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Data-intensive software is increasingly prominent in today’s world, where the collection, processing, and dissemination of ever-larger volumes of data has become a driving force behind innovation in the early twenty-first century. The trend towards massive data manipulation is broad-based, and case studies can be examined in domains from politics, to intelligence gathering, to scientific and medical research. The scientific domain in particular provides a rich array of case studies that offer ready insight into many of the modern software engineering, and software architecture challenges associated with data-intensive systems.
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We use “archive” and “repository” interchangeably throughout the chapter.
Metadata refers to “data about data.” As an example, consider a book data file, and its associated metadata, “author,” with potentially many values.
In the world of science data systems and data-intensive systems in general, “products” refer to the output data file(s) along with their metadata.
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- Architecting Data-Intensive Software Systems
Chris A. Mattmann
Daniel J. Crichton
Andrew F. Hart
J. Steven Hughes
Thomas H. Painter
- Springer New York
- Chapter 2
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