Reproducibility

Reproducibility standard for self-storage research

How Storage Units Near Me documents sources, transformations, quality gates, uncertainty, code versions, content-addressed files, and preserved self-storage research releases.

Published and last reviewed July 11, 2026 by Storage Units Near Me.

Standard

Reproducibility means reconstructing a specific release

A result is reproducible only when another investigator can identify the same estimand, release, observations, transformations, exclusions, weights, and uncertainty procedure. A screenshot or a current facility-page price is not a substitute for a time-stamped observation because asking rents and availability change.

The current program publishes its design before publishing a number. No numeric series is available to reproduce yet. This standard describes the evidence package required when a qualified release exists.

Reproduction paths

Three supported levels of verification

Level 1

Audit the claim

Use the release table, coverage report, uncertainty interval, methods version, and cited public benchmark to verify what was actually claimed.

Level 2

Re-run the transformation

Use the published field definitions, exclusion rules, weighting specification, executable-version identifier, and aggregate inputs made available for that release.

Level 3

Reacquire source observations

Visit the documented public source classes independently, subject to current robots rules, source terms, and applicable rights. Source pages can change after observation.

Release contents

Minimum evidence package for every release

  • Canonical release URL, release identifier, version, timestamps, status, and file checksums.
  • A precise estimand and separate definitions for recurring rent, promotions, fees, and fixed-horizon effective rent.
  • Observation window, source classes, access method, geographic frame, and collection coverage.
  • Parser and normalization versions, unit matching keys, deduplication logic, and all exclusion reasons.
  • Facility, operator, state, and matched-panel counts plus missingness and concentration diagnostics.
  • Index formula, weight construction, composition adjustment, bootstrap design, confidence interval, and sensitivity results.
  • Suppressed estimates and failed publication gates, not only the geographies that passed.
  • Rights statement explaining which aggregate files can be shared and which source records cannot.

Audit trail

Deterministic processing and provenance

Each retained observation receives a stable identifier derived from normalized identifying fields and a record hash. Collection time is stored in UTC. The audit trail links a published aggregate back to its release, method version, parser version, source URL class, inclusion decision, and transformation history without implying that restricted raw third-party material can be redistributed.

Random procedures, including facility-clustered bootstrap intervals, must declare their pseudorandom seed and iteration count. Time zones, rounding rules, missing-value handling, software runtime, and executable version are fixed in the release manifest.

Versioning

Content-addressed releases and reproducible corrections

A published release is never silently overwritten. A correction produces a new version, new checksums, an explanation of the change, and a link to the prior release. Prior files remain identifiable and are marked as current, superseded, or withdrawn. Method changes that alter the estimand or historical comparability receive a new methodology version.

Read the version and revision policy, data dictionary, and publication gates for the operational definitions.

Constraints

Known limits of independent reproduction

  • Public web offers may expire or change after their recorded observation time.
  • Robots instructions, source terms, authentication requirements, and page structures can change.
  • Third-party raw records may be unavailable for redistribution even when aggregate results can be published.
  • An independently reacquired sample can test the method but may not recreate an earlier market snapshot exactly.
  • Passing a statistical gate supports publication; it does not eliminate sampling, measurement, or coverage error.