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For example, a color histogram contains a separate and precise count of pixels for each possible distinct color in the image. The only element of approximation might be in the number of bits used to represent different colors: fewer bits imply that several actual colors are represented by one, which will be associated with the number of pixels that have any of the colors that are grouped together. Even this kind of approximation is not common, however. In databases, histograms are used as a mechanism for full-fledged compression and approximation of data distributions.

334-350, 2001. [SCK02]A. Somani, D. Choy, and J. C. Kleewein, "Bringing Together Content and Data Management Systems: Challenges and Opportunities," [IBM02], 686696 (2002). P. A. Larson: Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases, ACM Computing Surveys 22 (3), pp. 183-236, 1990. J. Shekita, R. J. G. Lindsay, H. Pirahesh, B. Reinwald: Efficiently Publishing Relational Data as XML Documents. VLDB 2000:65-76 [SK+01 ]J. Shanmugasundaram, J. J. Shekita, C.

Litwin, L. Mark, N. Roussopoulos: Interoperability of Multiple Autonomous Da-tabases, ACM Computing Surveys 22 (3), pp. 267-293, 1990. [LR02]F. Leymann and D. Roller, "Using Flows in Information Integration," [IBM02], 732-742 (2002). [MKTZ99] Nelson Mendona Mattos, Jim Kleewein, Mary Tork Roth, Kathy Zeidenstein: From Object-Relational to Federated Databases. BTW 1999:185-209 [MM+01] Jim Melton, Jan-Eike Michels, Vanja Josifovski, Krishna G. Kulkami, Peter M. Schwarz, Kathy Zeidenstein: SQL and Management of External Data.

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