Global Positioning System Reference
In-Depth Information
CCP authorities have made a decision to develop a new system that
not only integrates available spatial and conventional data of interest but
also allows dynamic data manipulation and presentation in tables, graphs,
and maps. Since CCP is a public institution that promotes development
in Central American countries, three of the requirements were to ensure
that (1) the new system is based on free software, (2) it does not require
specialized knowledge to access data, and (3) users may be able to perform
all manipulations and analysis through the Web. The necessity to use free
software relies on the recently issued decree by the Government of Costa
Rica that requires the use of free software, if available, in public institutions.
Although using free software requires the expertise of developers to face
many technical problems during implementation and maintenance, the CCP
authorities decided to take this risk and the related costs of hiring highly-
skilled developers. The requirement of relying on a system that does not
require geo-knowledge is to encourage non-expert users to consider spatial
data as “fi rst-class citizens” in the decision-making processes without the
necessity to overcome the (sometimes complex) problems of data integration
and improvements in data quality. The last requirement of using the Web
arises from considering geographically-spread users.
The available conventional and spatial data cover many years of Costa
Rican history, as well as current data that allow decision-making users to
better understand different aspects of regional evolution and development,
and help make informed decisions towards progress; therefore, adequate
structures and tools that facilitate storage of historical data and its analysis
are required.
Data included in our case study for presentation in this chapter is
currently limited to the period from 1981 to 2005 and refers to a number of
cases resulting from different types of cancer, as well as to demographics
data, e.g., populations, births, and deaths. Cancers are reported for each
district according to cancer types (e.g., breast cancer, stomach cancer,
leukemia) and gender, while demographics data does not consider cancer
types. On the one hand, the data for cancers was retrieved from the existing
database and it does not need any transformation. On the other hand, the
demographics data is mainly delivered as spreadsheets in some cases with
structures that demanded some programming effort. An example is given
in Fig. 3 that shows the data related to population (Fig. 3a), births (Fig. 3b),
and deaths (Fig. 3c) in Costa Rica for both male and female. The integration
processes were unnecessarily more complex than expected since data, e.g.,
in Figs. 3a and 3b, is represented by a “nice” view where the fi rst column
mixes provinces, counties, and districts using bold, indentation, and empty
rows for distinction of different granularity levels. Also, annual changes in
population are represented in one fi le, while the data related to births uses
one fi le for each year. The most complicated representation was given in the
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