**KDI:**

**Knowledge and Distributed Intelligence **

**in the Information Age**

**[\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline}**

***[Proposal Solicitation NSF 98-55]{.underline}***

**· [KNOWLEDGE NETWORKING]{.underline}**

**· [LEARNING AND INTELLIGENT SYSTEMS]{.underline}**

**· [NEW COMPUTATIONAL CHALLENGES]{.underline}**

**[ ]{.underline}[DEADLINES:]{.underline}**

[ April 1, 1998: Letter of Intent.]{.underline}

[ May 11, 1998: noon local time, for Knowledge Networking (KN) Full
Proposals.]{.underline}

[ May 12, 1998: noon local time, for New Computational Challenges (NCC)
Full Proposals.]{.underline}

[ May 13, 1998: noon local time, for Learning and Intelligent Systems
(LIS) Full Proposals.]{.underline}

[ ]{.underline}*[Next proposal deadline will be February 1, 1999, Full
Proposals]{.underline}*

Note: For proposals encompassing more than one KDI component,

the deadline is determined by the primary component, indicated by

the choice of organizational unit \-- KDI/KN, KDI/LIS, KDI/NCC \-- at

the top of the cover sheet in FastLane.

* * ***[Introduction]{.underline}***

***[ ]{.underline}***The recent growth in computer power and
connectivity has changed the face of science and engineering. The future
promises continued acceleration of these changes. The challenge today is
to build upon the fruits of this revolution.

[ This rise in power, connectivity, content, and flexibility is so
fundamental that it is dramatically reshaping relationships among people
and organizations, and quickly transforming our processes of discovery,
learning, exploration, cooperation, and communication. It permits us to
study vastly more complex systems than was hitherto possible and
provides a foundation for rapid advances in understanding of learning
and intelligent behavior in living and engineered systems. Today\'s
challenge is to realize the full potential of these new resources and
institutional transformations. Knowledge and Distributed Intelligence
(KDI) is a Foundation-wide effort designed to catalyze this next
step.]{.underline}

[ ]{.underline}***[Aims of the Knowledge and Distributed Intelligence
Activity]{.underline}***

NSF aims to achieve, across the scientific and engineering communities,
the next generation of human capability to generate, gather, model, and
represent more complex and cross-disciplinary scientific data from new
sources and at enormously varying scales; to transform this information
into knowledge by combining, classifying, and analyzing it in new ways;
to deepen our understanding of the cognitive, ethical, educational,
legal, and social implications of new types of interactivity; and to
collaborate in sharing this knowledge and working together
interactively.

The anticipated payoffs of KDI research include:

· [Deep, far-reaching scientific discovery]{.underline}

· [Increases in scientific productivity, and in the timeliness and
quality of the results]{.underline}

· [Increased ability to handle problems of greater complexity, scale,
and structure ]{.underline}

· [The creation of new scientific and engineering communities to exploit
novel discoveries]{.underline}

· [Enhancements in science and engineering education through development
of richer learning tools, technologies, and environments, and more
universal access to richer resources and tools]{.underline}

· [Enhanced understanding of the processes and results of learning and
applications thereof]{.underline}

· [A more complete understanding of the fundamental processes of
distributed intelligence in natural and artificial systems and their
application ]{.underline}

· [An understanding of the legal, ethical, and societal implications of
the increased capability to gather and access information]{.underline}

· [Enhanced ability to communicate and transfer new understanding and
technological innovations to society ]{.underline}

· [Advances in statistical data reduction, data visualization, data
mining, and data organization for retrieval so as to utilize vast stores
of data]{.underline}

· [Improved methods for expressing, computing with, and evaluating
different types of uncertainties in real-world data]{.underline}

[ ]{.underline}***[Three Foci of KDI: KN, LIS, and NCC]{.underline}***

To achieve the aims of KDI, proposals are solicited from individuals or
groups for research that is inherently multidisciplinary^\*^[^1] or
that, while lying within a single discipline, has clear impact on at
least one other discipline.

