Structuring complex results using network maps and hierarchical charts

Results from quantitative exposure and life cycle assessments are often complex, rendering their interpretation and communication to non experts difficult. However, such data can be disaggregated and structured using visualization techniques to increase their interpretability. We present a simple, interactive tool that allows disaggregating data according to user preferences and flexibly visualizing these data in quantitative network maps and hierarchical column charts. We show in a case study on a chemical in flooring that our tool can help users to rapidly identify exposure hot-spots and trace back related pathways. Our tool can be applied to various types of results from chemical substitution, life cycle impact assessment, and high-throughput risk screening to improve decision support by better results interpretation and communication. (C) 2018 The Authors. Published by Elsevier B.V.