NSF 11-502: Cyber-Enabled Discovery and Innovation (CDI)

Program Solicitation NSF 11-502

Replaces Document(s):
NSF 10-506

 

National Science Foundation Directorate for Biological Sciences Directorate for Computer & Information Science & Engineering Directorate for Education & Human Resources Directorate for Engineering Directorate for Geosciences Directorate for Mathematical & Physical Sciences Directorate for Social, Behavioral & Economic Sciences Office of Cyberinfrastructure Office of Integrative Activities Office of International Science and Engineering Office of Polar Programs

 

Full Proposal Submission Window Date(s) (due by 5 p.m. proposer's local time):

December 01, 2010 - January 19, 2011

Type I Full Proposal Submission Window

December 01, 2010 - January 20, 2011

Type II Full Proposal Submission Window

Important Information And Revision Notes

Future Type III Awards Not Anticipated: Previous CDI solicitations have indicated that funding opportunities would be provided in subsequent years for Type III awards, subject to the availability of funds.  That statement has been removed from this solicitation.  No Type III awards will be made in the FY 2011 CDI competition.

A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG), NSF 11-1, was issued on October 1, 2010 and is effective for proposals submitted, or due, on or after January 18, 2011. Please be advised that the guidelines contained in NSF 11-1 apply to proposals submitted in response to this funding opportunity. Proposers who opt to submit prior to January 18, 2011, must also follow the guidelines contained in NSF 11-1.

Cost Sharing: The PAPPG has been revised to implement the National Science Board's recommendations regarding cost sharing.  Inclusion of voluntary committed cost sharing is prohibited. In order to assess the scope of the project, all organizational resources necessary for the project must be described in the Facilities, Equipment and Other Resources section of the proposal.  The description should be narrative in nature and must not include any quantifiable financial information.  Mandatory cost sharing will only be required when explicitly authorized by the NSF Director.  See the PAPP Guide Part I: Grant Proposal Guide (GPG) Chapter II.C.2.g(xi) for further information about the implementation of these recommendations.

Data Management Plan: The PAPPG contains a clarification of NSF's long standing data policy.  All proposals must describe plans for data management and sharing of the products of research, or assert the absence of the need for such plans.  FastLane will not permit submission of a proposal that is missing a Data Management Plan.  The Data Management Plan will be reviewed as part of the intellectual merit or broader impacts of the proposal, or both, as appropriate. Links to data management requirements and plans relevant to specific Directorates, Offices, Divisions, Programs, or other NSF units are available on the NSF website at: https://www.nsf.govbfa/dias/policy/dmp.jsp. See
Chapter II.C.2.j of the GPG for further information about the implementation of this requirement.

Postdoctoral Researcher Mentoring Plan: As a reminder, each proposal that requests funding to support postdoctoral researchers must include, as a supplementary document, a description of the mentoring activities that will be provided for such individuals.  Please be advised that if required, FastLane will not permit submission of a proposal that is missing a Postdoctoral Researcher Mentoring Plan. See Chapter II.C.2.j of the GPG for further information about the implementation of this requirement.

Summary Of Program Requirements

General Information

Program Title: 

Cyber-Enabled Discovery and Innovation  (CDI)

Synopsis of Program:

Cyber-Enabled Discovery and Innovation (CDI) is NSF’s bold five-year initiative to create revolutionary science and engineering research outcomes made possible by innovations and advances in computational thinking.  Computational thinking is defined comprehensively to encompass computational concepts, methods, models, algorithms, and tools.   Applied in challenging science and engineering research and education contexts, computational thinking promises a profound impact on the Nation’s ability to generate and apply new knowledge.  Collectively, CDI research outcomes are expected to produce paradigm shifts in our understanding of a wide range of science and engineering phenomena and socio-technical innovations that create new wealth and enhance the national quality of life. 

CDI seeks ambitious, transformative, multidisciplinary research proposals within or across the following three thematic areas:  

• From Data to Knowledge: enhancing human cognition and generating new knowledge from a wealth of heterogeneous digital data;
• Understanding Complexity in Natural, Built, and Social Systems: deriving fundamental insights on systems comprising multiple interacting elements;  and
• Virtual Organizations: enhancing discovery and innovation by bringing people and resources together across institutional, geographical and cultural boundaries. 

With an emphasis on bold multidisciplinary activities that, through computational thinking, promise radical, paradigm-changing research findings, CDI promotes transformative research within NSF.  Accordingly, investigators are encouraged to come together in the development of far-reaching, high-risk science and engineering research and education agendas that capitalize on innovations in, and/or innovative use of, computational thinking.  Research and education efforts around the world are beginning to address various aspects of the CDI themes, and CDI projects are expected to build upon productive intellectual partnerships involving investigators from academe, industry and/or other types of organizations, including international entities, that advance CDI objectives within the rapidly evolving global context. 