In FY 1998, KDI will have three foci: Knowledge Networking (KN);
Learning and Intelligent Systems (LIS); and New Computational Challenges
(NCC). This document describes the three KDI foci, and serves as a
solicitation for proposals in all three areas. We anticipate that
research on many important problems will span the foci of KN, LIS, and
NCC, and proposals that do so are most welcome.

KN will focus on attaining new levels of knowledge integration,
information flow, and interactivity among people, organizations, and
communities.

LIS will emphasize research that advances basic understanding of
learning and intelligence in natural and artificial systems and supports
the development of tools and environments to test and apply this
understanding in real situations.

NCC will emphasize new computational approaches to frontier science and
engineering problems as well as problems involving data intensive
computations and simulations.

More detailed information about the three foci and their particular
emphases for FY 1998 follows.

**[KNOWLEDGE NETWORKING (KN)]{.underline}**

***[Introduction ]{.underline}***

Knowledge Networking research aims to build the scientific bases for
attaining new levels of interactivity and flow of information and
knowledge among people, organizations, and communities. Thus, it will
enable scientists, engineers, and other members of society to act in
concert to address ever more complex scientific and societal problems.

~~ ~~The goals of Knowledge Networking (KN) are (1) to understand the
fundamental processes through which knowledge is created, communicated,
validated, and valued in distributed systems of information, both
natural and engineered, and (2) to improve the technical, social,
educational, and economic performance of knowledge generation and use,
collaborative computation, and remote interaction.

KN will support multidisciplinary research on developing and employing
the next generation of communication networks, associated information
repositories, collaborative technologies, and knowledge management
techniques to gather, create, distribute, use, and evaluate knowledge in
new and secure ways. This explicitly includes research on the human,
behavioral, social, and ethical dimensions of knowledge networking.

The objectives of Knowledge Networking are:

· [To enhance communication across disciplines, languages, and cultures
]{.underline}

· [To improve the processing and integration of knowledge from different
sources, domains, and non-text media types ]{.underline}

· [To increase the effectiveness of teams, organizations, classrooms, or
communities that work together across distances or over
time]{.underline}

· [To deepen understanding of the ethical, legal, and social
implications of new developments in connectivity ]{.underline}

[ Proposals should address one or more of these objectives.]{.underline}

[ ]{.underline}***[Research Emphases for FY 1998]{.underline}***

In FY 1998, KN will emphasize three broad areas of knowledge networking:
foundational research; prototype development and research; and ethical,
social, and behavioral research. These areas are described more fully
below. The examples given below are meant to be illustrative, not
limiting.

**[Foundational Research]{.underline}**

The foundations for KN require basic research on organizing, distilling,
securing, and collectively acting upon information through dynamic
distributed processes; methods for building and linking complex data
structures, computations, and knowledge processes; and tools for
navigating, gathering, and displaying widely scattered and disparate
information. These foundations focus on transforming information into
knowledge and broadly disseminating that knowledge. The usage of these
tools in transforming and disseminating scientific knowledge will depend
critically on the participation of scientists and engineers working in
the specific knowledge domains of their expertise and on the processes
of scientific research in those domains.

[Processes and Dynamics of Distributed Intelligence]{.underline}

· [Computational aspects of distributed intelligence: dynamic task
allocation, interaction, coordination, process and organization
representation, collective learning, consistency management, protocol,
negotiation]{.underline}

· [Cognition by groups, teams, and organizations]{.underline}

· [Dynamics, adaptation and evolution of knowledge networks with
particular attention paid to the utilization of domain specific
knowledge and processes]{.underline}

· [Pathologies in large-scale distributed knowledge systems, such as
malicious agents, viruses, overload, \"knowledge storms"]{.underline}

[ Managing Heterogeneity and Achieving Interoperability]{.underline}

Computational and organizational foundations for coupling models,
knowledge, functionality, and human activities across scientific
disciplines and within different branches of individual disciplines,
including:

· [Managing heterogeneity and interoperability in dimensions such as
syntax, semantics, scale, and structure ]{.underline}

· [Composition of distributed models and activity]{.underline}

· [The use of discipline-specific scientific information and processes
in the design of knowledge interoperability criteria within and between
disciplines]{.underline}

