Spawn of the TIGER.
GDT, Navtech, and Tele Atlas datasets all spun from
the same humble beginnings - the U.S. Census Bureau's TIGER dataset. This original
dataset contained mainly digital streets and their address ranges. TIGER was born
when the USGS extended the U.S. Bureau of the Census' 1967 GBF/DIME dataset from a
small 2 percent of total U.S. land area and 60 percent of U.S. population (the
largest 145 metropolitan areas) to cover the entire country. In the public sector,
TIGER has since become a key component of the NSDI.
The private sector also saw potential value in the original TIGER linework and
attributes. Thanks in part to a 1973 Census workshop entitled "Data Uses in the
Private Sector," some of the major geodemographics firms of the time, such as
began providing marketing services based on geodemographic analysis of the GBF/DIME
dataset. This public/private partnering continued with the release of TIGER around
1990. But as with many of life's bleeding-edge technologies, TIGER had some
fundamental problems. It contained many errors and was not regularly maintained.
Also, TIGER's positional accuracy was originally no greater than that of a 1:100,000
scale USGS map - an accuracy standard requiring at least 90 percent of points to be
within 164.04 feet of their actual location. For many spatial applications, such as
cadastral or engineering projects, such accuracy was woefully inadequate. In addition,
the TIGER model was (and remains) daunting to the general public.
Recognizing the sales potential of a more accurate and easy-to-use spatial dataset,
GDT, Navtech, and Tele Atlas began cleaning up and reselling TIGER data. Part of the
value these private vendors added was simply compiling the entire U.S. dataset and
simplifying it as needed, for use in a GIS, for instance. The other big value was
improving both positional and attribute accuracy of the TIGER linework. To that end,
the private firms opened field offices, built relationships with local government
agencies and utility companies to obtain source material, and, when absolutely
necessary, drove the roads with GPS units to further enhance the data. More commonly,
though, teams of (otherwise unemployable) geographers realigned TIGER linework to
aerial orthophotographs, or conflated TIGER's attributes to more accurate road