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36 Big Data Analytics for Connected Vehicles and Smart Cities What Is Big Data? 37

• Understand: The development of knowledge based on information re-
ceived such as an understanding of the underlying mechanisms that
drive transportation demand or a detailed picture of traveler behavior.
This may lead to what could be referred to as wow and whoops moments.
A wow moment occurs when a connection or mechanism that was not
previously obvious is identified and understood. A whoops moment is
when new understanding brings a realization that there are deficien-
cies in the delivery of current transportation services. A whoops moment
does not necessarily represent a catastrophic event. A good response to
a whoops moment would be to recognize that a new problem has been
identified and develop a plan with the associated budget to fix it. This
is this step into the realm of scientific investment planning or results-
based work program development, which is discussed in more detail in
Chapter 8.
• Act: The final step in a process involves taking the understanding that
has been gained using the data to create new information and turn it
into actionable strategies. It is important to consider this step even at the
beginning of the process when data is being collected. There would be
no point in collecting data and spending time converting it into infor-
mation, if it resulted in understanding that could not be put into action.
At our current stage in smart city transportation this could involve the
reassignment of resources, the definition of new capacity requirements,
the application of more effective traffic engineering, or a change in tran-
sit service frequency.

It is noticeable that many transportation agencies embark on large-scale
data collection exercises without a clear and detailed understanding of the use
to which the data will be put. It is hoped that the application of big data and
analytics techniques will encourage transportation agencies to take a wider view
of the process and develop a detailed understanding of the proposed uses of
the data. This will in turn lead to better approaches for defining the quality
of the data required. In the longer term, it could also be expected that the es-
tablishment and operation of data lakes (centralized repositories of data) will
also enable automated responses as we develop a better understanding of cause
and effect in transportation. Chapter 9 details data lakes. Figure 3.4 illustrates
a trend that is anticipated in industry and commerce as big data and analytics
pervade the organization. It is to be expected that a similar trend in transporta-
tion will emerge.
From a starting point of reporting, better capabilities to analyze the mech-
anisms that relate to transportation demand and supply enable us to build the
capability to predict future transportation demand, supply, and conditions.