Motivation

1. GIS (now Geospatial Computational Science) has full ecosystem from undergraduate to Ph.D.
2. SDAR have some good enrollment trend.
3. Both on Data Science and have common interests:
   1. Courses:
      • Data visualization
      • Machine learning
      • Spatial analysis

Suggestions

• Curriculum
  • Incorporate further each others/ current elective/prerequisites
  • SDAR/GIS master's program fast-track?
  • Not change much but include each other further

Suggestions

• Joint conference + pre-conference workshop (Fall)
  • Theme: Spatial data science
    • Guest speakers
    • Student posters
    • Invited panel (6 papers, 3 internal, 3 DFW)
    • Alum speakers
    • Soft job fair (invited industry reps).

Suggestions

• Karl Tour to Taiwan in summer
  • To promote both programs particularly Geospatial programs (e.g. certificate, master, Ph.D.)
  • Build faculty exchange and possible dual degree program
  • give talks on promoting interest in Geospatial Computational Science (GCS).
• Internship for GCS students (undergraduate and graduate) in Taiwan