[ Computational Infrastructure, Tools and Environments]{.underline}

· [Secure and efficient network and communications infrastructures for
interactivity, including approaches to resource-limited and real-time
interactivity]{.underline}

· [Security, validation, authentication, and credibility of
information]{.underline}

· [Large-scale remote data acquisition, distributed data analysis,
experiment and sensor control, and simulation; especially interactive
and real-time aspects ]{.underline}

· [Distributed knowledge: sharable ontologies, processes for distributed
classification and taxonomy, collaborative knowledge construction,
representation and filtering tools, digital libraries and repositories
across disciplines and application domains, and translation of
representations]{.underline}

[ ]{.underline}**[Prototype Development and Research]{.underline}**

KN requires basic research and the accumulation of experience in
creating, using, and understanding the performance of domain-specific
prototype knowledge networks.

· [Constructing and using working prototypes of domain-specific,
multidisciplinary knowledge networks and collaboratories. Of specific
interest are prototypes and experiments that are
]{.underline}*[compatible]{.underline}*[ across networks and
disciplines, ]{.underline}*[accessible]{.underline}*[ to outside
communities, and ]{.underline}*[inclusive]{.underline}*[ of
disaggregated or virtual teams and members of very different disciplines
]{.underline}

· [Studies of the physical, behavioral, and organizational design of
knowledge networks and electronic collaborative work environments,
including organizational and decision-making processes and problems
specific to individual scientific disciplines]{.underline}

· [Development of engineering tools and methods for designing,
reproducing, and extending knowledge networks]{.underline}

· [Empirical studies of knowledge networks as arenas for scientific
experimentation, data gathering, analysis, and decision
making]{.underline}

[ ]{.underline}**[Ethical, Social and Behavioral Research on Knowledge
Networks]{.underline}**

Knowledge networks create new patterns of information flow, interaction,
and organization that require basic research into their social,
political, ethical, and economic characteristics. Normative and
empirical research are needed to address complex problems raised by the
new technologies envisioned under KN.

[Knowledge Dissemination and Sustainable Use of Knowledge Networks
]{.underline}

· [Cognitive and social processes of creating, developing, maintaining,
and dismantling knowledge networks]{.underline}

· [Intellectual property, privacy, confidentiality and credibility of
information and of participants in knowledge networks]{.underline}

· [Adapting knowledge networks to human needs, preferences, and
abilities, including cognitive, cultural, economic, and educational
differences in the access, use, and benefit from knowledge
networks]{.underline}

[ Social Integration and Impacts of Knowledge Networking]{.underline}

**· **[New methodologies, metrics, and investigations of the scientific,
technical, economic, and human performance capabilities and the social,
organizational, and economic impacts of knowledge networks ]{.underline}

· [Ethical, social, political, legal, and economic processes that
influence the creation, use, ownership, and governance of knowledge
networks]{.underline}

· [Creation, distribution, life course, and other characteristics of
"knowledge capital" ]{.underline}

[ ]{.underline}**[LEARNING AND INTELLIGENT SYSTEMS (LIS)]{.underline}**

**[ ]{.underline}*Understanding and Enhancing the Ability to Learn and
Create***

***[ ]{.underline}**[Introduction]{.underline}***

Efforts to understand the nature of learning and intelligence, and the
realization of these capacities in the human mind, are among the most
fundamental activities of science. The goal of LIS is to stimulate
research that will advance and integrate concepts of learning and
intelligence emerging from theoretical and experimental work in a
variety of disciplines, including education, cognitive science, computer
science, neuroscience, engineering, social science, and physical
science. Accordingly, LIS encompasses studies of learning and
intelligence in a wide range of systems, including (but not limited to)
the nervous systems of humans or other animals; networks of computers
performing complex computations; robotic devices that interact with
their environments; social systems of human or non-human species; and,
formal and informal learning situations. LIS also includes research that
promotes the development and use of learning technologies across a broad
range of fields. Development of new scientific knowledge on learning and
intelligent systems, and its creative application to education and
learning technologies, are integral parts of this solicitation.

