Provided data validation for the application:
Valid data types, Minimum and maximum ranges, Allowed values based on the business logic
There are already well established databases within the consortium, the London Pain Database (LPD) and QUAST (DFNS, Germany): The LPD is used for datamining of functional genomics
data to help identify individual genes and functional networks associated with chronic pain, QUAST on the other hand collects questionnaire
data, clinical and neurophysiological findings and calculates
valid clusters of phenotypes with different interaction patterns of sensory loss with and without different
types of peripheral and central hyperalgesia based on QST (quantitative sensory testing)
data.
This
type of
data is needed to accurately describe changes in diversity as students move between sectors because there is significant variation in student demographics at the school level that is often obscured when examining the issue at higher levels of aggregation (e.g. comparing charters as a group to surrounding school district or metropolitan area) and can complicate the drawing of
valid inferences about the relationship between public school choice and racial sorting.