, including the PeV (1015 eV) energy region, where 

the Universe is opaque to high energy gamma 

rays and where cosmic rays do not carry directional information because of their deflection by 

magnetic fields. 

IRIS: Incorporated Research Institutions for 

Seismology http://www.iris.edu/ A university 

research consortium dedicated to exploring 

the Earth’s interior through the collection and 

distribution of seismographic data. IRIS programs contribute to scholarly research, education, 

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earthquake hazard mitigation, and the verification 

of a Comprehensive Test Ban Treaty. The IRIS 

Data Management System manages and disseminates time series data from a variety of worldwide 

seismic instruments to provide basic data in support of earthquake studies and research into the 

structure of the Earth’s crust, mantle and core. 

LIGO: Laser Interferometer Gravitational Wave 

Observatory http://www.ligo.caltech.edu Dedicated to the detection of cosmic gravitational 

waves and harnessing of these waves for scientific research. The facility consists of two widely 

separated installations within the United States 

— one in Hanford Washington and the other in 

Livingston, Louisiana — operated in unison as a 

single observatory. 

Microbial Observatories http://www.nsf.

gov/bio/pubs/awards/mo.htm A network of sites 

or “microbial observatories” in different habitats 

to study and understand microbial diversity 

over time and across environmental gradients. 

Supported projects must establish or participate 

in an established, Internet-accessible knowledge 

network to disseminate information resulting 

from these activities. 

NEON: National Ecological Observatory 

Network http://www.neoninc.org/ A national research platform and virtual laboratory for studying the role of the biosphere in earths systems by 

examining the structure, function, and evolution 

of biological systems at regional to continental 

scales. A CI backbone will link field instrumentation and mobile instrument platforms, sensor 

networks, laboratory and field instrumentation, 

natural history archives, and analytical and 

modeling capabilities, to facilities for archival, 

computation, visualization, and forecasting. 

NHMFL: National High Magnetic Field 

Laboratory http://www.magnet.fsu.edu/index.

aspx Develops and operates high magnetic field 

facilities that scientists use for research in physics, 

biology, bioengineering, chemistry, geochemistry, 

biochemistry, materials science, and engineering. High magnetic fields are a critical link in the 

development of new materials that impact nearly 

every modern technology. 

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ORION and OOI: Ocean Research Interactive 

Observatory Networks http://orionprogram.

org/ and http://www.orionocean.org/OOI/default.html An integrated observatory network 

for oceanographic research and education with 

interactive access to ocean observing systems that 

track a wide range of episodicity and temporal 

change phenomena. OOI has three elements: 1) 

a global-scale array of relocatable deep-sea buoys, 

2) a regional-scaled cabled network consisting 

of interconnected sites on the seafloor, and 3) 

network of coastal observatories. 

Other Virtual Organizations:

AToL: The Tree of Life initiative http://atol.sdsc.

edu/ Supports the reconstruction of the evolutionary history of all organisms, seen as a grand 

challenge. The AToL research community works 

toward describing the evolutionary relationships 

of all 1.7 million described species. 

CASA: Center for Adaptive Sampling of the Atmosphere http://www.casa.umass.edu/ Integrates 

advancements in radar technology, networking 

and atmospheric sciences to develop a new, low 

cost network of weather radars that can adapt 

sampling procedures in real time in order to 

optimize information and provide unprecedented 

details of severe storms. 

CCMC: The Community Coordinated Modeling 

Center http://ccmc.gsfc.nasa.gov/ Provides access 

to modern space science simulations and supports the transition to space weather operations 

of modern space research models. To support 

community research CCMC adopts state of the 

art space weather models that are developed by 

outside researchers, executes simulation runs 

with these models, offers a variety of visualization 

and output analysis tools, and provides access to 

coupled models and existing model frameworks. 

CEDAR: Coupling, Energetics and Dynamics of Atmospheric Regions http://cedarweb.

hao.ucar.edu/cgi-bin/ion-p?page=cedarweb.ion 

For characterization and understanding of the 

atmosphere above ~60 km, with emphasis on 

the processes that determine the basic composition and structure of the atmosphere. Activities 

include collaborative research projects, multi-site 

field campaigns, workshops, and participation of 

graduate and undergraduate students.

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CIG: Computational Infrastructure for Geodynamics http://www.geodynamics.org/ Membership-governed organization that supports Earth 

science by developing and maintaining software 

for computational geophysics and related fields. 