Congruent with the three thematic areas, CDI projects will enable transformative discovery to identify patterns and structures in massive datasets; exploit computation as a means of achieving deeper understanding in the natural and social sciences and engineering; abstract, model, simulate and predict complex stochastic or chaotic systems; explore and model nature’s interactions, connections, complex relations, and interdependencies, scaling from sub-particles to galactic, from subcellular to biosphere, and from the individual to the societal; train future generations of scientists and engineers to enhance and use cyber resources; and facilitate creative, cyber-enabled boundary-crossing collaborations, including those with industrial and international dimensions, to advance the frontiers of science and engineering and broaden participation in STEM fields. 

Two types of CDI awards will be supported as a result of the FY 2011 CDI competition:

• Type I awards will require efforts up to a level roughly comparable to: summer support for two investigators with complementary expertise; two graduate students; and their collective research needs (e.g. materials, supplies, travel) for three years.
• Type II awards will require larger (than Type I) efforts up to a level roughly comparable to: summer support for three investigators with complementary expertise; three graduate students; one or two senior personnel (including post-doctoral researchers and staff); and their collective research needs (e.g. materials, supplies, travel) for four years.  The integrative contributions of the Type II team should clearly be greater than the sum of the contributions of each individual member of the team.

Cognizant Program Officer(s):

• Eduardo Misawa, ENG/CMMI, telephone: (703) 292-8080, email: cdi@nsf.gov

• Thomas Russell, OD/OIA and MPS/DMS, telephone: (703) 292-8080, email: cdi@nsf.gov

• Kenneth Whang, CISE/IIS, telephone: (703) 292-8080, email: cdi@nsf.gov

Applicable Catalog of Federal Domestic Assistance (CFDA) Number(s):

• 47.041 --- Engineering
• 47.049 --- Mathematical and Physical Sciences
• 47.050 --- Geosciences
• 47.070 --- Computer and Information Science and Engineering
• 47.074 --- Biological Sciences
• 47.075 --- Social Behavioral and Economic Sciences
• 47.076 --- Education and Human Resources
• 47.078 --- Office of Polar Programs
• 47.079 --- Office of International Science and Engineering
• 47.080 --- Office of Cyberinfrastructure
• 47.081 --- Office of Experimental Program to Stimulate Competitive Research

Award Information

Anticipated Type of Award:  Standard Grant or Continuing Grant

Estimated Number of Awards:    30   - In FY 2011, the number of Type I and Type II awards will be determined based on the results of separate review processes.

Anticipated Funding Amount:   $36,000,000  - Pending availability of funds, a minimum of $36,000,000 will be available in FY 2011 for proposals submitted in response to this solicitation.

Eligibility Information

Organization Limit: 

Proposals may only be submitted by the following:

• Universities and Colleges - Universities and two- and four-year colleges (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Such organizations also are referred to as academic institutions.
• Non-profit, non-academic organizations: Independent museums, observatories, research labs, professional societies and similar organizations in the U.S. associated with educational or research activities.

Proposals that capitalize upon productive intellectual partnerships involving investigators from academe, industry and/or other types of organizations, including international entities, are encouraged.  Partnerships between academe and other types of organizations, both foreign and domestic, promise the identification of compelling research challenges, and the more effective transformation of discoveries into innovations that create wealth and other societal impacts.  While NSF will consider supporting CDI activities undertaken by SBIR-eligible organizations through subawards, other for-profit entities and international partners must support their participation in CDI projects from other funding sources.

PI Limit: 

None Specified

Limit on Number of Proposals per Organization: 

None Specified

Limit on Number of Proposals per PI: 2

An individual may participate as Principal Investigator, co-Principal Investigator or other Senior Personnel in at most two full proposals in each annual competition.  Any individual whose biographical sketch is provided as part of the proposal will be considered Senior Personnel in the proposed activity, with or without financial support from the project.  After the proposal submission deadline, if a person appears on more than two full proposals, submitters have up to two weeks after the deadline to withdraw excess proposals to reduce that person's participation to two proposals.  After that time, the first two submitted proposals (in FastLane time-stamp chronological order) in which that individual is participating will be accepted for review, and the remainder will be returned without review.  For this purpose, a multi-institution collaborative project is treated as one proposal that is considered submitted when the last component proposal is submitted. 

Proposal Preparation and Submission Instructions

A. Proposal Preparation Instructions

Letters of Intent: Not Applicable

Preliminary Proposal Submission: Not Applicable

Full Proposals:

Full Proposals submitted via FastLane: NSF Proposal and Award Policies and Procedures Guide, Part I: Grant Proposal Guide (GPG) Guidelines apply. The complete text of the GPG is available electronically on the NSF website at:
https://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg.

Full Proposals submitted via Grants.gov: NSF Grants.gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.gov Guidelines apply (Note: The NSF Grants.gov Application Guide is available on the Grants.gov website and on the NSF website at:
https://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide)

B. Budgetary Information

Cost Sharing Requirements: Inclusion of voluntary committed cost sharing is prohibited.

Indirect Cost (F&A) Limitations:  Not Applicable

Other Budgetary Limitations: Not Applicable

C. Due Dates

Full Proposal Submission Window Date(s) (due by 5 p.m. proposer's local time):

December 01, 2010 - January 19, 2011

Type I Full Proposal Submission Window

December 01, 2010 - January 20, 2011

Type II Full Proposal Submission Window

Proposal Review Information Criteria

Merit Review Criteria:   National Science Board approved criteria. Additional merit review considerations apply. Please see the full text of this solicitation for further information.

