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  • Local data is put into a common microdata model at each site
  • At each site the common model undergoes a common process
  • In the common process first demographic events are organized into episodes whose data quality is measured
  • Likewise with epidemiological events
  • Finally, indicators (aggregates) are constructed
  • DDI 4 is used to chronicle these activities 
  • The common process is "blocked out" in line with the GSBPM/GLBPM. Together the blocks form a DataPipeline with preconditions and postcondtions
  • Preconditions and postconditions are microdata and aggregate data where the postcondition(s) of one block are the precondition(s) of another
  • Within each block a series of more granular data transformations are described

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