Structuring Complex Results using Network Maps and Hierarchical Charts

Chloe Annelies Lanters; Peter Fantke

doi:10.1016/j.procir.2017.11.147

Structuring Complex Results using Network Maps and Hierarchical Charts

Chloe Annelies Lanters
, Peter Fantke^*

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Research › peer-review

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Abstract

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.

Original language	English
Journal	Procedia CIRP
Volume	69
Pages (from-to)	441-446
ISSN	2212-8271
DOIs	https://doi.org/10.1016/j.procir.2017.11.147
Publication status	Published - 2018
Event	25th CIRP Life Cycle Engineering (LCE) Conference - Copenhagen, Denmark Duration: 30 Apr 2018 → 2 May 2018 Conference number: 25 http://www.lce2018.dk

Conference

Conference	25th CIRP Life Cycle Engineering (LCE) Conference
Number	25
Country/Territory	Denmark
City	Copenhagen
Period	30/04/2018 → 02/05/2018
Internet address	http://www.lce2018.dk

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1016/j.procir.2017.11.147

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@inproceedings{d6ee31a4e2cb4645aa932ad8857ee999,

title = "Structuring Complex Results using Network Maps and Hierarchical Charts",

abstract = "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.",

author = "Lanters, \{Chloe Annelies\} and Peter Fantke",

year = "2018",

doi = "10.1016/j.procir.2017.11.147",

language = "English",

volume = "69",

pages = "441--446",

journal = "Procedia CIRP",

issn = "2212-8271",

publisher = "Elsevier",

note = "25th CIRP Life Cycle Engineering (LCE) Conference ; Conference date: 30-04-2018 Through 02-05-2018",

url = "http://www.lce2018.dk",

}

TY - GEN

T1 - Structuring Complex Results using Network Maps and Hierarchical Charts

AU - Lanters, Chloe Annelies

AU - Fantke, Peter

N1 - Conference code: 25

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

U2 - 10.1016/j.procir.2017.11.147

DO - 10.1016/j.procir.2017.11.147

M3 - Conference article

SN - 2212-8271

VL - 69

SP - 441

EP - 446

JO - Procedia CIRP

JF - Procedia CIRP

T2 - 25th CIRP Life Cycle Engineering (LCE) Conference

Y2 - 30 April 2018 through 2 May 2018

ER -

Structuring Complex Results using Network Maps and Hierarchical Charts

Abstract

Conference

UN SDGs

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