There are two parallel and compelling reasons for focusing on the
general area of learning and intelligent systems:

First, there has been a convergence of techniques and ideas addressing
questions in cognitive science and behavior of intelligent systems. For
example, there has been a growing use of neural networks, pattern
recognition, visualization, simulation, nonlinear dynamical systems
analysis, and probabilistic and statistical learning theory in these
fields. As another example, researchers in many disciplines \--
including biochemistry, biophysics, neuroscience, and cognitive science
\-- are studying how the nervous system changes as a result of
experience, at levels ranging from individual synapses, to neural
circuits, to brain systems subserving complex perceptual and cognitive
functions. Although concepts and methods differ across levels of
analysis, a growing integration across levels is creating fruitful
theoretical frameworks and rich bodies of data for advancing our
understanding of learning and intelligent systems.

Second, as our knowledge and understanding of learning, intelligent
systems, and information technologies grows, so does the need to
integrate and apply this understanding within a broad social context.
Research on associated technologies and systems can and has enabled
better understanding of learning and cognition and has led to better
classroom practice. Integrating research with prototyping in these
critical areas promises rapid advances in both theory and application.

For information regarding proposals funded by LIS in FY 1997 see
[http://www.ehr.nsf.gov/lis/award97.htm]{.underline}

***[Research Emphases for FY 1998]{.underline}***

~~ ~~The research emphases for LIS in FY 1998 are essentially the same
as in FY 1997. Specifically, LIS seeks projects that propose:

1\. To identify, investigate, and model the ways natural and artificial
systems operate in order to arrive at unifying principles that explain:

· [How learning and intelligent behavior occur in humans, in other
natural systems, and in artificial systems]{.underline}

· [The types of learning tasks and decision making that are best suited
for each]{.underline}

· [The kinds of information and decisions each characteristically
produces or creates]{.underline}

· [The impact of interactions among alternative interactive learning
environments, social contexts and experiences ]{.underline}

[ 2. To enhance the ability of students and researchers to learn and to
create by developing a comprehensive set of learning and research tools,
methods and technologies that use biological, behavioral, cognitive,
linguistic, social, and educational concepts with interactive,
collaborative, and multisensory technologies, and are accessible to
people with varied abilities, knowledge, and expectations.]{.underline}

[ 3. To further basic research designed to develop fundamental knowledge
concerning the nature of learning and intelligence in natural or
artificial systems, and to apply such knowledge in a variety of
situations such as education, learning technologies, design of robotic
devices and smart instrumentation, and networks of computer
systems.]{.underline}

[ ]{.underline}**[NEW COMPUTATIONAL CHALLENGES (NCC)]{.underline}**

***[Introduction]{.underline}***

New Computational Challenges (NCC) focuses on research and tools to
discover, model, simulate, display, and understand complex systems or
complicated phenomena; to control resources or deal with massive volumes
of data in real time, particularly distributed resources or data; to
represent, predict, and design complex systems; and to understand their
behaviors. NCC builds on the success, but broadens the scope, of prior
NSF efforts such as the Grand Challenge initiatives.

NCC aims to enable wide scientific collaboration and effective
management of complex systems. This will require significant advances in
hardware and software to handle multiple representations, scales, and
structures; to enable distributed collaboration among disparate
communities; and to facilitate real-time interactions and control.

Many phenomena are too complicated to understand in detail from simple
observation or by reduction to isolated components and often require the
coupling of disciplinary scientists and engineers and those involved in
enabling methods and technologies in order to produce new ways to
approach previously intractable problems. The very structure of the
problem \-\-- its mathematical, logical, or computational form \-\-- may
change as scale, level of resolution, or granularity changes. Many
important problems require multiple data types, qualitative information,
feedback during the computation to steer it, and a variety of numerical
and symbolic computations. Advances in raw computing power have outpaced
the effectiveness of existing tools and the degree to which they will
scale to large numbers of distributed systems. The development of
meaningful simulations that combine disparately structured models into
new types of simulations is critical. While understanding complex
phenomena is obviously important, predicting their behavior and
potentially controlling or changing it, and doing so in real time, alter
the fundamental nature of the problem and introduce enormous challenges
across a broad spectrum of science and engineering research.