Award Administration Information

Award Conditions:   Standard NSF award conditions apply.

Reporting Requirements:   Standard NSF reporting requirements apply.

Table Of Contents

Summary of Program Requirements

Introduction

Program Description

Award Information

Eligibility Information

Proposal Preparation and Submission Instructions

Proposal Preparation Instructions

Budgetary Information

Due Dates

FastLane/Grants.gov Requirements

NSF Proposal Processing and Review Procedures

NSF Merit Review Criteria

Review and Selection Process

Award Administration Information

Notification of the Award

Award Conditions

Reporting Requirements

Agency Contacts

Other Information

I. Introduction

Our everyday lives have been transformed by the impact of computation and communication.  This impact can be observed in the national economy where information technology has contributed in significant and numerous ways to growth in productivity, and to a plethora of new products and services.  For example, advances in computing have led to improvements in healthcare diagnoses, access and delivery, in education where learning is increasingly mediated by information technologies, and in science and engineering where the conduct of research is being revolutionized by an increasingly pervasive and sophisticated cyberinfrastructure.  There has also been an impact at a conceptual level.  Applying computing to problem-solving has led to, and continues to engender, the development of new ways of conceptualizing, analyzing and solving problems, particularly problems related to complex systems where more traditional research tools afford only limited progress.

Motivated by compelling research challenges across the science and engineering frontier, NSF has been making investments in computational science and engineering research, education, and infrastructure for many years.  The potential of an increasingly powerful and functionally-complete cyberinfrastructure to advance science and engineering discovery and learning recently culminated in the creation and initial implementation of the agency’s
Cyberinfrastructure Vision for 21^st Century Discovery. 

Recognizing that contemporary advances in computational capabilities – most notably algorithms, architectures, data storage, languages, manipulation and visualization, networking, processing power, software systems, and a growing community of experienced computational scientists and engineers – place us on the threshold of a transformation in our understanding of the world around us, NSF has formulated a bold initiative called Cyber-Enabled Discovery and Innovation (CDI).  All NSF directorates and programmatic offices are participating.

II. Program Description

The Cyber-Enabled Discovery and Innovation (CDI) initiative has been designed to yield revolutionary science and engineering research outcomes made possible by innovations and advances in computational thinking.  Computational thinking is defined comprehensively to encompass computational concepts, methods, models, algorithms, and tools. Applied in challenging and compelling science and engineering research and education contexts, computational thinking promises a profound impact on the Nation’s ability to generate and apply new knowledge.  In addition, the challenge of applying computational thinking to very difficult problems in science and engineering will stimulate further advances in computational thinking.

Collectively, CDI research outcomes will produce paradigm shifts in our understanding of a wide range of science and engineering phenomena and socio-technical innovations that create new wealth and enhance the national quality of life. CDI investigators are expected to generate groundbreaking multidisciplinary research and education outcomes across biological sciences, computer and information sciences, education, engineering, geosciences, mathematical sciences, physical sciences, and social, behavioral, and economic sciences. The development and creative use of computational thinking to enable discovery and innovation on all fronts of science and engineering is likely to stimulate advances that collectively accelerate development of an increasingly powerful cyberinfrastructure.

With an emphasis on bold, multidisciplinary activities that, through computational thinking, promise radical, paradigm-changing science and engineering outcomes, CDI promotes transformative research within NSF.  Accordingly, investigators are encouraged to come together in the development of far-reaching, high-risk research and education agendas that capitalize on innovations in, and/or innovative use of, computational thinking to create new knowledge and societal impact far beyond today’s capabilities.  Research and education efforts around the world are beginning to address various aspects of the CDI themes, and CDI projects are expected to build upon productive intellectual partnerships involving investigators from academe, industry and/or other types of organizations, including international entities, that advance CDI objectives within the rapidly evolving global context.

A competitive CDI proposal will:

Describe an ambitious research and/or education agenda that, through computational thinking, promises paradigm-shifting advances in more than one field of science, engineering, or education;

Provide a compelling rationale for how innovations in, and/or innovative use of, computational thinking will yield the desired project outcomes; and,

Draw on productive intellectual partnerships that capitalize upon knowledge and expertise synergies in multiple fields or sub-fields of science, engineering, or education, and/or in multiple types of organizations, including academic, for-profit, and not-for-profit entities, both foreign and domestic.

Projects that make use of existing computational concepts, methods, models, algorithms, and tools to significantly advance only one field of science or engineering should be submitted to an appropriate NSF program in that field instead of to CDI. 

