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Personal profile


Dr Sarah Goodwin is a Lecturer with the Immersive Analytics research group. Her work explores visual analytic solutions for complex, multi-dimensional and geospatial data sets and her research seeks to create novel geospatial visualisation techniques and improve user-centred visualisation design methodologies.  

Working closely with the Monash Energy Institute, Sarah is focusing on the exploration of novel visualisations for the energy sector at different levels from individual households to control room scenarios. She completed her PhD research at City, University of London, exploring residential consumer segmentation and smart home data analysis in the UK. This research exposed the effects of scale and geography on multivariate analysis through visualisation technqiues.

Sarah has an academic and professional background in geospatial analysis and information visualisation, having worked for over 15 years as a GIS technician, geo-data analyst, consultant and a researcher for some of the leading research centres for spatial analysis and visualisation around the world, including the giCentre at City, University of London, UK; the g2Lab at HafenCity University, Hamburg, Germany and the Geospatial Science Department at RMIT University, Melbourne.

Sarah's work on methodologies, focus on the use of creativity workshops in visualisation design studies with domain experts. Along with Energy Analysts, Sarah has worked closely with domain experts in different fields, including Epidemiologists and Spatial Modellers from Peter Doherty Institute, Melbourne University and Queensland University of Technology (2016-2017) to explore disease model and uncertainty visualisation for different user groups, as well as Constraint Programmers, within Monash's Optimisation Research Group (2015-2016), to explore visual profiling solutions for combinatorial optimisation problems.

Research interests

  • Infovis Design Studies and Methodologies
  • Creativity Techniques and Workshops
  • Geographical Information Visualisation
  • Spatial Temporal Visual Analytics
  • Human Computer Interaction
  • Multidimensional Data Visualisation
  • Geodemographics
  • Uncertainty Visualisation
  • Energy, Smart and Micro Grid Visualisation
  • Movement and Flow Data Visualisation
  • City and Urban Data Visualisation

Monash teaching commitment

Education/Academic qualification

Geographical Information Science, Doctor of Philosophy, City University London

Award Date: 14 Sep 2015

Geographical Information Systems, Master of Science, City University London

Award Date: 22 Nov 2007

Geography, Bachelor of Science (Honours), University of Manchester

Award Date: 1 Jul 2003

Research area keywords

  • Visualization
  • Analytics and big data
  • Energy
  • Computer Graphics
  • Smart grid
  • HCI
  • Smart Cities
  • Geostatistics
  • GIS
  • Spatial temporal statistics
  • Spatial cognition
  • Creativity

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Research Output

  • 6 Article
  • 5 Conference Paper

Context-Aware Smart Energy Recommender (CASER)

Sitoula, P., Rahayu, D., Haghighi, P. D., Goodwin, S. & Ling, C., Dec 2019, The 17th International Conference on Advances in Mobil Computing & Multimedia (MoMM2019): MoMM2019PROCEEDINGS. Delir Haghighi, P., Luiz Salvadori, I., Steinbauer, M., Khalil, I. & Anderst-Kotsis, G. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 13–19 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

What-why analysis of expert interviews: analysing geographically-embedded flow data

Yang, Y. & Goodwin, S., 1 Apr 2019, Proceedings - 2019 IEEE Pacific Visualization Symposium, PacificVis 2019: 23-26 April 2019 Bangkok, Thailand. Maciejewski, R., Seo, J. & Westermann, R. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 122-126 5 p. 8781587. (IEEE Pacific Visualization Symposium; vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

A framework for creative visualization-opportunities workshops

Kerzner, E., Goodwin, S., Dykes, J., Jones, S. & Meyer, M., Jan 2018, In : IEEE Transactions on Visualization and Computer Graphics. 25, 1, p. 748-758 11 p.

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Many-to-many geographically-embedded flow visualisation: An evaluation

Yang, Y., Dwyer, T. G., Goodwin, S. & Marriott, K., Jan 2017, In : IEEE Transactions on Visualization and Computer Graphics. 23, 1, p. 411-420 10 p., 7539669.

Research output: Contribution to journalArticleResearchpeer-review

29 Citations (Scopus)
8 Citations (Scopus)


IEEE InfoVis Best Paper Honorable Mention Award

Yalong Yang (Recipient), Dwyer, Tim (Recipient), Goodwin, Sarah (Recipient) & Marriott, Kimbal (Recipient), 2016

Prize: Prize (including medals and awards)