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The original data format was hard to access and navigate, so during the hackathon event in March the data was cleaned and reorganised in a more user-friendly way.
To obtain high-quality spectra, the data was cleaned and recalibrated to within 5 ppm using known subformula annotation [8], all other peaks without a valid subformula within 5 ppm of the recalibrated data were removed.
Before the data was cleaned and made accessible through DataViva, it was difficult to make comparisons across time (longitudinally) and between entities (geographies, industries, occupations, universities, etc).
Data was cleaned and checked for duplicates.
The data was cleaned, any discrepancies were checked against the original questionnaires and the accuracy of data entry was verified.
Data was cleaned by the second investigator before being locked, following which analysis was conducted by the lead investigator.
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Data were cleaned in Microsoft Excel (version 12.0; Microsoft Corporation, Redmond, WA, USA).
- Data cleaning programmes were written in STATA 10.0 (Stata Corp, and all data were cleaned using the programs.
Once the data is cleaned, it can be written to BigQuery, where it becomes immediately accessible.
This data are cleaned and maintained by the North Carolina Education Research Data Center (NCERDC) at Duke University.
All data were cleaned using the same procedures as outlined in experiment 1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com