@InProceedings{karpovich:case-study,
  author = {John F. Karpovich and James C. French and Andrew S. Grimshaw},
  title = {High Performance Access to Radio Astronomy Data: A Case Study},
  booktitle = {Proceedings of the 7th International Working Conference on
  Scientific and Statistical Database Management},
  year = {1994},
  month = {September},
  note = {Also available as Univ. of Virginia TR CS-94-25},
  URL = {ftp://ftp.cs.virginia.edu/pub/techreports/CS-94-25.ps.Z},
  keywords = {scientific database, parallel I/O, pario-bib},
  comment = {Apparently a subset of karpovich:bottleneck. They store a sparse,
  multidimensional data set (radio astronomy data) as a set of tagged data
  values, ie, as a set of tuples, each with several keys and a data value. They
  use a PLOP format to partition each dimension into slices, so that each
  intersection of the slices forms a bucket. They decide on the splits based on
  a preliminary statistical survey of the data. Bucket overflow is handled by
  chaining. Then, they evaluate various kinds of queries, ie, multidimensional
  range queries, for their performance. In this workload queries (reads) are
  much more common than updates (writes).}
}