Motivated by transformative science and engineering research opportunities, CDI seeks bold research and education proposals within or across the following three thematic areas:

From Data to Knowledge: enhancing human cognition and generating new knowledge from a wealth of digital data

An abundance of digital data promises a profound impact in both the quality and rate of discovery and innovation in science and engineering, as well as in other societal contexts.  Worldwide, researchers are producing, accessing, analyzing, integrating and storing massive amounts of digital data daily, through observation, experimentation and simulation, as well as through the creation of collections of digital representations of tangible artifacts and specimens.  Modern experimental and observational instruments generate and collect large sets of data of varying types (numerical, video, audio, textual, multi-modal, multi-level, multi-resolution) at increasing speeds.  Often, the data users are not the data producers, and they thus face challenges in harnessing data in unforeseen and unplanned ways.  In many science or engineering applications, for example, in mesoscale weather prediction or critical infrastructure protection applications, the ability to gather, organize, analyze, model, and visualize large, multi-scale, heterogeneous data sets in rapid fashion is often crucial. 

New methods are required that create knowledge and understanding from an abundance of digital data across the science and engineering frontier, and that accelerate the transformation of knowledge into new products and services that stimulate economic growth as well as other societal benefits.  Driven by compelling science and engineering research and education opportunities, new efforts to support the complex tasks of data analysis and discovery must be explored. 

The massive scale and often dynamic nature of science and engineering data dictate that relevant computational technologies be fast, flexible, and capable of operating at multiple levels of abstraction.  Data of different types often must be synthesized into a single model that permits an emphasis on data meaning rather than on the forms in which the data were originally represented.  Models may dynamically incorporate information via data assimilation and machine learning.  Alternative models may be compared in exploratory data analysis.  A key component of developing or parameterizing a model is often an inverse problem: deducing system properties and structures, parameter values, or underlying principles from data. Inverse problems are commonly non-unique or in some way ill-posed, so that the data may not determine a unique model, and selection of the best model may require careful optimization. Ultimately, the value of a model depends on the major challenge of validation against "ground truth"; feedbacks between mathematical, computational, and application-domain analyses, each influencing the next step in the others, are vital to real-world insight. 

Analysis of large data sets, both real-time and offline, demands scalable algorithms whose computational complexity grows as slowly as possible with the scale of the data.  Research may require the development of novel algorithms that, for example, can discern and exploit parametric, geometric, and topological properties of data, as well as the development of novel data mining and dimension reduction methodologies that can expose the knowledge underlying science and engineering data. Some of the important ways of extracting information from data include data aggregation and annotation, pattern recognition, perturbation and sensitivity analysis, real-time manipulation, filtering and estimation, spectral graph analysis, statistical analysis, and stochastic simulation. New visualization methods can enhance human cognition, allowing scientists, engineers, researchers, educators, and students to detect and comprehend previously indiscernible abstract concepts, patterns, and important exceptions amidst vast data.  Approaches informed by knowledge of human cognition and perception can amplify individuals’ capability to perceive, understand, synthesize and reason about complex and often dynamic data.  In some science and engineering domains, innovative technologies may also need to address the data confidentiality, privacy, security, provenance, and regulatory issues that often impact the use of data. 

Ambitious CDI projects in this area will allow investigators to confirm the expected and reveal the unexpected in multiple science or engineering domains.  Under this theme, CDI seeks proposals for multidisciplinary efforts focused on the development and evaluation of new approaches to data mining, data federation, knowledge extraction and knowledge representation, and visualization in demanding scientific and engineering applications.  New approaches in computational thinking applied in the context of From Data to Knowledge will support collaboration and teamwork, often among people of diverse backgrounds and levels and areas of expertise.  Projects should promise to communicate the results of research findings in ways that both deepen and broaden their impact in a wide variety of application domains.

Understanding Complexity in Natural, Built, and Social Systems: deriving fundamental insights on systems comprising multiple interacting elements

Identifying general principles and laws that characterize complexity and capture the essence of complex systems is one of the major challenges of 21^st century science and engineering.  Complex systems are more than just complicated; they display distinct characteristics not encountered in "simple" systems, such as multi-scale interactions, emergent behavior, pattern formation, and self-organization, and they are often inherently stochastic or operate in unpredictable settings.  Nonlinear couplings and feedbacks across multiple processes and scales typify these systems.  They are not amenable to reductionism; finding constructs that persist through the dynamics is fundamental, and involves a major role for innovative computational experimentation.  As well as advancing science and engineering, the understanding of complexity will enable the design, synthesis, and control of novel complex engineered systems.  Furthermore, it will facilitate intervention in and analysis of complex natural and social systems. This theme therefore promotes the exploration and modeling of natural interactions, connections, complex relations, and interdependencies, scaling from sub-particles to galaxies, from subcellular to biosphere, and from the individual to the societal, across time, in order to understand, mimic, synthesize, and exploit complex systems.

The functionalities offered by computational thinking allow “experiments” to take place entirely in cyberspace.  In many situations, simulation through computation is the only feasible approach to a systematic investigation of realistic complex scientific phenomena, or is essential to the scientific basis for and design of "traditional" experiments.  Key challenges include accuracy and resolution, efficiency, perturbation analysis, uncertainty, stochasticity, validation against “ground truth”, long-term dynamics, and predictive modeling.   Simulations and computational experiments in mainstream and informal education can engage students and the public in the excitement of scientific and engineering discovery.

