Mundane Observations

Why the network view matters

Bikes do not live in isolation. People choose routes and parking based on safety, lighting, time pressure, and where friends tend to leave their bikes. A network view helps reveal these relationships as patterns rather than one off anecdotes.

• Nodes represent bike parking spots or observed stop points.
• Edges represent observed movement or proximity that encourages movement.
• Communities reveal pockets of activity that feel coherent to riders.

Data vs information

Advanced scripting is useful for showing patterns fast. It is not the whole story. Computed outputs can be fragile when the inputs are noisy or biased. Data are raw measurements. Information is what you get after context, checks, and interpretation. The assignment here pushed me to localize data by going outside, logging conditions, and cross checking with simple models.

• Collect locally. Note time of day, weather, signage, human behavior.
• Compute carefully. Use models to suggest questions, not final answers.
• Translate to information. Tie results to design and policy decisions.

As a CS student, this is the habit I want to practice. Script well, but verify on the ground. Build tools that respect the difference between data and information.

Network structure

To make sense of how people actually park and move with bikes, I mapped observed points as nodes and linked places where movement was common. Clusters formed near safer, brighter, and busier blocks while other spaces felt left out. This helped surface where a simple design change like lighting or signage could shift behavior.