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Procedures for data validation and cut-off points (in counts/min) to determine the time spent in sedentary, light, moderate, and vigorous activities were based on a previous publication [ 53].
We then proposed a stepwise procedure for data analysis and variant validation.
Data management protocol has been developed for this study, including guidelines and procedures for data collection, validation, entry, storage, analysis and dissemination.
Since 2000, much of the data generated each year is in electronic form and the procedures for data entry and validation have changed.
Therefore, some limitations are present in our approach as regards, for instance, either automatic procedures for data encription and validation or database federation.
In order to ensure data quality and to select reads for subsequent data validation procedures we used several filtering steps.
For starters, when creating or working on a spreadsheet, make a habit of using data validation functionality.
Herein we discuss a procedure seeking for further validation of these networks.
In order to ensure a high level of data quality, complex data validation procedures are installed.
After careful data validation procedures, we characterized biodiversity gaps, a necessary first step before trying to bridge these gaps31.
See Data Validation for more information.
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