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188 Big Data Analytics for Connected Vehicles and Smart Cities Building a Data Lake 189

Figure 9.3 A proposed approach methodology for the implementation of a smart city and
transportation data lake.

The overall philosophy behind the approach is to make incremental or
stepwise progress toward the establishment and operation of the data lake. Ini-
tially the focus is placed on a very small number of use cases that are addressed
in a pilot project. The pilot use cases are then used as the basis for conducting
the approach methodology on a pilot project. During the pilot project, all ele-
ments of the operation of the data lake are brought into play, including inges-
tion, preparation, discovery, and exchange of data. Each step in the methodol-
ogy is explained in the following sections.

Preparing for the Data Lake
Preparation or planning for the data lake includes exploring requirements and
objectives with the target end users. In the case of a smart city transportation
initiative, end users typically consist of city officials and other city transporta-
tion partners such as departments of transportation, transit agencies and other
transportation service providers. It would also be helpful to bring relevant pri-
vate-sector participants into the dialogue at this early stage.

Identifying Pilot Subjects
The use case concept is employed as a major tool in identifying subjects for
the pilot. The use case pilot described in Chapter 5 can be an effective format
for capturing the use case information. Whether the format is used or not, it
is essential to capture the primary ingredients for the pilot, including the data
to be used, the expected value to be achieved, and an initial understanding of
the analytics to be applied. The selection criteria for the use cases are as follows:

• The use cases deliver immediate value to the city.
• Data to support the analytics required for the use cases is readily available
either from city sources, transportation partners, or the private sector.