CIG consists of: (a) a coordinated effort to 

develop reusable and open-source geodynamics 

software; (b) an infrastructure layer of software 

for assembling state-of-the-art modeling; (c) 

extension of existing software frameworks to 

interlink multiple codes and data through a superstructure layer; (d) strategic partnerships with 

computational science and geoinformatics; and 

(e) specialized training and workshops. 

CLIVAR: Climate Variability and Predictability 

http://www.clivar.org/ An international research 

program addressing many issues of natural 

climate variability and anthropogenic climate 

change, as part of the wider World Climate Research Programme (WCRP). It makes available 

a wide variety of climate-related data and models 

via a web interface and data management system. 

CUAHSI HIS: The Consortium of Universities 

for the Advancement of Hydrologic Science, Inc. 

http://www.cuahsi.org/ Represents about 100 

U.S. universities and develops infrastructure and 

services that support advancement of hydrologic 

science and education. The CUAHSI Hydrologic 

Information System (HIS) project is conducted 

by a group of academic hydrologists collaborating with the San Diego Supercomputer Center 

as a technology partner to produce a prototype 

Hydrologic Information System. 

C-ZEN: Critical Zone Exploration Network 

http://www.czen.org/ Promotes interdisciplinary 

research on the zone defined by the outer limits 

of vegetation and the lower boundary of ground 

water – identified by the National Research 

Council as the Critical Zone (NRC, 2001). 

CZEN cyberinfrastructure consists of a critical 

zone ontology, development of tools for knowledge discovery and management, and data and 

metadata standards development. 

DEISA: Distributed European Infrastructure 

for Supercomputing Applications http://www.

deisa.org/ A consortium of leading national 

supercomputing centers that currently deploys 

and operates a persistent, production quality, 

distributed supercomputing environment with 

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European continental scope. DEISA’s purpose is 

to enable discovery across a spectrum of science 

and technology through deep integration of existing national high-end computational platforms, 

coupled by a dedicated network and supported by 

innovative system and grid software. 

EGEE: The Enabling Grids for E-sciencE http://

public.eu-egee.org/ Funded by the European 

Commission to build on recent advances in grid 

technology and develop a service grid infrastructure which is available to scientists 24 hours-aday. Spanning over 30 countries and 150 sites 

across Europe, EGEE supports applications in 

Earth Sciences, High Energy Physics, Bioinformatics, Astrophysics, and other domains. 

GCAT: Genomic Consortium for Active Teaching http://www.bio.davidson.edu/projects/gcat/

gcat.html A consortium of institutions whose 

purpose is to integrate genomic techniques in 

the undergraduate life sciences curricula. GCAT 

provides faculty with resources and training to 

utilize the technology and means to share data 

across institutions. 

GEON: The Geosciences Network http://www.

geongrid.org/ Advances geoinformatics by training geoscience researchers, educators, students 

and practitioners in the use of cyberinfrastructure. GEON provides a service-oriented architecture (SOA) for support of “intelligent” search, 

semantic data integration, visualization of 4D 

scientific datasets, and access to high performance 

computing platforms for data analysis and model 

execution, via the GEON Portal. 

GLOBEC: U.S. GLOBEC (GLOBal ocean 

ECosystems dynamics) http://www.pml.ac.uk/

globec/ Looks at how climate change and variability translate into changes in the structure and 

dynamics of marine ecosystems, marine animal 

populations and in fishery production. Research 

approaches use inter-related modeling, processoriented studies, broad scale observations, and 

retrospective studies. 

IPBIR: Integrated Primate Biomaterials and 

Information Resource http://www.ipbir.org/ To 

assemble, characterize, and distribute high-quality DNA samples of known provenance with 

accompanying demographic, geographic, and 

behavioral information in order to stimulate and 

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facilitate research in primate genetic diversity and 

evolution, comparative genomics, and population 

genetics. 

LEAD: Linked Environments for Atmospheric 

Discovery: http://lead.ou.edu/ Seeks to mitigate the impacts of extreme weather events by 

accommodating the real time, on-demand, and 

dynamically-adaptive needs of mesoscale weather 

research. A major underpinning of LEAD 

is dynamic workflow orchestration and data 

management in a web services framework with 

grid-enabled systems. 

MARGINS: http://www.nsf-margins.org/Home.

html Focuses on understanding the complex interplay of processes that govern creation and destruction of continental margins and result in the 

concentration of both resources and geohazards 

where land and oceans meet. Data from collaborative research projects are available via a Data 

Management System and web-based services. 

