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A General Primer for Data Harmonization

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 Primer for Data Harmonization," OSF Preprints baf2j_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:baf2j_v1
    DOI: 10.31219/osf.io/baf2j_v1
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