Much of the understanding of complexity will come from mathematical and statistical modeling and analysis, based on both theoretical and empirical studies.  Mimicking and synthesizing systems will exploit a wide variety of techniques. Complexity often requires advances in numerical methods for differential, algebraic, and discrete systems.  Other approaches include agent-based modeling, neural networks, and dynamically interactive human-in-the-loop calculations.  An important consideration for large systems is that scalable methods and tools be available in the working environments of scientists, engineers, and STEM educational researchers.

Virtual Organizations: enhancing discovery and innovation by bringing people and resources together across institutional, geographical and cultural boundaries

Virtual Organizations (VOs) can facilitate the conduct of cutting-edge, transformative research and learning within and across all fields of science and engineering.  As complex, networked socio-technical systems supported by cyberinfrastructure, VOs promise to connect people and resources across institutional and geographic boundaries, to foster dynamic configurations of instruments, data streams, facilities, and researchers, and to enable new discoveries and new approaches to scientific inquiry and education through remote access to experimental tools, observational instruments, simulation systems, and globally dispersed individuals.  Because they extend beyond traditional “brick and mortar” research institutions, VOs allow for more flexible boundaries, memberships, and lifecycles and for scientific inquiry to be performed at a scale and a distance never before possible.  Achieving such radical scalability and seamless integration and interoperability will require the application of computational thinking to all levels of VO formulation, design, implementation, and maintenance.

Successful projects that designate VO as their primary theme must produce paradigm-shifting research in two or more scientific disciplines, sub-disciplines or interdisciplinary science, engineering, or education areas (the science of virtual organizations may be one of the research areas).  In addition, successful VO projects must include significant efforts to advance the understanding of VOs as new modalities of science, engineering, and education by means of well-designed evaluation and/or social scientific research.  That is, a project must contribute systematic knowledge and principled understanding of factors that enable effective science and engineering VOs.

VO proposals should address some of the myriad socio-technical challenges of formulating, designing, building, and advancing effective VOs for science, engineering, and education.  As distributed, dynamic, and computationally-enhanced modes of operation and organization, VOs will need to overcome traditional boundaries in unprecedented ways and not only expand but diversify the research and educational opportunities and experiences available to researchers, students, and citizens.  As such, VOs may also be explored as a primary vehicle for enhancing innovation and broadening participation in research and in STEM education.

Understanding how to model and leverage VOs as socio-technical systems to generate and accelerate transformative research within and across different science and engineering disciplines necessarily requires the bringing together of domain scientists with expertise in, for example, network science, cognitive science, artificial intelligence and machine learning, game theory, workflow and value chain analysis, statistical physics, software/hardware design, information privacy and security, participatory and social computing, operations research, and organizational studies.  Accordingly, CDI investigators of different disciplinary perspectives should collaborate on the formulation, design, development, implementation, and continuous improvement of VOs to test and verify proposed theories and models of distributed learning and discovery with specific problems, populations and purposes.

All three themes are inter-related.  Realistic modeling and accurate, efficient solution of models are becoming possible for ever more complex phenomena, which defy understanding by other means.  Such models and increasingly sophisticated scientific observations are described in terms of data of unprecedented scale, from which insight must be extracted through more ingenious techniques than before.  Attacking these problems also requires larger organizations, often both geographically dispersed and intellectually diverse; empowerment of such groups is central to this transformation.  Accordingly, proposals in one theme, or that cross two or more of the three themes, are encouraged.

In order to realize the full potential of cyber-enabled discovery and innovation, CDI will contribute to the preparation of a workforce trained in computational thinking, with broad participation that ensures inclusion of students and faculty from historically underrepresented populations, minority-serving institutions, and institutions serving students with disabilities.

Effective international collaborations involve true intellectual partnership in which successful outcomes depend on the unique contributions of U.S. and international partners. They engage junior researchers and students in the collaboration, taking advantage of cyber environments to prepare a globally-engaged workforce. Collaborations with industry to couple scientific with technical insight can foster education in innovation and broaden the identification of problems that can benefit from CDI.

For additional information about CDI, including frequently asked questions, see
https://www.nsf.gov/crssprgm/cdi/.  Examples of motivating science and/or engineering research and education opportunities can also be found there.  This list is provided for the purposes of illustration only; it is neither exhaustive, nor indicative of preference regarding research areas.  Similarly, proposals that address NSF-appropriate aspects (for clarification, see the Grant Proposal Guide,
https://www.nsf.gov/pubs/policydocs/pappguide/nsf11001/gpg_1.jsp#IB) of national science and technology priorities are welcome; see Memorandum M-10-30 from the Office of Management and Budget and the Office of Science and Technology Policy,
http://www.whitehouse.gov/sites/default/files/omb/assets/memoranda_2010/m10-30.pdf.

III. Award Information

Two types of CDI awards will be supported in the FY2011 competition of CDI:

Type I awards require efforts up to a level roughly comparable to: summer support for two investigators with complementary expertise; two graduate students; and their collective research needs (e.g. materials, supplies, travel) for three years.