***[Research Emphases for FY 1998]{.underline}***

As noted in the introduction, many scientific and engineering problems
are encompassed by new challenges in computation. For Fiscal Year 1998,
NCC will emphasize only two of these: (1) scientific and engineering
problems involving interactions between phenomena at different scales or
structures, and (2) problems requiring a dynamic interplay between
computations and data. Proposals that address these two problems or that
use them to motivate advances in enabling computational technologies are
welcome. In subsequent years, the focus of NCC may be broadened to
include other computational challenges in addition to the two chosen for
emphasis in FY 1998.

· **[Problems of Scale and Structure]{.underline}**

[ Problems involving multiple scales in space or time occur throughout
engineering and science. Examples include inferring macroscopic
properties of a material from its microstructure; turbulence, which
plays a critical role in fluid flows as varied as mixing of fuel and air
in combustion engines, airflow around an airplane, and blood flow in the
heart; scaling of flow in porous media from the pore level to the field
level, which has important applications to oil recovery and
environmental issues; and fluid circulation in the oceans and the
atmosphere. The brain, a dynamic, highly-connected, multi-level
organization, involves both scale and structure.]{.underline}

[ An overlapping set of complex computational problems are those
concerning phenomena that arise from interactions among large numbers of
relatively simple objects or elements. Examples include the complex
perceptual and cognitive phenomena that arise from interactions among
neurons in the brain; the behavior of the immune system in responding to
antigens; social behaviors in animals ranging from insects to humans;
human economic and social activities; and, the operation of distribution
networks such as power grids and communication systems. ]{.underline}

· **[Interplay Between Computations and Data]{.underline}**

[ Better understanding of complex phenomena now requires a dynamic
interplay between computations and data, often in real time. Most
simulations are entirely initial-value in style: guess at a start,
compute, see what happens, then change the guess. Simulations that could
adapt to intermediate results or changing data would greatly reduce the
number of iterations. In addition, some problems require this adaptive
interplay for effective solution. These include command-control problems
such as air traffic control, dispatch systems, radar and sonar
identification, and other recognize-and-respond problems. Resource
management and process control problems, especially with time
constraints, are also of this kind. ]{.underline}

[ Data-mining problems are of a different nature. Here the idea is to
discover \"unusual\" items in a large dataset. Examples arise in
seismology, high-energy physics, astronomy, credit card fraud, and
management and protection of networked resources such as databases or
computers. ]{.underline}

[ Another kind of problem is combining different kinds of data. There
are difficulties in validating data, assessing the effects of individual
errors and their combinations, and in representing and visualizing data;
practical methods for a multiplicity of large-scale datasets are needed.
]{.underline}

[ Understanding of complex phenomena often depends on mapping different
kinds of data against each other. Examples include tracking any time
evolution or spatial evolution of phenomena against a spatial database
(GIS, satellite and other map data), such as agricultural data, erosion
and floods, epidemics, and other ecological/environmental phenomena; and
mapping measurements of a behavior against measurements of physiological
change, e.g., speech or vision against brain activity.]{.underline}

[ The examples given in the preceding paragraphs are meant to be
illustrative and not limiting.]{.underline}

[ ]{.underline}***[KDI Review Criteria]{.underline}***

[All proposals are subject to the guidelines and review criteria
described in the newly revised NSF Grant Proposal Guide (GPG),
]{.underline}**[NSF 98-2]{.underline}**[. For a description of NSF
program activities, refer to: Guide to Programs, ]{.underline}**[NSF
97-150]{.underline}**[. Single copies of these publications are
available at no cost from the NSF Publications Clearinghouse (301)
947-2722, or via E-mail (Internet: pubs@nsf.gov), and they can be found
on the NSF Website, http://www.nsf.gov.]{.underline}

