Environment Systems and Decisions

, Volume 34, Issue 1, pp 49–59 | Cite as

Research prioritization using hypothesis maps



This work presents a method to aid in the prioritization of research within a scientific domain. The domain is encoded into a directed network in which nodes represent factors in the domain, and directed links between nodes represent known or hypothesized causal relationships between the factors. Each link is associated with a numeric weight that indicates the degree of understanding of that hypothesis. Increased understanding of hypotheses is represented by higher weights on links in the network. Research is prioritized by calculating optimal allocations of limited research resources across all links in the network that maximize the degree of overall knowledge of the research domain. We quantify the level of knowledge of individual nodes (factors) in the map by a network centrality measure that reflects in dependencies between knowledge level of nodes and the knowledge level of their parent nodes in the map. We analyzed a funded research proposal concerning the fate and transport of nanomaterials in the environment to illustrate the method.


Research prioritization Nanomaterial fate and transport Causal maps 



Support for this research was provided by the Department of Education under Grant Award P200A090055-11, the National Science Foundation and the Environmental Protection Agency NSF Cooperative Agreement EF-0830093, the Center for the Environmental Implications of NanoTechnology (CEINT), and Carnegie Mellon University. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the ED, NSF or the EPA. This work has not been subjected to EPA review, and no official endorsement should be inferred.

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Alan Masinter
    • 1
  • Mitchell Small
    • 1
  • Elizabeth Casman
    • 1
  1. 1.Department of Engineering and Public PolicyCarnegie Mellon UniversityPittsburghUSA

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