19CrAYS

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Based on non-IT, well-established, technical field and methods Has potential to solve intractable, complex challenges but also vulnerable to same forces that blocked prior ‘movements’ Science is structured, highly analytical with a culture of questioning assumptions and requiring objective proof Science is based on big data and handles it every day in every Science knows how to manage distributed sources, differing semantics, quality problems, linking business needs to operational data But, this is a culture shift from traditional data management New ideas: raw data, calibration transforms, uncertainty, continuous assessment and improvement, willingness to admit errors and immediately fix them 10
Example from DARPA Evidence Extraction & Link Discovery Today’s Situation: ~10k messages/day from multiple sources read by multiple analysts and analyzed in multiple manual non-integrated tools Similar to Social Network Analysis 11
Page 1 and 2: “She's tidied up and I can't find
Page 3 and 4: Robin Bloor, President and Chief An
Page 5 and 6: J. Kevin Moran Vice Admiral J. Kevi
Page 7: Phasic Systems Inc. www.phasicsyste
Page 14 and 15: “We spent years and many millions
Page 16 and 17: The US Navy struggled for years wit
Page 19: US Navy: VADM (Ret) Moran, executiv
Page 22 and 23: The data encompassed all HR data in
Page 24: There were many types of conflicts.
Page 28 and 29: Data Rationalization is the process
Page 30 and 31: Design Rationalization Issues • M
Page 32: Suffix in source A, prefix in B, ne
Page 36 and 37: Key terms used for decades but deba
Page 38 and 39: Multiple Rate/Rating entries that c
Page 40 and 41: Navy HPC HR-XML 40
Page 43: Logical Models derive directly from
Page 47 and 48: Different Meanings (Legal and Busin

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