Before the Chart, Before the Choice: How Framing Shapes Visualisation and Decision-Making

Visualisations are never done in a vacuum. Every map, chart or dashboard is a bridge from what we know to the incremental insights that aim to enable better decisions. In this analytical process, key factors determine effectiveness: the conceptual framing that influences definitions, measurements, and thresholds, and the choices of scale and aggregation. We draw from our practice and reflect on how such factors shape policy debates and public understanding. A city can appear deindustrialised or diversifying, informal or a start-up hub, unequal or resilient, depending on certain choices made in the data representation.

Prior knowledge of the reality being captured by data provides a conceptual frame, with transformative influence on what is visible and what is not. What counts as a city, affordable house, or most frequent commute choice? Nobody announces these decisions. They get made in government meetings and policy documents, often unnoticed by masses. What's left behind is a number: a threshold, a category, a line on a map, that starts to feel like "the fact" when visualised. This session is about what happens when you move that line and what it feels like to be the person who drew it.

Using cases from projects I have worked on with my team at the lab:

1. Urban Definition: India defines a place as "urban" based on how many men have left farming, not women. So, in a village where women are in the service sector but men migrated? Stays rural. No roads, no schemes. The work is real. The definition is blind to it.

2. Mobility Pattern: City transport surveys show two-wheelers dominate in aggregate. But that's how men move. Women walk and take buses for safety, cost, and access. They're invisible in the data that shapes transit policy.

3. Housing Affordability: Finance rules suggest a two-income Bengaluru family can afford a home in a certain price range. In reality? Those homes don't exist near jobs or schools. The rule exists; the market doesn't support it.

These aren't coincidental mismatches but choices made by real decision makers that become invisible rules of who gets counted and who doesn't.

The interactive exhibit doesn't explain this but makes one feel it. Three modules, each built as a choice situation in the exhibit. In the first, you play a planning official setting thresholds for what makes a settlement urban and you commit. Then the map loads, showing what India looks like under your definition, compared to versions different choices would have produced. In the second, you toggle between mobility proxies and occupation categories, watching who gets counted as economically active shift in real time. In the third, you build affordable housing band using Karnataka's per capita income data. Then hit reveal and see what's actually being built in Bengaluru, and where.

The point is in the sequence: you choose before seeing, commit before understanding what's at stake.

The imagined audience for this session: Urban planners, policymakers, data practitioners, researchers, journalists, and anyone curious about how invisible technical choices shape their cities, transport, and housing options.