GEOM90007 Chap.13 Evaluation, Storytelling and Project Synthesis

Evaluation, Storytelling and Project Synthesis

Define visualisation evaluation

Evaluation, Storytelling and Project Synthesis frames a decision through visualisation evaluation, data story and design rationale.

The objective is to test the view with representative tasks, revise from observed failures and present the final claim with limitations, so the chapter should be read as a chain from problem definition to evidence, option comparison and accountable action.

Start with visualisation evaluation and name the decision owner, affected stakeholders and time horizon.

The same visualisation evaluation fact can matter differently across those positions, so the opening frame determines which evidence is relevant.

Use data story to explain how the present condition produces an opportunity, cost or risk. A strong data story mechanism states what changes, for whom and through which organisational, market or institutional process.

Apply design rationale when comparing options.

Keep the design rationale criteria distinct, test trade-offs and ask which assumption drives the recommendation. A score or matrix helps only when its criteria are justified by the case.

Trace data story

For the application — test the view with representative tasks, revise from observed failures and present the final claim with limitations — finish with an actor, action, rationale and review trigger.

This turns the design rationale analysis into a recommendation while keeping the decision open to new evidence.

Build a decision ledger. Separate the current condition, the stakeholder affected, the evidence supporting visualisation evaluation, the mechanism represented by data story and the criterion supplied by design rationale.

If a design rationale recommendation cannot point back to one of those entries, it is probably preference dressed as analysis rather than a consequence of the case.

Compare at least two feasible options against the same criteria. State who benefits under design rationale, who bears cost or risk, what capability implementation requires and what evidence would reveal failure.

This comparison is essential when students need to test the view with representative tasks, revise from observed failures and present the final claim with limitations, because an attractive option is not defensible until its trade-offs are visible.

Rehearse the GEOM90007 visualisation evaluation response as a short briefing: one sentence for the decision, two for the evidence and mechanism, one for the alternative and one for the qualified recommendation.

Then expand only the data story move that needs more support. This protects the argument structure under a strict word or time limit.

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

AskSia practice: apply 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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