Ghost Data

Ghost data is the data that is not there (invisible), and there are many types.
Data type
In physics (quantum field theory), a ghost, ghost field, or gauge ghost is an unphysical state in a gauge theory. Ghosts are necessary to keep gauge invariance in theories where the local fields exceed a number of physical degrees of freedom. Analogously, how to (gauge) deal with ghost data (invisible, not visualized or not recognized) is still challenging data scientists. The common example of ghost data is virtual, sparse, missing, or pretend data. One example is the evidence gap in global health research and related research on the issue of counterfeit drugs. Global health research and policies have warned about the increasing threat of counterfeit and inferior drugs .
In addition to missing data, ghost data also includes other invisible data. These data may be the one that some people can perceive but others cannot, such as survival as a digital ghost, ghost images , digital museum and archive .
Data processing
Replicated along the external boundaries, ghost data lets data-parallel visualization algorithms operate correctly and without further communication. A classic example of this is isosurface extraction (also called isocontouring). Ghost data lets the interpolation be consistent on both sides of the boundary, thereby ensuring a crack-free surface. Ghost data's uses aren't limited to isocontouring. Ghost data is also needed for gradient calculations, reconstructing material interfaces in Eulerian hydrodynamics simulations, smoothing out scalars for volume renderings with pseudocolors, and many other computations involving
neighbor data. The cost of storing ghost data is felt by all parties: during write (for the simulation code) and read (for the simulation code or the visualization code), and especially in the footprint on the disk. One layer of ghost data suffices for all subsequent visualization and analysis.

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