NCAR: National Center for Atmospheric 

Research http://www.ncar.ucar.edu/ A federally 

funded research and development center that, 

together with partners at universities and research 

centers, studies Earth’s atmosphere and its interactions with the Sun, the oceans, the biosphere, 

and human society. NCAR hosts numerous 

projects that span the full range of VO activities 

and it recently launched a set of integrative initiatives designed to explore the Earth system from a 

21st-century vantage point: http://www.ncar.ucar.

edu/stratplan/initiatives.html 

NCED: National Center for Earth-surface 

Dynamics http://www.nced.umn.edu/ Fosters an 

integrated, predictive science of the skin of the 

Earth – “critical zone” - where interwoven physical, biological, geochemical, and anthropogenic 

processes shape Earth’s surface. NCED’s main 

cyberinfrastructure activities relate to a California 

field site at Angelo Coast Range Reserve with a 

steep, relatively rapidly eroding landscape where 

an advanced environmental observatory with a 

wireless network and automated environmental 

sensors are under construction.

NCN: Network for Computational Nanotechnology http://www.ncn.purdue.edu/ Advances 

approaches and simulation tools that allow engineers to design new nanoelectronic and NEMS 

technologies. The fields include: i) nanoelectron-

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ics, ii) NEMS, and iii) nano-bioelectronics, with 

the overall goal of connecting dry electronic and 

mechanical nanosystems to wet biological nanosystems. NanoHUB http://www.nanohub.org/ 

is a web-based initiative spearheaded by NCN 

that provides online simulation tools for nanoelectronics and molecular dynamics, along with 

semiconductor devices, processes and circuits. 

PEATNET: Peatland Ecosystem Analysis and 

Training Network http://www.peatnet.siu.edu/ 

An international interdisciplinary collaborative 

effort focused on northern peatland ecosystems. 

Web site serves as a mechanism to coordinate 

PEATNET activities and communicate findings 

and outcomes, and as the location of a peatland 

Web-discussion group and the PEATNET Virtual 

Resource Center. 

PRAGMA: The Pacific Rim Application and Grid 

Middleware Assembly www.pragma-grid.net/mission.htm Formed to establish sustained collaborations and advance the use of grid technologies 

in applications among a community of investigators working with leading institutions around the 

Pacific Rim. In PRAGMA, applications are the 

key, integrating focus that brings together necessary infrastructure and middleware to advance the 

application’s goals. 

RIDGE http://ocean-ridge.ldeo.columbia.edu/

general/html/home.html A long-term research 

program to study Earth’s oceanic spreading ridge 

system as an integrated whole, from its inception 

in the mantel to its manifestations in the biosphere and water column. Ridge 2000 supports 

interdisciplinary research and availability of data 

through web-based services. 

SAHRA: The Center for Sustainability of semiArid Hydrology and Riparian Areas http://www.

sahra.arizona.edu/ Promotes sustainable management of semiarid and arid water resources, with 

three components: the SAHRA Geo-database 

(SGD) for data storage and sharing, hydrologic 

observations, and integrated modeling at three 

resolutions. 

SBN: Seamount Biogeosciences Network http://

www.earthref.org/SBN/ Brings together the 

diverse science disciplines involved in seamount 

research for improved communication and scientific collaboration, data archiving and integration, 

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and sharing of seagoing logistical operations. Key 

SBN components include regular workshops and 

the development of a community website and 

database. 

Suominet: Real Time Integrated Atmospheric 

Water Vapor and TEC from GPS http://www.

suominet.ucar.edu/ Measures phase delays 

induced in GPS signals by the ionosphere and 

neutral atmosphere with high precision and converts these delays into integrated water vapor and 

total electron content (TEC). These measurements contribute to our understanding of the 

Earth’s weather and climate system and TEC data 

addresses topics in upper atmospheric research. 

TeraGrid www.teragrid.org An open scientific 

discovery infrastructure combining leadership 

class resources at eight partner sites to create an 

integrated, persistent computational resource. 

Deployed in September 2004, TeraGrid brings 

over 40 teraflops of computing power and nearly 

2 petabytes of rotating storage, and specialized 

data analysis and visualization resources into production, interconnected at 10-30 gigabits/second 

via a dedicated national network. 

