Science as Knowledge, Practice, and Map Making: The Challenge of Defining Metrics for Evaluating and Improving DOE-Funded Basic Experimental Science

Industrial R&D laboratories have been surprisingly successful in developing performance objectives and metrics that convincingly show that planning, management, and improvement techniques can be value-added to the actual output of R&D organizations. In this paper, I will discuss the more difficult case of developing analogous constructs for DOE-funded non-nuclear, non-weapons basic research, or as I will refer to it - basic experimental science. Unlike most industrial R&D or the bulk of applied science performed at the National Renewable Energy Laboratory (NREL), the purpose of basic experimental science is producing new knowledge (usually published in professional journals) that has no immediate application to the first link (the R) of a planned R&D chain. Consequently, performance objectives and metrics are far more difficult to define. My claim is that if one can successfully define metrics for evaluating and improving DOE-funded basic experimental science (which is the most difficult case), then defining such constructs for DOE-funded applied science should be much less problematic. With the publication of the DOE Standard - Implementation Guide for Quality Assurance Programs for Basic and Applied Research (DOE-ER-STD-6001-92) and the development of a conceptual framework for integrating all the DOE orders, we need to move aggressively toward the threefold next phase: (1) focusing the management elements found in DOE-ER-STD-6001-92 on the main output of national laboratories - the experimental science itself; (2) developing clearer definitions of basic experimental science as practice not just knowledge; and (3) understanding the relationship between the metrics that scientists use for evaluating the performance of DOE-funded basic experimental science, the management elements of DOE-ER-STD-6001-92, and the notion of continuous improvement