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Title: Creating Structured, Linked Geographic Data from Historical Maps: Challenges and Trends
Citation Type: Book, Section
Publication Year: 2019
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DOI: https://doi.org/10.1007/978-3-319-66908-3_3
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Abstract: Historical geographic data are essential for a variety of studies of cancer and environmental epidemiology, urbanization, and landscape ecology. However, existing data sources typically contain only contemporary information. Historical maps hold a great deal of detailed geographic information at various times in the past. Yet, finding relevant maps is difficult, and the map content is not machine-readable. This chapter presents the challenges and trends in building a map processing, modeling, linking, and publishing framework. The framework will enable querying historical map collections as a unified and structured spatiotemporal source in which individual geographic phenomena (extracted from maps) are modeled (described) with semantic descriptions and linked to other data sources (e.g., DBpedia). This framework will allow making use of historical geographic datasets from a variety of maps, efficiently, over large geographic extents. Realizing such a framework poses significant research challenges in multiple fields in computer science including digital map processing, data integration, and the Semantic Web technologies, and other disciplines such as spatial, social, and health sciences. Tackling these challenges will not only advance research in computer science and geographic information science but also present a unique opportunity for interdisciplinary research.
Url: https://link.springer.com/chapter/10.1007/978-3-319-66908-3_3
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Authors: Chiang, Yao-Yi; Duan, Weiwei; Leyk, Stefan; Uhl, Johannes, H; Koblock, Craig, A
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Pages: 37-63
Volume Title: Using Historical Maps in Scientific Studies
Publisher: SpringerBriefs in Geography
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Data Collections: IPUMS NHGIS
Topics: Land Use/Urban Organization, Other, Population Data Science, Population Mobility and Spatial Demography
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