TESS: Time-sharing Experiments for the Social 

Sciences http://www.experimentcentral.org/ 

Permits original data collection through national 

telephone surveys to which researchers can add 

their original questions and through arrangements that allow researchers to run their own 

studies on random samples of the population that 

are interviewed via the Internet. 

UNAVCO http://www.unavco.org/ A non-profit, 

membership-governed consortium that supports 

and promotes high-precision techniques for 

the measurement and understanding of crustal 

deformation. The data processing center analyzes 

and distributes GPS data from continuous GPS 

installations globally, including the dense array of 

stations dedicated to the EarthScope project. 

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Page	 	 Credit

Cover and © 2002 The Regents of the University of California 

inside cover 

i Sam Kittner/kittner.com

iv Courtesy of Ronald Cohen, Carnegie Institution of Washington 

2 Blake Harvey, NCSA

4 Marcus Thiebaux, Information Sciences Institute, University of Southern California 

6 Aleksei Aksimentiev and Klaus Schulten, Theoretical and Computational Biophysics 

 Group, Beckman Institute for Advanced Science and Technology, University of 

 Illinois at Urbana-Champaign

7 Christy Bowe, ImageCatcher News Service

8 (top) © 2007 JupiterImages Corporation

8 (bottom) Marcelo Garcia and Mariano Cantero, University of Illinois at UrbanaChampaign, and S. Balachandar, University of Florida

9 Leroy N. Sanchez, Los Alamos National Laboratory

11 Peter West, National Science Foundation 

12 © University Corporation for Atmospheric Research

13 Bob Wilhelmson, NCSA and the University of Illinois at Urbana-Champaign; Lou 

 Wicker, National Oceanic and Atmospheric Administration’s National Severe 

 Storms Laboratory; Matt Gilmore and Lee Cronce, University of Illinois 

Atmospheric Science Department. Visualization by Donna Cox, Robert Patterson, 

 Stuart Levy, Matt Hall and Alex Betts, NCSA

14 Courtesy of Theoretical and Computational Biophysics Group, Beckman Institute, 

 University of Illinois at Urbana-Champaign; Mercury Cluster background image 

 courtesy of NCSA and the Board of Trustees of the University of Illinois

15 Gary Strand, NCAR

16 Scientific contact Ed Seidel (eseidel@aci.mpg.de); simulations by Max Planck 

 Institute for Gravitational Physics (Albert-Einstein-AEI); visualization by Werner 

 Benger, Zuse Institute, Berlin (ZIB) and AEI. The computations were performed on 

 NCSA’s It

17 Peter Virnau, Massachusetts Institute of Technology

19 Kyle McQuilkin and Ryan Ridgely, Ohio University

Image Credits
Cyberinfrastructure Vision

for 21st Century Discovery

- 57 -

National Science Foundation March 2007

Page	 	 Credit

20 James Matthews, Linghao Zhong and John Brady, Cornell University; Mike 

 Himmel and Mark Nimlos, NREL; Tauna Rignall, Colorado School of Mines; Mike 

 Crowley, The Scripps Research Institute. Work was funded by an NREL subcontract 

 funded by DOE Office of the Biomass Program

21 Jason C. Fisher, © 2005 American Institute of Biological Sciences 

22 National Virtual Observatory and California Institute of Technology 

(http://us-vo.org/)

23 National Science Foundation

24 Courtesy of Montage, IPAC, Caltech, SDSC. This research made use of Montage, 

 funded by NASA’s Earth Science Technology Office, Computation Technologies 

 Project, under Cooperative Agreement Number NCC5-626 between NASA and 

 the California Institute of Technology. Montage is maintained by the NASA/IPAC 

 Infrared Science Archive

25 IRIS

26, 27 © CERN

28 Wolfgang Bluhm

30 EarthScope

32 Curtis Suplee, National Science Foundation

33 Ethan Dicks, National Science Foundation

34 John Orcutt, Scripps Institute of Oceanography 

35 HPWREN

36 Peggy Greb, Agricultural Research Service Image Gallery, USDA

38 Prairie View Solar Observatory

39 The JASON Project

40 Gary Meek, Georgia Institute of Technology

41 Theoretical and Computational Biophysics Group, University of Illinois at 

 Urbana-Champaign

42 Patrick Motl, Mario D’Souza, Joel E. Tohline, and Juhan Frank, Louisiana 

 State University
National Science Foundation

4201 Wilson Boulevard

Arlington, VA 22230

NSF 07-28