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SUMMARY:MapReader Workshop: Using Machine Learning to Analyze Large Collec
 tions of Digitized Maps - Katherine McDonough\, Rosie Wood\, Kalle Westerl
 ing
DTSTART;TZID=Europe/Amsterdam:20240925T090000
DTEND;TZID=Europe/Amsterdam:20240925T120000
DTSTAMP:20260819T031732Z
UID:pretalx-spathum24-FYVZZG@pretalx.com
DESCRIPTION:MapReader is a software library that was designed for humaniti
 es research with big digitised map collections. The winner of the 2023 Roy
  Rosenzweig Prize for Innovation in Digital History from the American Hist
 orical Association\, MapReader was developed first within the Living with 
 Machines project\, but was created with a wider community of historians in
  mind as future users.  Learn more about MapReader at https://github.com/m
 aps-as-data/MapReader.\n\nMapReader performs two tasks. \n1. Patch classif
 ication allows users to identify concepts of visual interest on maps\, and
  then to define queries for predicting whether those concepts are present 
  on hundreds or thousands of individual sheets. The power of this approach
  is its flexibility for any number of spatially-driven research questions.
 \n2. Text spotting makes it possible to create a structured dataset of all
  text on a map image. MapReader implements models made available during th
 e 2024 MapText competition (Chazalon\, Joseph. “ICDAR 2024 Competition o
 n Historical Map Text Detection\, Recognition\, and Linking”. Presented 
 at the International Conference on Document Analysis and Recognition (ICDA
 R)\, Athens\, Greece\, September 4\, 2024. https://doi.org/10.5281/zenodo.
 13628614.)\n\nThis workshop aims to bring together historians and others w
 ith an interest in using digitised historical map collections as primary s
 ources for digitally-inflected research. By bringing together peers workin
 g in this space\, we aim to learn about and discuss ways to encourage open
  research in the humanities through skill development and shared digital r
 esources and infrastructure. \n\nDuring the workshop\, participants will:\
 n- Learn about the research and theoretical motivations behind MapReader\,
  and how it fits in a growing ecosystem of computer vision tools for human
 ities research\n- Test a demo of MapReader with sample data\n- Learn the b
 asics of computer vision and machine learning as applied to computational 
 maps research\n- Discuss how to apply MapReader to your own map collection
 s\n- Reflect on the opportunities for using “automatic” methods for an
 alysing maps in humanistic research
LOCATION:MG2 01.10
URL:https://pretalx.com/spathum24/talk/FYVZZG/
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