EAN: 9783031271793

INTEGRITY CONSTRAINTS ON RICH DATA TYPES - SHAO...

This book examines the recent trend of extending data dependencies to adapt to rich data types
in order to address variety and veracity issues in big data. Readers will be guided through the
full range of rich data types where data dependencies have been successfully applied  including
categorical data with equality relationships  heterogeneous data with similarity relationships
numerical data with order relationships  sequential data with timestamps  and graph data with
complicated structures. The text will also discuss interesting constraints on ordering or
similarity relationships contained in novel classes of data dependencies in addition to those
in equality relationships  e.g.  considered in functional dependencies (FDs). In addition to
exploring the concepts of these data dependency notations  the book investigates the extension
relationships between data dependencies  such as conditional functional dependencies (CFDs)
that extend conventional functional dependencies (FDs). This forms in the book a family tree of
extensions  mostly rooted in FDs  that help illuminate the expressive power of various data
dependencies. Moreover  the book points to work on the discovery of dependencies from data 
since data dependencies are often unlikely to be manually specified in a traditional way  given
the huge volume and high variety in big data. It further outlines the applications of the
extended data dependencies  in particular in data quality practice. Altogether  this book
provides a comprehensive guide for readers to select proper data dependencies for their
applications that have sufficient expressive power and reasonable discovery cost. Finally  the
book concludes with several directions of future studies on emerging data.

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