This module will allow you to execute data quality rules upon your project data to check for discrepancies in your data. Listed below are some pre-defined data rules that you may utilize and run. You may also create your own rules or edit, delete, or reorder the rules you have already created. To find discrepancies for a given rule, simply click the Execute button next to it, or click the Execute All Rules button to fire all the rules at once. It will provide you with a total number of discrepancies found for each rule and will allow you to view the details of those discrepancies by clicking the View link next to each. Read more detailed instructions.

The pre-defined rules listed in red text cannot be modified, reordered, or removed. They are there if you wish to use them. You may also build and execute your own rules at the bottom of the table below. Rules can be set up using a literal logic format (e.g., [age] > 65) that will be evaluated as a boolean value (true or false) after an existing record's value for that field is substituted (e.g., assuming a record's value is 23 for 'age', 23 > 65 evaluates as false). The logic will be applied to all existing records in the project, and for any record for which the logic evaluates as true, it will return it as a discrepancy for that rule. Similar to branching logic and calculated fields, REDCap variable/field names may be utilized in the rule logic by placing the variable name inside square brackets [ ]. Also, for longitudinal projects, you may reference a field on one specific event by prepending the variable name in the logic with the unique event name in square brackets.

Checking the 'real-time execution' checkbox for any custom data quality rule will enable the rule to be executed invisibly on data entry forms whenever a user clicks the Save button to create or modify a record. After clicking Save, it will execute all relevant data quality rules invisibly (i.e. behind the scenes) and will display a warning pop-up message if any of the rules have been violated, in which it will display a list of the data quality rules that were violated and also display the fields involved with their data values. If no rules were violated, then it will save the record as usual and not display a pop-up message. Just like the results that are returned when executing rules on the Data Quality page itself, results displayed on data entry forms for 'real-time execution' can be excluded (if desired) so that they will not be displayed again if they are still in violation in the future.

Special functions may also be used within the logic as well (similar to functions in calculated fields), all of which are listed on the Help & FAQ page. If Data Access Groups exist for this project, then discrepancies will also be stratified according to their group (assuming the user viewing this page is not in a group). Any user within a Data Access Group will only be able to see the discrepancies for their own group. Also, if users do not have user privileges to view or edit data on specific data entry forms, then they will not be able to view data from those forms if displayed in any results on this page as a data quality discrepancy.

If a discrepancy has been found for a given rule, any individual discrepancy in the list of results may be excluded from those results in the future. Excluding a result merely prevents it from being included in the count of discrepancies if the rule is executed again in the future. Excluded results can be accessed again by clicking the 'view' link at the top of the results table for that rule, after which they can be un-excluded, if desired.

Upload or download Data Quality Rules

•  Upload Data Quality Rule (CSV)
•  Download Data Quality Rule (CSV)

You can only add new Data Quality Rules to the project by uploading a CSV file with a new Data Quality Rules configuration. The format for the CSV upload file can be acquired by exporting the CSV file of your existing Data Quality Rules.

Note: You cannot edit or delete existing Data Quality Rules using the CSV file but can only do that by clicking the edit/delete icon next to a given Rule.

Select your CSV file of Data Quality Rules to be added:

Displayed below is a preview of all new data quality rules you are about to commit. Please look over the additions, and then approve them by clicking the Upload button.

Note: These new data quality rules will be added to the existing set of data quality rules.

Data Quality Rules

Processing rule 0 of 0 Processing Complete! Execute rules: All All except A&B Clear

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	Rule #	Rule Name	Rule Logic  (Show discrepancy only if...)	Real-time execution?	Total Discrepancies	Delete rule?

pd-3	A	Blank values*	-		Execute
pd-6	B	Blank values* (required fields only)	-		Execute
pd-4	C	Field validation errors (incorrect data type)	-		Execute
pd-9	D	Field validation errors (out of range)	-		Execute
pd-5	E	Outliers for numerical fields (numbers, integers, sliders, calc fields)**	-		Execute
pd-7	F	Hidden fields that contain values***	-		Execute
pd-8	G	Multiple choice fields with invalid values	-		Execute
pd-10	H	Incorrect values for calculated fields	-		Execute
pd-11	I	Fields containing "missing data codes"	-		Execute
	Add	Enter descriptive name for new rule (e.g., Participants below age 18)	Enter logic for new rule (e.g., [age] < 18) How do I use special functions?	Execute in real time on data entry forms?

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