Chapter 10 attempts to bring several of the strands of the report together into a proposal for a taxonomy of some of the major algorithmic problems arising in massive data analysis. The committee hopes that the ideas in this section will serve to organize the research landscape and also provide a point of departure for the design of “middleware” that links high-level inferential goals to the algorithms and hardware needed to achieve those goals.

In accordance with the study’s statement of task, Chapters 2 through 10 identify gaps in current theory and practice, and Chapters 3 through 10 propose a number of elements of a research agenda. Finally, Chapter 11 presents the committee’s primary conclusions.

REFERENCES

Halevy, A., P. Norvig, and F. Pereira. 2009. The unreasonable effectiveness of data. IEEE Intelligent Systems 2:8-12.

NRC (National Research Council). 1996. Massive Data Sets: Proceedings of a Workshop. National Academy Press, Washington, D.C.



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