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A General Guide for Harmonizing Data

Author

Listed:
  • Cheng, Cindy

    (Technical University of Munich)

  • Messerschmidt, Luca
  • Bravo, Isaac
  • Waldbauer, Marco
  • Bhavikatti, Rohan
  • Schenk, Caress
  • Grujic, Vanja
  • Model, Tim
  • Kubinec, Robert

    (New York University Abu Dhabi)

  • Barceló, Joan

    (New York University - Abu Dhabi)

Abstract

Data harmonization is an important method for generating the requisite datasets to support big data analyses. To date however, articles about data harmonization are field-specific and highly technical, mak- ing it difficult for researchers to derive general principles for how to engage in and contextualize data harmonization efforts. This commentary provides general guidance and criteria for researchers who are considering undertaking such efforts or seek to evaluate the quality of existing ones. We derive these guidelines from the extant literature and our own experience in harmonizing data for the emergent and important new field of COVID-19 public health and safety measures (PHSM).

Suggested Citation

  • Cheng, Cindy & Messerschmidt, Luca & Bravo, Isaac & Waldbauer, Marco & Bhavikatti, Rohan & Schenk, Caress & Grujic, Vanja & Model, Tim & Kubinec, Robert & Barceló, Joan, 2023. "A General Guide for Harmonizing Data," OSF Preprints baf2j, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:baf2j
    DOI: 10.31219/osf.io/baf2j
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    References listed on IDEAS

    as
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