GEOM90007 Chap.13 Evaluation, Storytelling and Project Synthesis

Evaluation, Storytelling and Project Synthesis

Define visualisation evaluation

Evaluation, Storytelling and Project Synthesis connects visualisation evaluation, data story and design rationale along an information-visualisation pipeline: data type, visual encoding, perception, task fit and evaluation.

The practical aim is to test the view with representative tasks, revise from observed failures and present the final claim with limitations; the display is defensible only when each encoding choice can be traced back to the analytical question and the structure of the data.

Place visualisation evaluation at its correct stage: question, data specification, transformation, encoding, perception, tool or evaluation.

For visualisation evaluation, record the variables, measurement levels, granularity, missingness and comparison task wherever they apply before choosing or judging a chart.

Use data story to make the next transformation, encoding, layout, interaction or evaluation step explicit.

When data story involves marks and channels, state which values they represent and check whether scale, ordering, aggregation or filtering changes the apparent pattern.

Use design rationale to test perceptual and task fit.

In Evaluation, Storytelling and Project Synthesis, ask whether viewers can make the required comparison accurately, whether uncertainty and exceptions remain visible, and whether colour, position, motion or interaction creates an avoidable accessibility or interpretation cost.

Trace data story

For the application — test the view with representative tasks, revise from observed failures and present the final claim with limitations — compare at least one alternative encoding against the same data and task.

Retain the design only if the design rationale evaluation shows that it reveals the intended relationship without introducing a stronger distortion or hiding the evidence needed to challenge it.

Make a compact pipeline audit for visualisation evaluation: question or data field; transformation; mark and visual channel where applicable; intended task; evaluation evidence; and likely failure.

Locate data story and design rationale at their actual stages so a technically valid implementation is not mistaken for an effective display.

Test a changed data story view. Hold the data and question stable, replace the channel most closely tied to data story, and predict which comparison becomes easier or harder.

Evaluate the result with design rationale, including uncertainty, accessibility and the possibility that an apparent pattern is produced by scale, binning, projection or interaction state.

Critique Evaluation, Storytelling and Project Synthesis in task order: state the question around visualisation evaluation, classify the data, describe the role of data story, predict the perceptual judgement and report the design rationale evaluation evidence.

Revise the first stage where design rationale shows that the visual no longer supports the task instead of adding decoration to a structurally unsuitable chart.

Test with design rationale

A complete response should make the task visible before the detail: identify what must be decided, define the relevant terms, connect the evidence to data story, and use design rationale to test the result.

The final sentence about design rationale should answer the question actually asked rather than merely repeat the topic.

The controlling limit is specific: A persuasive narrative must not hide alternative explanations, uncertainty or inconvenient observations.

Keep that design rationale limit beside the worked example, because it separates a careful GEOM90007 answer from one that sounds confident but claims more than the task or evidence supports.

For revision, retrieve visualisation evaluation, data story and design rationale without notes, explain their relationship aloud, then complete a changed version of the application: test the view with representative tasks, revise from observed failures and present the final claim with limitations.

Record the first failed data story reasoning move and repair it before attempting another case.

What this chapter covers

• 01

  visualisation evaluation

• 02

  data story

• 03

  design rationale

• 04

  Applying visualisation evaluation

• 05

  Limits of data story and design rationale

Worked example: Evaluation, Storytelling and Project Synthesis

Key terms

visualisation evaluation

The systematic assessment of whether a visualisation supports intended tasks accurately, efficiently, accessibly and understandably. Use this definition when the task is to test the view with representative tasks, revise from observed failures and present the final claim with limitations.

data story

A structured sequence of evidence, annotation and narrative that guides an audience through a defensible analytical claim. Use this definition when the task is to test the view with representative tasks, revise from observed failures and present the final claim with limitations.

design rationale

An explicit explanation linking audience, task, data, encoding and interaction choices to evidence and trade-offs. Use this definition when the task is to test the view with representative tasks, revise from observed failures and present the final claim with limitations.

Evaluation, Storytelling and Project Synthesis FAQ

Assessment move

Reconstruct the relationship among visualisation evaluation, data story and design rationale; complete the chapter application without notes; then test the result against this limit: A persuasive narrative must not hide alternative explanations, uncertainty or inconvenient observations.

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