spatial-data-integration

Materials for working group on integrating heterogeneous data across scales

Thu Morning Discussion - General Problem Outline:

• have data + meta-data about some quantity
  • sometimes direct measurement
  • sometimes indirect measurement + transformation / interpretation process
• generally has mixed regions of overlap
• data have different "resolution" + "uncertainty"
  • conventional spatial / temporal issues
  • also precision generally: variation, bias, complex distribution of results relative "finer" scale measurement
  • sometimes well characterized in meta data, sometimes no provenance
• want to create reference mesh from this data
  • automatable process
  • propagated uncertainty
  • synthesized finer scale where none available
• using mesh:
  • forecasting
  • back-propagation of subsequent modeling reults to re-evaluate data
  • identify experiments / observations with maximal returns

Thu Afternoon Discussion - Minimal Version of the Problem

• 1D "space": all measures are located on a line + no time
• observations with x + measurement source, and particular z measurements
• measurement sources have distribution shapes / lineal area descriptions (possibly as functions of x / z?)
• consumer supplies grid + desired sample size + whole grid model prior
• process returns meshes of particular z values