BSB_Sim/docs/data_collection_protocol.md

Data collection protocol (draft)

1. Obtain institutional ethics/privacy review where required and use the completed participant information and consent form.
2. Assign a random participant code. Do not put names or contact details in filenames or the signature database.
3. Record device type, sampling setup, session date/code, and whether pressure or contact-area data are available in a separate access-controlled study log. Do not write unnecessary personal information into the signature CSV.
4. Collect several genuine samples per participant, with a short pause between attempts. Mark examples explicitly as genuine.
5. If studying skilled or random forgeries, collect them only under the approved protocol, keep the target identity in user_id, and label their type in the label column. Avoid coercive or deceptive collection.
6. Use the common CSV columns user_id,label,t,x,y,p,area,pen_down. Each file should contain one signature sequence; timestamp units must be consistent within a dataset. Optional p and area fields should be blank or omitted when unsupported.
7. Store raw files in data/raw/own/, restrict access, and keep them out of version control. Store encryption keys separately from the database.
8. Keep participant-level identities together when making train/test splits. Tune thresholds on a development set and report the final test set only once. Report the number of participants, genuine samples, and each forgery type alongside FAR, FRR, and EER.