[ The new NSF general review criteria specified in GPG for proposals
submitted to NSF after October 1st, 1997 are: (1) What is the
intellectual merit of the proposed activity? and (2) What are the
broader impacts of the proposed activity? Under these broad criteria,
for this solicitation, reviewers, to the extent they are qualified to
make judgments, will consider the following questions:]{.underline}

[ I. Intellectual Merit]{.underline}

· [To what extent does the proposed activity suggest and explore
creative original concepts?]{.underline}

· [What is the potential and general impact of the project on the
science being addressed?]{.underline}

· [Is there potential multidisciplinary synergism among the various
research components? What is the potential multidisciplinary impact of
the research?]{.underline}

· [How well conceived and organized is the proposed
activity?]{.underline}

· [What is the potential of the project to make new advances, mobilize
new human resources, or lead to fundamental changes in
methodology?]{.underline}

· [How well qualified is the proposer (individual or team) to conduct
the project? (If appropriate, the reviewer will comment on the quality
of prior work.)]{.underline}

· [Is there sufficient access to resources needed for the
project?]{.underline}

· [In the case of group proposals, is there an effective
management/leadership plan and what is the evidence that the team can
work together?]{.underline}

[ ]{.underline}II. Broader Impacts

· [How well does the proposed activity advance discovery and
understanding while promoting teaching, training, and learning? Is the
training of students and researchers integrated into the
project?]{.underline}

· [How well does the proposed activity broaden the participation of
underrepresented groups (e.g., gender, ethnicity, disability,
geographic, etc.)?]{.underline}

· [To what extent will the proposed activity enhance the infrastructure
for research and education, such as facilities, instrumentation,
networks, and partnerships?]{.underline}

· [Do the concepts and methodologies being developed have the long term
potential for applicability to real world problems including research
and development in education?]{.underline}

· [How effective are the plans for dissemination of the results across
several science and engineering disciplines, educational communities,
and/or application groups?]{.underline}

***[KDI Proposal Submission and Review Process]{.underline}***

**[Who May Submit]{.underline}**

Proposals submitted on behalf of individuals or groups in response to
this solicitation will be accepted from colleges, universities, and
other nonprofit research institutions in the United States.
Multi-institutional arrangements are permitted and partnerships with
industry are encouraged.

**[How to Submit]{.underline}[ ]{.underline}**

**[Letter of Intent]{.underline}[ ]{.underline}**

[To help plan for the review process for KDI proposals, a short
electronic message of intent to submit a proposal should be sent prior
to ]{.underline}**[April 1, 1998 to]{.underline}**[
]{.underline}**[kdiletin@nsf.gov]{.underline}**[. The message (at most
two pages, in unencoded ASCII text) should indicate as specifically as
possible the subject and a short description of the anticipated
research, the focus (or foci) you judge to be most closely related to
the project (i.e., one or more of KN, LIS, and NCC), and a list of the
probable participants and their institutional affiliations.
]{.underline}

**[Proposals]{.underline}**

KDI proposals are required to be submitted electronically using the NSF
FastLane system for electronic proposal submission and review, available
through the World Wide Web on the FastLane Home Page at
[http://www.fastlane.nsf.gov` `]{.underline}Instructions for preparing
and submitting a standard NSF proposal via FastLane are located at
[http://www.fastlane.nsf.gov/a1/newstan.htm]{.underline}.

[In order to use NSF FastLane to prepare and submit a proposal, you must
use a browser that supports multiple buttons and file upload (e.g.,
Netscape 3.0 and above for Windows, UNIX, or Macintosh). In addition,
Adobe Acrobat Reader is needed to view and print forms. Adobe Acrobat
Exchange 2.0 or above, Adobe Acrobat Distiller 2.0 or above, or Adobe
Acrobat 3.X (which includes Adobe Exchange and Adobe Distiller) is
needed for creating PDF files. To access the FastLane Proposal
Preparation application, your institution needs to be a registered
FastLane institution. A list of registered institutions and the FastLane
registration form are located on the FastLane Home Page. To register an
organization, authorized organizational representatives must complete
the registration form. Once an organization is registered, PINs for
individual staff are available from the organization's sponsored
projects office.]{.underline}

