Mission Communications

Mission Goal

Turn mission data into a story people can understand: choose one dataset and explain what it means, why it matters, and what you learned—without distorting the truth.

Why This Matters

Data doesn’t speak by itself. In real missions, teams must translate telemetry into decisions, updates, and learning. If you can’t explain what the data means, you can’t improve the mission.

Inputs From Other Teams

• Instrumentation: a real sample dataset (CSV/JSON/log), plus units and sampling interval.
• Command & Control: the mission timeline (when key events occurred).
• Mission Design: what you expected to happen (hypothesis or predicted pattern).

What You Must Produce (Deliverables)

1. One chart or table (simple, readable, correctly labelled units).
2. One “story spine”: Setup → Signal → Surprise → So What → Next Step.
3. One plain-English interpretation (150–220 words) grounded in the evidence.
4. One caution statement (what the data does not prove).

Templates

Short tweet template (≤ 280 chars)

Our mission data shows [signal]. We measured [data + unit] every [interval]. Biggest surprise: [surprise]. Next we’ll [next test]. (Chart in our log!)

Newsletter paragraph template (3–5 sentences)

This week we analysed [dataset name] from [mission phase]. The main pattern was [signal + direction], which suggests [meaning]. We were surprised by [surprise], so our next step is [next test/change]. Important: this data does not prove [overclaim].

Assembly slide outline (5 slides max)

1. What data did we collect? (units + interval)
2. What does it look like? (one chart)
3. What does it mean? (interpretation)
4. What surprised us? (one insight)
5. What will we change next? (one action)

Step-by-Step

1. Pick one dataset (e.g., temperature, acceleration, signal strength).
2. Confirm basics: units, interval, sensor location, mission phase.
3. Make one chart with a title, labelled axes, and units (no fancy effects needed).
4. Write the story spine: Setup → Signal → Surprise → So What → Next Step.
5. Add a caution: name at least one limitation (noise, drift, missing time sync).
6. Peer review: can another student explain the pattern in one sentence?

Success Criteria

• Your chart/table is readable, labelled, and honest (units and interval included).
• Your interpretation refers directly to the evidence (“we saw X at time Y”).
• You state a limitation and avoid overclaiming.
• You propose one practical next step to improve the mission or data quality.

Evidence Checklist

• ✅ One chart or table with units
• ✅ Story spine (5 parts)
• ✅ 150–220 word interpretation
• ✅ One caution statement
• ✅ One next-step action

Ethics (Truthfulness, Privacy)

• Truthfulness: never “smooth” away inconvenient data without saying so.
• Privacy: remove personal identifiers and sensitive locations from logs before publishing.
• Clarity: distinguish between measurement and inference.

Common Failure Modes

• Charts with no units or unclear axes.
• Storytelling that ignores contradictory data.
• “Correlation = causation” claims without proof.
• Using averages only (hiding spikes that matter).

Stretch Goals

• Compare two runs (before/after a change) and explain the difference.
• Add a “confidence” rating (high/medium/low) with reasons.
• Create a tiny “mission logbook” page with chart + story + next step.