Data Quality Toolkit 2024

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Revision as of 15:21, 14 February 2024 by Kds15e (talk | contribs) (Add outline of data quality toolkit formatting, with examples)
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Overview

This page was created to aggregate common data quality issues and potential solutions to those issues in collection management systems and CMS-agnostic tools. Data quality issues are grouped into data categories, and tutorials are provided for (1) identifying and (2) fixing the issues.

This page was inspired by Bob Mesibov's Data Cleaner's Cookbook.

Catalog Numbers and Other Identifiers

Duplicate Catalog Numbers

Problem: The same catalog number is used multiple times within your dataset. (This problem may or may not be intentional, depending on your collection's policies. It is generally best to not duplicate catalog numbers, when possible).

How to FIND this Problem in Your Dataset:

  • Arctos:
  • Excel:
  • OpenRefine
  • Specify:
  • Symbiota:
  • TaxonWorks:

How to FIX this Problem in your Dataset:

  • Arctos:
  • Excel:
  • OpenRefine
  • Specify:
  • Symbiota:
  • TaxonWorks:

Dates

Identified Date Earlier than Collected Date

Problem: The date the specimen was identified (dateIdentified field) is earlier than the date the specimen was collected (eventDate).

How to FIND this Problem in Your Dataset:

  • Arctos:
  • Excel:
  • OpenRefine
  • Specify:
  • Symbiota:
  • TaxonWorks:

How to FIX this Problem in your Dataset:

  • Arctos:
  • Excel:
  • OpenRefine
  • Specify:
  • Symbiota:
  • TaxonWorks:

Geography

Misspelled Geographic Unit Names

Problem: The geographic units (e.g., country, state, county) are misspelled, resulting in poor matching of geographic unit names to existing geographic lists.

How to FIND this Problem in Your Dataset:

How to FIX this Problem in your Dataset:

Taxonomy

Misspelled Taxonomic Names

Problem: Scientific names are misspelled, resulting in poor matching of taxonomic names to taxonomic databases.

How to FIND this Problem in Your Dataset:

How to FIX this Problem in your Dataset: