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The unique characteristics of scientific data and queries cause traditional indexing techniques to perform poorly on scientific workloads, occupy excessive space, or both. Refinements of bitmap indexes have been proposed previously as a solution to this problem. In this article, we describe the difficulties we encountered in deploying bitmap indexes with scientific data and queries from two real-world domains. In particular, previously proposed methods of binning, encoding, and compressingdoi:10.1145/1272743.1272746 fatcat:umx62g5wxbgbrfe6k4zlfbhage