EconPapers    
Economics at your fingertips  
 

A General Guide for Harmonizing Data

Cindy Cheng, Luca Messerschmidt, Isaac Bravo, Marco Waldbauer, Rohan Bhavikatti, Caress Schenk, Vanja Grujic, Tim Model, Robert Kubinec and Joan Barceló
Additional contact information
Cindy Cheng: Technical University of Munich

No baf2j, OSF Preprints from Center for Open Science

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).

Date: 2023-11-09
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://osf.io/download/654d3964c9ac3f085d2f7953/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:baf2j

DOI: 10.31219/osf.io/baf2j

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().

 
Page updated 2025-03-22
Handle: RePEc:osf:osfxxx:baf2j