[For questions or problems concerning submitting a KDI proposal via
FastLane, please contact a FastLane User Support person at electronic
mail: flprop@nsf.gov or phone: (703) 306-1142 (If you reach the
automated attendant, please dial extension 4686).]{.underline}

[It is advisable to submit your proposal before the day of the deadline
to avoid the possibility of encountering a queue.]{.underline}

[The submission must follow GPG guidelines, with the following additions
and exceptions to the guidelines:]{.underline}

[On the cover page you must enter NSF 98-55 as the program solicitation
number and you must enter KDI/KN, KDI/LIS, or KDI/NCC, as the NSF
organization to consider this proposal. In case the proposal is at the
intersection of several KDI foci, choose the primary one and indicate in
the Project Description the overlap.]{.underline}

[The following makes up the Project Description file to be uploaded to
FastLane:]{.underline}

[1) Project Summary]{.underline}

[2) A project description of up to 15 single-spaced pages. The
description should indicate the roles of the senior investigators on the
project.]{.underline}

[3) For each PI or co-PI, up to 2 additional pages to describe results
of prior NSF support focusing only on those results relevant to the
proposed project.]{.underline}

4\) [An additional section, up to 2 pages, that describes and justifies
specifically a) the plans for dissemination of the results and b) the
institutional commitment as to space and equipment.]{.underline}

5\) For projects with a three year budget exceeding \$1.0 million
(optional for projects with smaller budgets), an additional page
describing realistic performance goals for each year.

6\) For projects involving more than one university department, or more
than one organization, an additional 1-page description of the project
management plan. Subcontracts may be used in multi-institutional
proposals.

**[Full proposals must be received at NSF no later than 11.59.59 P.M.
EST, May 8, 1998.]{.underline}**

**[A hard copy of NSF Form 1207 (Cover Sheet) with original signatures
must be received by 5:00 P.M. EST, May 22, 1998. The Cover Sheet should
be sent to the following address:]{.underline}**

[Proposal Number \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline}

[Solicitation No. NSF 98-55]{.underline}

[NATIONAL SCIENCE FOUNDATION PPU]{.underline}

[4201 WILSON BLVD.]{.underline}

[ARLINGTON, VA 22230]{.underline}

[All proposals will undergo review by a panel or panels specially
constituted for the KDI theme. Ad hoc mail reviews will be employed
where additional disciplinary expertise is necessary.]{.underline}

**[Inquiries]{.underline}**

Questions of a general nature regarding KDI (submission, review and
award processes, award sizes, general requirements, etc.) should be
submitted via e-mail to [kdi@nsf.gov]{.underline}. Specific topical
questions on one of the three KDI focus areas should be e-mailed to the
respective address:

[KN: kn@nsf.gov]{.underline}

[LIS: lis@nsf.gov]{.underline}

[NCC: ncc@nsf.gov]{.underline}

[Additional detailed information on KDI in general, as well as KN, LIS,
and NCC can be obtained from
]{.underline}*[http://www.nsf.gov/kdi]{.underline}*[. In particular,
lists of reports, studies, and workshop proceedings, as well as
motivating scientific problems relevant to these foci can be accessed at
this website.]{.underline}

***[Award Information]{.underline}***

Under this announcement, NSF solicits proposals for any funding amount
up to \$1.0 million per year for up to three years, and expects to make
grants at a wide variety of award sizes and durations. NSF expects to
fund approximately 60 to 75 standard three year research awards under
KDI, depending on the quality of submissions and the availability of
funds. In exceptional cases, awards for up to five years may be
considered if the justification and promise are compelling. All awards
will be made as grants subject to specified reporting procedures.
Approximately \$50 million will be available for KDI in FY 1998.

A second KDI competition will be held in FY 1999, subject to
availability of funds. An updated solicitation, which may include
revised research emphases or adjustments to submission and review
procedures, will be released in advance of this competition.