Type II awards require larger (than Type I) efforts up to a level roughly comparable to: summer support for three investigators with complementary expertise; three graduate students; one or two senior personnel (including post-doctoral researchers and staff); and their collective research needs (e.g. materials, supplies, travel) for four years. The integrative contributions of the Type II team should clearly be greater than the sum of the contributions of each member of the team.

In FY 2011, the number of Type I and Type II awards will be determined based on the results of separate review processes.

IV. Eligibility Information

Organization Limit: 

Proposals may only be submitted by the following:

Universities and Colleges - Universities and two- and four-year colleges (including community colleges) accredited in, and having a campus located in the US, acting on behalf of their faculty members. Such organizations also are referred to as academic institutions.

Non-profit, non-academic organizations: Independent museums, observatories, research labs, professional societies and similar organizations in the U.S. associated with educational or research activities.

Proposals that capitalize upon productive intellectual partnerships involving investigators from academe, industry and/or other types of organizations, including international entities, are encouraged.  Partnerships between academe and other types of organizations, both foreign and domestic, promise the identification of compelling research challenges, and the more effective transformation of discoveries into innovations that create wealth and other societal impacts.  While NSF will consider supporting CDI activities undertaken by SBIR-eligible organizations through subawards, other for-profit entities and international partners must support their participation in CDI projects from other funding sources.

PI Limit: 

None Specified

Limit on Number of Proposals per Organization: 

None Specified

Limit on Number of Proposals per PI: 2

An individual may participate as Principal Investigator, co-Principal Investigator or other Senior Personnel in at most two full proposals in each annual competition.  Any individual whose biographical sketch is provided as part of the proposal will be considered Senior Personnel in the proposed activity, with or without financial support from the project.  After the proposal submission deadline, if a person appears on more than two full proposals, submitters have up to two weeks after the deadline to withdraw excess proposals to reduce that person's participation to two proposals.  After that time, the first two submitted proposals (in FastLane time-stamp chronological order) in which that individual is participating will be accepted for review, and the remainder will be returned without review.  For this purpose, a multi-institution collaborative project is treated as one proposal that is considered submitted when the last component proposal is submitted. 

V. Proposal Preparation And Submission Instructions

A. Proposal Preparation Instructions

Full Proposal Preparation Instructions: Proposers may opt to submit proposals in response to this Program Solicitation via Grants.gov or via the NSF FastLane system.

Full proposals submitted via FastLane: Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Grant Proposal Guide (GPG). The complete text of the GPG is available electronically on the NSF website at:
https://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg. Paper copies of the GPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-7827 or by e-mail from nsfpubs@nsf.gov. Proposers are reminded to identify this program solicitation number in the program solicitation block on the NSF Cover Sheet For Proposal to the National Science Foundation. Compliance with this requirement is critical to determining the relevant proposal processing guidelines. Failure to submit this information may delay processing.

Full proposals submitted via Grants.gov: Proposals submitted in response to this program solicitation via Grants.gov should be prepared and submitted in accordance with the NSF Grants.gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.gov. The complete text of the NSF Grants.gov Application Guide is available on the Grants.gov website and on the NSF website at:
(https://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide). To obtain copies of the Application Guide and Application Forms Package, click on the Apply tab on the Grants.gov site, then click on the Apply Step 1: Download a Grant Application Package and Application Instructions link and enter the funding opportunity number, (the program solicitation number without the NSF prefix) and press the Download Package button. Paper copies of the Grants.gov Application Guide also may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-7827 or by e-mail from nsfpubs@nsf.gov.

In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following:

Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via the NSF FastLane system. Chapter II, Section D.4 of the Grant Proposal Guide provides additional information on collaborative proposals.

Additional Full Proposal Preparation Instructions:

Cover Sheet: 

Select the CDI program solicitation number from the Program Announcement/Solicitation pull down menu.  Go to the Unit Selection Lists section.  In the “Divisions" selection box, under "Directorate: O/D Office of the Director", you will see the Office of Integrative Activities (OIA).  Go straight to the “Programs” selection box, and select the relevant CDI Type (Type I or II).  The Type you choose will be added to the “Current List of selected NSF Units”.  Then click “Go Back”, click “Go” button next to “Remainder of the Cover Sheet” to get to that section.

Grants.gov Users: The program solicitation number will be pre-populated by Grants.gov on the NSF Grant Application Cover Page. Grants.gov users should refer to Section VI.1.2. of the NSF Grants.gov Application Guide for specific instructions on how to designate the NSF Unit of Consideration.

Provide a short informative title for the proposed CDI project. To assist NSF staff in sorting full proposals for review, for the FY 2011 competition, full proposal titles should begin with “CDI-Type I:” or “CDI-Type II:”.  The system allows one PI and at most four Co-PIs to be designated for each proposal.  If your project involves international partners, check the international activities box and list the countries involved. If needed, additional lead personnel should be designated as non co-PI, Senior Personnel on the Budget form.

