Topological Data Structures

Topological Data Structures is a data organization framework in geographic information science that explicitly represents the spatial relationships among vector geometric entities—such as points, lines, and polygons—by encoding adjacency, connectivity, and containment to ensure logical consistency and support advanced spatial analysis.

554

Publications

28.1K

Citations

1.5K

Authors

689

Institutions

Publications per year

2017–2026

288

Authors

1.5K

  1. GC
    Gunnar Carlsson

    Stanford University, United States

    7 publications · 3.7K citations

    7

    h-index

  2. PB
    Peer‐Timo Bremer

    Lawrence Livermore National Laboratory, United States

    6 publications · 388 citations

    6

    h-index

  3. JL
    Jiyeong Lee

    University of Seoul, South Korea

    6 publications · 356 citations

    6

    h-index

  4. GP
    Giovanni Petri

    Institute for Scientific Interchange, Italy

    6 publications · 352 citations

    6

    h-index

  5. VP
    Valerio Pascucci

    Lawrence Livermore National Laboratory, United States

    6 publications · 388 citations

    6

    h-index

1–5 of 1.5K

Venues

  1. arXiv (Cornell University)

    Repository · 30 publications · 719 citations

    17

    h-index

  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 10 publications · 452 citations

    10

    h-index

  3. 10

    h-index

  4. Expert Systems with Applications

    8 publications · 342 citations

    8

    h-index

  5. Computer Graphics Forum

    7 publications · 408 citations

    7

    h-index

1–5