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Handbook / labs

labs

Lab: Data Placement

Goal: choose authoritative, working, temporary, and final locations for a research project before large files are created.

Goal: choose authoritative, working, temporary, and final locations for a research project before large files are created.

Prerequisites: the project's supervisor/information owner and intended compute environment are known.

Execution context: planning exercise. Do not move or delete real data while completing it.

Scenario Inventory#

For each artifact, choose a location and justify it:

Artifact Questions to answer
Python source and tests Who reviews it? Does it belong in GitHub?
Raw dataset Is it published, internal, confidential, or restricted?
Processed training data Can it be recreated? Does computation need fast I/O?
Model checkpoints Which are temporary and which support a result?
Logs and metrics How long are they needed and who reads them?
Final figures/tables What must be preserved for a thesis/publication?
Software tokens Which credential store handles them?
Temporary job files What happens when the job or scratch lifetime ends?

Complete The Location Map#

Information owner:
Classification:
Source code:
Authoritative raw data:
Euler working data:
Temporary data:
Checkpoints:
Logs and metrics:
Final results:
Long-term handover/archive:
Backup and restore owner:
Retention/cleanup date:

Use system choices, the NAS guide, and Euler storage.

Add Repository Boundaries#

Review .gitignore. It should normally exclude local secrets, data, checkpoints, caches, environments, and generated output while keeping source, tests, configuration examples, and documentation visible.

Do not add a broad pattern such as *.csv if small source-controlled test fixtures legitimately use that extension. Prefer project directories such as data/local/, checkpoints/, or results/generated/.

Verification#

Ask the supervisor/information owner to confirm:

  • the classification and approved services;
  • the authoritative raw-data copy;
  • which working locations are backed up;
  • which temporary locations may be purged;
  • the required final handover artifacts.

Common Failures And Safe Recovery#

  • Large file already committed: stop pushing, notify the repository owner, and move it to approved storage before coordinated history cleanup.
  • Only copy is in scratch or Blade D:: copy and verify it in approved durable storage immediately.
  • Collaborators need write access: use the approved group/ACL procedure; do not make the directory world-writable.

Understand Before Accepting AI Output#

  • The agent did not infer data classification or ownership.
  • I verified storage behavior from current policy/source documentation.
  • I know which files are authoritative and which are disposable.
  • No secret value appears in the location map.

Evidence#

Submit the approved map, a safe .gitignore diff when relevant, and one sentence explaining how final results can be restored or reproduced.

Ask For Help When#

Classification, licensing, consent, ownership, approved cloud use, or retention is unclear.