***[Grant Administration]{.underline}***

Awards made as a result of this announcement are administered in
accordance with the terms and conditions of NSF GC-1, \"Grant General
Conditions,\" or FDP-III, \"Federal Demonstration Partnership General
Terms and Conditions,\" depending on the grantee organization. Copies of
these documents are available at no cost from the NSF Publications
Clearinghouse (301) 947-2722, or via e-mail [pubs@nsf.gov]{.underline}
(Internet). More comprehensive information is contained in the NSF Grant
Policy Manual (NSF 95-26, July 1995), for sale through the
Superintendent of Documents, Government Printing Office, Washington, DC
20404. The telephone number at GPO is (202) 783-3238 for subscription
information.

***[Reporting Requirements]{.underline}***

Upon completion of the project, a Final Project Report (NSF Form 98A),
including Part IV Summary, will be required. NSF will send the form with
Part I information preprinted to the Principal Investigator (Project
Director) approximately one month prior to the grant\'s expiration date.
Applicants should review the sample form in the GPG prior to proposal
submission so that appropriate tracking mechanisms are included in the
proposal plan to ensure that complete information will be available at
the conclusion of the project.

The Foundation provides awards for research in the sciences and
engineering. The awardee is wholly responsible for the conduct of such
research and preparation of the results for publication. The Foundation,
therefore, does not assume responsibility for the research findings or
their interpretation.

***[Additional Information]{.underline}***

The Foundation welcomes proposals from all qualified scientists and
engineers and strongly encourages women, minorities, and persons with
disabilities to compete fully in any of the research related programs
and activities described here. In accordance with federal statutes,
regulations, and NSF policies, no person on grounds of race, color, age,
sex, national origin, or disability shall be excluded from participation
in, be denied the benefits of, or be subject to discrimination under any
program or activity receiving financial assistance from the National
Science Foundation.

Facilitation Awards for Scientists and Engineers with Disabilities
(FASED) provide funding for special assistance or equipment to enable
persons with disabilities (investigators and other staff, including
student research assistants) to work on NSF projects. See the program
announcement or contact the program coordinator at (703) 306-1636.

Privacy Act and Public Burden. The information requested on proposal
forms is solicited under the authority of the National Science
Foundation Act of 1950, as amended. It will be used in connection with
the selection of qualified proposals and may be disclosed to qualified
reviewers and staff assistants as part of the review process; to
applicant institutions/grantees; to provide or obtain data regarding the
application review process, award decisions, or the administration of
awards; to government contractors, experts, volunteers, and researchers
as necessary to complete assigned work; and to other government agencies
in order to coordinate programs. See Systems of Records, NSF 50,
Principal Investigators/Proposal File and Associated Records, and
NSF-51, 60 Federal Register 4449 (January 23, 1995). Reviewer/Proposal
File and Associated Records, 59 Federal Register 8031 (February 17,
1994). Submission of the information is voluntary. Failure to provide
full and complete information, however, may reduce the possibility of
your receiving an award.

Public reporting burden for this collection of information is estimated
to average 120 hours per response, including the time for reviewing
instructions. Send comments regarding this burden estimate or any other
aspect of this collection of information, including suggestions for
reducing this burden, to Gail McHenry, Reports Clearance Officer,
National Science Foundation, 4201 Wilson Boulevard, Arlington, VA 22230.

The National Science Foundation has TDD (Telephonic Device for the Deaf)
capability, which enables individuals with hearing impairment to
communicate with the Foundation about NSF programs, employment, or
general information. To access NSF TDD, dial (703) 306-0090; for FIRS,
1-800-877-8339.

CFDA: CFDA #47.041, 47.049, 47.050, 47.070, 47.074, 47.075, 47.076,
47.078

[OMB: 3145-0058 ]{.underline}

[P.T.: 04, 18, 35, 36, 38]{.underline}

[KW.: 0414007, 0503000, 0607004, 0607070, ]{.underline}

[0706000, 0710015, 404000, 410000, 414000, ]{.underline}

[1002030, 1004000, 1010000, 1016000]{.underline}

[^1]: ^\ [\*]{.underline}^[ Throughout we will use "multidisciplinary"
    to include "interdisciplinary" and
    "cross-disciplinary."]{.underline}