Maps as Data
Start Date
20-3-2024 12:00 AM
End Date
20-3-2024 12:00 AM
Description
Instead of principally thinking of maps as the outcome of digital humanities research, Machine Learning opens the door to investigating very large collections of maps as input. On both the “Living with Machines” and Machines Reading Maps projects, I have worked with a range of library partners to create datasets inferred from the content of these collections. This talk explores the design of our data creation methods (in particular our software library MapReader), how open and reproducible digital research can support humanistic inquiry, and why these approaches allow us to not only understand, but analyze, maps in new ways.
Keywords
digital scholarship
Type
Keynote Presentation
Language
eng
Location
budsc2024/keynote (Keynotes)
Maps as Data
budsc2024/keynote (Keynotes)
Instead of principally thinking of maps as the outcome of digital humanities research, Machine Learning opens the door to investigating very large collections of maps as input. On both the “Living with Machines” and Machines Reading Maps projects, I have worked with a range of library partners to create datasets inferred from the content of these collections. This talk explores the design of our data creation methods (in particular our software library MapReader), how open and reproducible digital research can support humanistic inquiry, and why these approaches allow us to not only understand, but analyze, maps in new ways.