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Interim Report on the Second Triennial Review of the National Nanotechnology Initiative (2013) / Chapter Skim
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3 The Role of Metrics
Pages 11-15

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From page 11...
... In manufacturing, a material or product is measured for three reasons: for quality control, for quality improvement, and to establish that a legal requirement specified in a contract between a supplier and a customer has been met. In the first case, all that is needed is a simple, reliable measure to identify when an acceptable outcome is no longer being produced; measurement yields a result as simple as "acceptable/unacceptable," and the information that it provides stays local to provide quality control.
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From page 12...
... Academe's answer to such problems is to evaluate a person on the basis of a model of academic success that uses a set of subjective, qualitative metrics supported by quantitative data on output and subjective evaluation of the data. That combination of subjective evaluations and quantitative output metrics has evolved to support a model of academic success for faculty at different career stages and performance levels, from assistant to full professor.
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From page 13...
... 3 Although software algorithms and data-mining offer promising approaches to data collection, the committee believes that use of a specific set of keywords or field categories, identified by research investigators or program managers, could be improved sufficiently with relatively little effort to be useful for future data collection. However, the committee was surprised to learn that the current software system for project monitoring in NSF, called FastLane -- whereby investigators enter data into multiple fields to describe project participants, results, and outcomes, including papers published -- apparently could not be used to mine the data supplied by NNI-supported projects.
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From page 14...
... Essentially, the framework links NNI research products, including grants, papers, and patents; NNI people; NNI agencies and other corporate, government, and academic institutions; and short-term, intermediate-term, and long-term NNI outcomes. Many of the proposed metrics for assessing output are available to or are under development by various agencies and firms.
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From page 15...
... FIGURE 3.1 How inputs lead to outputs and, eventually, benefits: National Nanotechnology Initiativerelated research funded through federal agencies leads, in one mode of translation, to publications and patents, which in turn lead to societal benefits realized in the creation of new knowledge, products, companies, and jobs.
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Key Terms

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  • output data
  • national nanotechnology
  • nni participating
  • participating agencies

  • nni agencies
  • quantitative data
  • nni goals
  • academic success
  • machine learning

  • star metrics
  • software algorithms
  • relatively easily
  • quality improvement
  • require substantial

  • qualitative metrics
  • nni program
  • nni outcomes
  • quantitative output
  • nni research

  • nni metrics
  • project monitoring
  • render objective
  • directly accessing
  • research products

  • specific set
  • nsf star
  • requires careful
  • developing metrics
  • major federal


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