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Assessing Public Metabolomics Metadata, Towards Improving Quality.

João D Ferreira1, Bruno Inácio1, Reza M Salek1

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|December 14, 2017
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Summary

Public resources require quality metadata for discoverability. Automatic quality measures can encourage data owners to improve metadata, enhancing data sharing and scientific accountability.

Keywords:
coveragedata sharingmetadata qualityontologiesspecificity

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Area of Science:

  • Biomedical Informatics
  • Data Science
  • Metabolomics

Background:

  • Public resources require robust metadata for discoverability, reproducibility, and interoperability.
  • Existing data-sharing policies for metadata annotation are often overlooked by data owners.

Purpose of the Study:

  • To analyze automatic measures of metadata quality.
  • To propose the application of these measures to encourage improved metadata annotation.
  • To enhance data sharing and scientific accountability.

Main Methods:

  • Analysis of automatic metadata quality measures.
  • Application of measures within the MetaboLights metabolomics data repository.
  • Manual validation and temporal analysis of metadata quality measures.

Main Results:

  • Automatic measures can effectively assess metadata quality.
  • The proposed measures correlate with manual quality assessments.
  • Metadata quality can be tracked and improved over time.

Conclusions:

  • Automatic metadata quality assessment is a viable approach.
  • Implementing these measures can incentivize data owners to enhance metadata.
  • This contributes to higher quality data, better data sharing, and increased scientific accountability.