Foresight and Understanding from Scientific Exposition (FUSE)

Today, the identification and assessment of emerging technical capabilities is a time-consuming, domain-specific, and expert-intensive process. This demanding process is often carried out under severe time constraints on either too much or too little data, with limited reproducible auditing and bias controls, and with limited systematic validation against real world activities. furthermore, the increasing globalization of science and technology raises the potential for high-impact technical capabilities to emerge in increasingly diverse technical, socio-economic, and geographic areas.

Analysts and subject-matter experts need a reliable, evidence-based capability that allows them to dramatically accelerate the horizon-scanning process and reduce the labor involved to identify specific technical areas for in-depth review. It is essential that an automated capability can nominate both known and novel technical areas based on quantified indications of technical emergence with sufficient supporting evidence and arguments for that nomination. It is anticipated that FUSE technology will provide new analytic tools to help analysts maintain technical vigilance, across all disciplines and multiple languages, in the face of the exponentially growing flood of textual content.

The FUSE Program seeks to develop automated methods that aid in the systematic, continuous, and comprehensive assessment of technical emergence using information found in published scientific, technical, and patent literature. A fundamental hypothesis if the FUSE Program is that real-world processes of technical emergence leaves discernible traces in the public scientific, technical, and patent literature. FUSE envisions a system that could (1) process the massive, multi-discipline, growing, noisy, and multilingual body of full-text scientific, technical, and patent literature from around the world; (2) automatically generate and prioritize related document groups that represent an emerging technical area, nominate those that exhibit technical emergence, and provide compelling evidence for the emergence; and (3) provide this capability for literature in English and at least two non-English languages. Technology developed from the FUSE Program will automatically nominate both known and novel technical areas based on quantified indicators of technical emergence with sufficient supporting evidence and arguments for that nomination. The FUSE Program will also address the vital challenge of validating such a system, using real world data.

Research Area(s)

  • Technical emergence
  • Text analytics
  • Knowledge discovery
  • Big data
  • Social network analysis
  • Natural language processing
  • Forecasting
  • Machine learning

Related Publications

To access FUSE program-related publications, please enter the following into a Google Scholar search query: "D11PC20152 OR D11PC20153 OR D11PC20154 OR D11PC20155 OR D11PC2015"

Related Article(s)

What's the next big tech trend? This federal agency thinks it can predict the answer

Text-mining offers clues to success

The Shape of the Future: From TIPS to FUSE

Raytheon BBN gets $1.7M federal deal to develop automation system

Press Releases and Statements

IARPA Launches New Program to Enable the Rapid Discovery of Emerging Technical Capabilities