Project Summary (1-page limit): At the top of this page enter the title of the CDI project, beginning with “CDI-Type I:” or “CDI-Type II:”, the name of the PI and the lead institution, and the primary and other relevant CDI themes.  Provide a summary description of the CDI project, including its transformative research and education goals, and the innovations in, and/or innovative use of, computational thinking being proposed.  In separate statements, provide a succinct summary of the intellectual merit and broader impacts of the proposed project.  Full proposals that do not address the intellectual merit and broader impacts of the proposed project in separate statements will be returned without review.

Coordination Plan (3-page limit, in addition to the usual 15-page limit for project description): Each proposal must contain a clearly labeled coordination plan (separate section of the project description), which includes 1) the specific roles of the PI, co-PIs, other senior personnel and paid consultants at all institutions involved, 2) how the project will be managed across institutions and disciplines, 3) identification of the specific coordination mechanisms that will enable cross-institution and/or cross-discipline scientific integration (e.g., yearly workshops, graduate student exchange, project meetings at conferences, use of the grid for videoconferences, software repositories, etc.), and 4) pointers to the budget line items that support these coordination mechanisms.

Proposals that designate Virtual Organizations as their primary theme must include, as part of the coordination plan, plans for carrying out and reporting rigorous evaluation and continuous improvement of the VO.  At a minimum, such plans should address issues such as the VO's structure, governance and processes and the effects of these VO design choices on the nature of the resources and the support needed to create and maintain them, the nature of the participants (who they are, what activities they engage in, and why) and the VO's impacts on participants and on external stakeholders.  Simple summative metrics such as counts of publications, website visits and member accounts are not adequate for evaluating VO effectiveness.

Exclusive of the coordination plan, the project description must be no longer than 15 pages.

Single copy documents:  Full proposals that do not provide the following information will be returned without review.

Project Personnel (text-searchable PDF, in FastLane, under Additional Single Copy Documents).  List all Senior Personnel in the project.  For each person, provide the last name, first name, and institution/organization.  In the main body of the proposal, a corresponding biographical sketch should be provided for all individuals included on this list, as instructed in Section II.C.2.f of the Grant Proposal Guide. 

Collaborators/Individuals with Conflicts of Interest (text-searchable PDF, in FastLane, under Additional Single Copy Documents).  Provide a list, in an alphabetized table, of the full names and institutional affiliations of all persons with potential conflicts of interest as specified in NSF’s Grant Proposal Guide.  For each PI, Co-PI and other Senior Personnel, include all co-authors/editors and collaborators (within the past 48 months), all graduate advisors and advisees, and any other individuals or institutions with which the investigator has financial ties (please specify type).  In addition, list all subawardees who would receive funds through the CDI award.

Electronic Documents (#1 in Excel, CSV format, e-mailed manually to cdi@nsf.gov after proposal submission, with subject heading referring to the 7-digit proposal number that starts with "11"; #2 entered on a web form and e-mailed automatically by submitting the form):

In addition, the proposers must send the following two documents immediately after submission of their proposal.

"List of Personnel, Collaborators and Affiliates": After receipt of the proposal number from FastLane, send an e-mail to cdi@nsf.gov. The subject heading of the e-mail should note the proposal number and the lead institution.  Attach the document described below, prepared on a template that will be available at https://www.nsf.gov/crssprgm/cdi/.  NSF personnel will use automated data handling of this document.  To facilitate this, the file should be in the CSV "flat text" format, with unformatted data entry under the column headings (Proposal Number, PI or SP Last_Name, etc.) in the template.  Carriage returns, splitting items over multiple cells, extra spaces, etc., will interfere with automated handling.  The document is an Excel spreadsheet containing two lists: one (columns C-E) lists the last names, first names and institutional affiliations of all PIs, Co-PIs, and other senior personnel; the second (columns F-H) lists the full names and institutional affiliations of all people having conflicts of interest with any PIs, Co-PIs, and other senior personnel.  This list will be used by NSF to check for conflicts of interest in assembling the review community.  The filename should be the proposal number (which begins with "11"; not the temporary proposal number used during proposal preparation) followed by the three characters "coi" (for example, for a proposal number 1123456, this file name will be 1123456coi.csv where the extension csv will be automatically added by Excel when saving the file using the CSV format).  The 7-digit proposal number beginning with "11" should appear in every row of the file, in column B, as indicated by the sample that will be available at
https://www.nsf.gov/crssprgm/cdi/.  Each project participant in columns C-E should be listed (repeatedly) in all rows that name his/her conflicted individuals in columns F-H, as in the sample.

(There is redundancy between the Additional Single Copy Documents, which become part of the FastLane proposal file, and Electronic Document (1), which is used for automated data handling.  At present, it is not technically possible for one document to perform both functions.)

"Themes and Keywords": After receipt of the proposal number from FastLane, go to the "Themes & Keywords Form" that will be available at
https://www.nsf.gov/crssprgm/cdi/.  Follow the instructions on the form and press "Submit" to send to NSF an automatic e-mail containing the information.  This will identify the primary and other relevant CDI themes and up to 3 keywords selected from the CDI keyword list (or of the PI's own choosing) that best describe the major areas of the multidisciplinary research and education being proposed. This information will be used internally to NSF to facilitate the review process and not to exclude areas that are not explicitly represented in the CDI keyword list.

