Data Structure Generalization

Data Structure Generalization is a theoretical framework in geographic information science that specifies principles and rules for systematically simplifying or abstracting spatial data structures while preserving essential topological, geometric, and semantic properties across varying levels of detail.

151

Publications

8.5K

Citations

361

Authors

178

Institutions

Publications per year

2017–2026

19

Authors

361

  1. PV
    Peter van Oosterom

    Delft University of Technology, Netherlands

    3 publications · 199 citations

    3

    h-index

  2. RC
    Richard Cole

    New York University, United States

    3 publications · 158 citations

    3

    h-index

  3. WL
    Witold Litwin

    Université Paris Dauphine-PSL, France

    3 publications · 333 citations

    3

    h-index

  4. RH
    Ramesh Hariharan

    Indian Institute of Science Bangalore, India

    3 publications · 158 citations

    3

    h-index

  5. AE
    Alon Efrat

    University of Arizona, United States

    2 publications · 22 citations

    2

    h-index

1–5 of 361

Venues

  1. SIAM Journal on Computing

    7 publications · 419 citations

    7

    h-index

  2. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 4 publications · 1.2K citations

    4

    h-index

  3. 4

    h-index

  4. ACM SIGPLAN Notices

    3 publications · 158 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 86 citations

    3

    h-index

1–5