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• Analytics to be used: A list of the proposed analytics that will form the
basis of the output of the analysis work. Here again, this is an initial list
of analytics to be used and will be supplemented by additional analytics
that will be discovered during the work. The analytics can be supported
by several different analytics techniques, including the following:

• Graph analytics: Initial relationships between data elements and peo-
ple; can also show the strength of the relationship based on data at-
tributes.
• Text analytics: These can uncover underlying sentiment within so-
cial media, and compliance are infractions and communications and
documents of all kinds. They can also be word cloud visualizations as
used in this book.
• Path pattern and time series analytics: These provide insight on inter-
action patterns between people, products, or data elements.
• Structured query language (SQL): This is a standardized query lan-
guage for requesting information from a database. It provides flexible
ways to manipulate data and to make queries from a big data set using
the language of business tools.
• Statistical modeling: This includes statistical modeling techniques
such as linear least squares regression, nonlinear least squares regres-
sion, weighted least squares regression, and locally weighted scatter-
plot smoother (curve fitting).
• Machine learning: Techniques to sift through data with minimal hu-
man input to gain new insights previously undetected. This can form
the basis for decision support and automation.

This format is an approach adopted by a major big data and analytics
practitioners and solution providers [2] with many years of experience in de-
veloping and implementing use case descriptions associated with big data and
analytics projects.
The purpose of Appendix A is twofold: to explain a few transportation use
cases and to illustrate how the use cases are put together in practice. The inten-
tion is to provide practical examples of use cases that can be applied to smart
city transportation initiatives. These can be used as a starting point for a more
complete set and as a model on how to create a practical use case template.

8.6 Summary

The use case is a very important tool to gauge the implementation of big data
and analytics techniques regarding smart city transportation. This chapter ex-