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VTValiTracAI

Checklist · CHK-05

Mapping Data Quality Checklist

Units, timestamps, gaps, duplicates, flatlines, jumps, identifiers and metadata.

Purpose

A data-quality checklist applied to logger datasets before analysis in a mapping or monitoring study, so that unit ambiguity, timestamp problems, gaps, duplicates, flatlines, jumps and metadata errors are found and documented before statistics are calculated. It mirrors the quality checks in the ValiTrac mapping workflow.

What it covers

  • Identification and metadata
  • Timestamps
  • Completeness
  • Plausibility
  • Dataset assembly
  • Summary, actions and sign-off

How to complete it

  1. 1.Apply to every sensor file individually and then to the merged dataset.
  2. 2.Record the finding and the resolution for each item (corrected at source, excluded with justification, accepted with limitation).
  3. 3.Never alter raw files; document any cleaning as a separate processed dataset with a record of the changes.

Before you use it

  • Replace every square-bracket token, starting with [LABORATORY NAME], [ADDRESS] and [EFFECTIVE DATE]. The full token list is in GD-01 Read Me First.
  • Have the content technically reviewed against how your laboratory actually works, then approved by the responsible manager before it becomes a controlled document.
  • Update the Word fields after editing so the table of contents and page numbers are correct: select all, then press F9.
  • Record the document in your own document register and set its review date.

Related documents

This is an original template published by ValiTrac. It does not reproduce the text of ISO/IEC 17025 or of any accreditation body publication, and it does not by itself confer or guarantee accreditation. Customise, review and approve it before use.