Themes: "From Data to Knowledge", "Understanding Complexity", "Virtual Organizations"

Keywords: The CDI keyword list is available on
https://www.nsf.gov/crssprgm/cdi/

The template for document (1) and the web form for document (2) are available at: https://www.nsf.gov/crssprgm/cdi/

Remember to e-mail document (1) to cdi@nsf.gov; do not use FastLane.

NOTE: Full proposals that fail to provide these electronic documents with proper information and according to the required format will be returned without review.

No other items or appendices are to be included.  Full proposals containing items other than those required above or by the Grant Proposal Guide (GPG) will not be reviewed or considered for NSF funding.

B. Budgetary Information

Cost Sharing:   Inclusion of voluntary committed cost sharing is prohibited

Budget Preparation Instructions:Budgets should include travel funds for the PIs to attend annual CDI grantees' meetings.

C. Due Dates

Full Proposal Submission Window Date(s) (due by 5 p.m. proposer's local time):

December 01, 2010 - January 19, 2011

Type I Full Proposal Submission Window

December 01, 2010 - January 20, 2011

Type II Full Proposal Submission Window

D. FastLane/Grants.gov Requirements

For Proposals Submitted Via FastLane:

Detailed technical instructions regarding the technical aspects of preparation and submission via FastLane are available at: https://www.fastlane.nsf.gov/a1/newstan.htm. For FastLane user support, call the FastLane Help Desk at 1-800-673-6188 or e-mail fastlane@nsf.gov. The FastLane Help Desk answers general technical questions related to the use of the FastLane system. Specific questions related to this program solicitation should be referred to the NSF program staff contact(s) listed in Section VIII of this funding opportunity.

Submission of Electronically Signed Cover Sheets. The Authorized Organizational Representative (AOR) must electronically sign the proposal Cover Sheet to submit the required proposal certifications (see Chapter II, Section C of the Grant Proposal Guide for a listing of the certifications). The AOR must provide the required electronic certifications within five working days following the electronic submission of the proposal. Further instructions regarding this process are available on the FastLane Website at: https://www.fastlane.nsf.gov/fastlane.jsp.

For Proposals Submitted Via Grants.gov:

Before using Grants.gov for the first time, each organization must register to create an institutional profile. Once registered, the applicant's organization can then apply for any federal grant on the Grants.gov website. The Grants.gov's Grant Community User Guide is a comprehensive reference document that provides technical information about Grants.gov. Proposers can download the User Guide as a Microsoft Word document or as a PDF document. The Grants.gov User Guide is available at: http://www.grants.gov/CustomerSupport. In addition, the NSF Grants.gov Application Guide provides additional technical guidance regarding preparation of proposals via Grants.gov. For Grants.gov user support, contact the Grants.gov Contact Center at 1-800-518-4726 or by email: support@grants.gov. The Grants.gov Contact Center answers general technical questions related to the use of Grants.gov. Specific questions related to this program solicitation should be referred to the NSF program staff contact(s) listed in Section VIII of this solicitation.

Submitting the Proposal: Once all documents have been completed, the Authorized Organizational Representative (AOR) must submit the application to Grants.gov and verify the desired funding opportunity and agency to which the application is submitted. The AOR must then sign and submit the application to Grants.gov. The completed application will be transferred to the NSF FastLane system for further processing.

VI. NSF Proposal Processing And Review Procedures   

Proposals received by NSF are assigned to the appropriate NSF program where they will be reviewed if they meet NSF proposal preparation requirements. All proposals are carefully reviewed by a scientist, engineer, or educator serving as an NSF Program Officer, and usually by three to ten other persons outside NSF who are experts in the particular fields represented by the proposal. These reviewers are selected by Program Officers charged with the oversight of the review process. Proposers are invited to suggest names of persons they believe are especially well qualified to review the proposal and/or persons they would prefer not review the proposal. These suggestions may serve as one source in the reviewer selection process at the Program Officer's discretion. Submission of such names, however, is optional. Care is taken to ensure that reviewers have no conflicts of interest with the proposal.

A. NSF Merit Review Criteria

All NSF proposals are evaluated through use of the two National Science Board (NSB)-approved merit review criteria: intellectual merit and the broader impacts of the proposed effort. In some instances, however, NSF will employ additional criteria as required to highlight the specific objectives of certain programs and activities.

The two NSB-approved merit review criteria are listed below. The criteria include considerations that help define them. These considerations are suggestions and not all will apply to any given proposal. While proposers must address both merit review criteria, reviewers will be asked to address only those considerations that are relevant to the proposal being considered and for which the reviewer is qualified to make judgements.

What is the intellectual merit of the proposed activity?
How important is the proposed activity to advancing knowledge and understanding within its own field or across different fields? How well qualified is the proposer (individual or team) to conduct the project? (If appropriate, the reviewer will comment on the quality of the prior work.) To what extent does the proposed activity suggest and explore creative, original, or potentially transformative concepts? How well conceived and organized is the proposed activity? Is there sufficient access to resources?