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Personal profile

Biography

Dr Sarah Goodwin is a Lecturer with the Immersive Analytics Lab (IALab).  She is interested in exploring creative visual analytic solutions for complex, multi-dimensional and geospatial data sets. Her research is particularly focused on user-centred visualisation design methodologies and novel geospatial visualisation techniques. Sarah recieved her PhD in 2015 from City University of London. Her PhD research focused on visualisation for energy analysts and future smart home analytics. Her interest in the energy domain has continued and she is now working with Monash's Energy Material and Systems Institute (MEMSI) to explore visualisation opportunities for the energy sector.

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

Sarah's research has explored the use of visualisation to expose the effects of scale and local geographical variation in multivariate analysis. Most recently her work has focused 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

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 2012 2018

  • 6 Article
  • 2 Conference Paper

A Framework for Creative Visualization-Opportunities Workshops

Kerzner, E., Goodwin, S., Dykes, J., Jones, S. & Meyer, M., 19 Aug 2018, (Accepted/In press) In : IEEE Transactions on Visualization and Computer Graphics. 25, 1, 11 p.

Research output: Contribution to journalArticleResearchpeer-review

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

Visual encoding of dissimilarity data via topology-preserving map deformation

Bouts, Q. W., Dwyer, T., Dykes, J., Speckmann, B., Goodwin, S., Riche, N. H., Carpendale, S. & Liebman, A., 1 Sep 2016, In : IEEE Transactions on Visualization and Computer Graphics. 22, 9, p. 2200-2213 14 p., 7328332.

Research output: Contribution to journalArticleResearchpeer-review

Visualizing Multiple Variables Across Scale and Geography

Goodwin, S., Dykes, J., Slingsby, A. & Turkay, C., 31 Jan 2016, In : IEEE Transactions on Visualization and Computer Graphics. 22, 1, p. 599-608 10 p., 7192660.

Research output: Contribution to journalArticleResearchpeer-review