  Despite the growing availability of big data in many fields, historical data
on socioevironmental phenomena are often not available due to a lack of
automated and scalable approaches for collecting, digitizing, and assembling
them. We have developed a data-mining method for extracting tabulated, geocoded
data from printed directories. While scanning and optical character recognition
(OCR) can digitize printed text, these methods alone do not capture the
structure of the underlying data. Our pipeline integrates both page layout
analysis and OCR to extract tabular, geocoded data from structured text. We
demonstrate the utility of this method by applying it to scanned manufacturing
registries from Rhode Island that record 41 years of industrial land use. The
resulting spatio-temporal data can be used for socioenvironmental analyses of
industrialization at a resolution that was not previously possible. In
particular, we find strong evidence for the dispersion of manufacturing from
the urban core of Providence, the state's capital, along the Interstate 95
corridor to the north and south.
