pect of the program might be a once-a-year conference at an Army laboratory or facility, where the principal investigators (PIs) would report on accomplishments during the year. The program needs enlightened management to support interdisciplinary work accomplished through the interaction of a diversity of PIs. The essence of the program would be the achievement of fundamental advances in network research based on, among other things, statistical physics, applied mathematics, and the development of mathematical models of social phenomena by generously funding only exceptionally talented individuals who are collectively organized into a national network.
Such a program would be the first to address the needs of network science per se. It would be devoted to the study of networks as coherent entities characterized by their architecture, structure, and dynamics. By deliberately adopting a broad theoretical and methodological focus, the program would encourage the creation of fundamentally novel ideas. A wide diversity of approaches can be a key feature of long-term success. Keeping the goals broad and flexible would allow the Army to cultivate such diversity, whereas narrowly defining the program would eliminate much of the creative potential for breakthroughs and new ideas.
The Army’s needs are broad and fundamental in nature: It must learn how to approach the creation of a predictive description of large, interacting, layered networks. A basic science program is the first step toward building the critical mass of talent needed to address specific Army problems in this area. This modest approach would allow the Army to identify the relevant research community and organize it so that, in time, it could be called upon to address more specific needs.
The proposed approach differs from existing programs in agencies such as the National Science Foundation (NSF) and the National Institutes of Health (NIH) in that it focuses on network science per se. While a significant amount of research is taking place in communities addressing the applications of networks, almost none of this research is funded by dedicated network science programs.
As a consequence of its discussions with Army and DOD representatives, the committee has come to realize that the fundamental problems underlying effective network-centric operations (NCO) lie in the social domain. Yet how people interact and utilize technology or make decisions based on shared knowledge are areas almost unexplored in the Army’s current basic research portfolio. Applications to biology, engineering, and the physical sciences are also essential to Army applications, but the Army is already funding research in these areas. The committee suggests that, on the margin, the most significant problem is not how to build better satellites, tanks, or medicines, but rather how to organize millions of individuals to collect intelligence, deliver supplies, and prosecute wars over an increasingly global and constantly shifting geographical and political playing field (Garstka and Alberts, 2004). This is a monumental problem that has not, however, traditionally been the province of science. Rather it has been managed through a mixture of intuition, experience, and tradition. A significant fraction of the proposed program should address this organizational problem the way scientific problems are addressed: through a combination of theoretical modeling, data analysis, and controlled experimentation.
In Scenario 1 (Appendix E) the committee indicates promising research topics in four broad areas: network structure, network dynamics, network robustness and vulnerability, and network services. Each area has theoretical, empirical, and experimental components. A basic research investment in each of these areas of network science would provide value for the Army. The committee also offers suggestions for improving the return on investment by modest changes in the way that basic research in network science is managed.
Scenario 2 envisages applying best practices in industrial R&D management to the Army’s investments in projects that combine basic and applied network science. Specifically, the committee expects the objective of these projects to be the articulation of technology investment options that could be exercised by the Army and its vendors to provide a desired capability. The amount of this investment is envisaged to be between $25 million and $100 million annually, roughly $25 million per project. There are expected to be investments in the university community for the basic research and in both Army in-house activities and commercial firms for the applied research. The committee envisages, however, that the R&D projects would be managed in a way profoundly different from the way in which current Army in-house and external centers are managed.
The selection of projects to be funded would be market driven and controlled by a top-level Army team. It is expected that connections between the basic and applied portions of the research will be much more intimate. Modern Internet collaborative tools would be used to manage the day-to-day work in rough analogy to the global design of industrial products. The activities are managed in small, intimate groups devoted to specific subprojects that are integrated into the overall project in a looser networked fashion. People flow from one small group to another over time. The entire team makes up a social network consisting of smaller, more tightly coupled social networks. In short, this scenario envisages the application of modern communications networks and tools and the insights of modern social network theory to transform the management of Army R&D projects.
In Appendix E the committee provides details for market-driven management of such projects. The next-generation R&D model is a new and different approach similar to that of networked organizations like eBay, Intel, and GE. It is based on principles that have worked for many successful