Building Linked Data from Historical Maps

Historical maps provide a rich source of data for social science researchers since they contain detailed documentation of a wide variety of factors, such as land-use changes, development of transportation networks, changes in waterways, destruction of wetlands, etc. However, these maps are typically available only as scanned documents and it is labor intensive for a scientist to extract the needed data for a study. In this paper, we address the problem of how to convert vector data extracted from multiple historical maps into Linked Data. We describe the methods for efficiently finding the links across maps, converting the data into RDF, and querying the resulting knowledge graphs. We present preliminary results that demonstrate that our approach can be used to efficiently determine changes in the Los Angeles railroad network from data extracted from multiple maps.