Welcome to MoSt
What is data storytelling, and why does it matter for mobility decisions?
If you're a mobility practitioner — transport planner, policy analyst, urbanist — you already have the data. The hard part is turning it into something a busy decision-maker can act on in five minutes. This is what MoSt teaches.
A data story is four things at once
Drop any one pillar and you lose the story. A spreadsheet on its own is just data. A chart without words is open to misreading. A wall of text without numbers is just opinion. And without interaction, the audience can't probe their own follow-up questions — they have to come back to you.
Data
The raw evidence — usually a few well-chosen numbers, not a spreadsheet dump.
Visualization
The chart, map, or table that makes the pattern readable in seconds.
Narration
The framing — what the audience should take from this and what to do next.
Interaction
The controls that let the audience answer their own follow-up questions.
Why this matters
Mobility decisions — bike lane funding, transit route changes, EV subsidy levels, congestion-charge zones — get made on calendar cycles that don't wait for the perfect dataset. If your data story doesn't help the decision-maker decide, the decision gets made anyway. Just without your evidence in the room.
The seven MoSt modules teach you to produce a data story that is decision-oriented (not just descriptive), audience-fit (not just technically correct), and quality-assessed (not just shipped).
How MoSt works
Seven short modules and one running example: a cycling-infrastructure decision facing a mid-sized German city. Each module starts with the concept (what it is, why it matters, where it fits), then a short practice task you can do in 5–10 minutes.
- Defining the Core QuestionTurn a vague topic into a decision-driving question.
- Selecting the Right DataPick the data that answers the question, not the data that exists.
- Visualizing for DecisionsChoose the chart that makes the answer obvious in 5 seconds.
- Adapting to Your AudienceMatch language and depth to who's actually reading.
- Building the Narrative ArcSetup → tension → resolution. Every story needs all three.
- Adding InteractionLet the audience explore your chart's follow-up questions themselves.
- IntegrationAssemble everything and self-assess against the MobiDaS quality requirements.
About the research base
MoSt operationalizes findings from two mobility-data research projects at TU Ilmenau:
- MobiDaS (Mobility Data Stories) — defines the seven quality requirements (R1–R7) that you'll self-assess your story against in Module 7.
- MODAS — provides complementary findings on decision-oriented mobility communication. External link to MODAS
The instructional design — concept-first, explain-then-practice, persistent progress — draws on Cognitive Load Theory (Sweller) and Situated Learning.