Ontology-based Data Fusion

Ontology-Based Data Fusion is a data fusion methodology that utilizes formal ontologies to enable semantic interoperability and automated reasoning during the integration of heterogeneous geospatial datasets.

81

Publications

2.7K

Citations

277

Authors

131

Institutions

Publications per year

2017–2026

29

Authors

277

  1. PC
    Paulo Costa

    George Mason University, United States

    7 publications · 185 citations

    7

    h-index

  2. EB
    Erik Blasch

    United States Air Force Research Laboratory, United States

    7 publications · 139 citations

    7

    h-index

  3. KB
    Kathryn Blackmond Laskey

    George Mason University, United States

    5 publications · 163 citations

    5

    h-index

  4. JP
    J. P. de Villiers

    University of Pretoria, South Africa

    3 publications · 60 citations

    3

    h-index

  5. MM
    Mieczyslaw M. Kokar

    Northeastern University, United States

    3 publications · 56 citations

    3

    h-index

1–5 of 277

Venues

  1. International Conference on Information Fusion

    Conference · 3 publications · 85 citations

    3

    h-index

  2. Information Fusion

    3 publications · 135 citations

    3

    h-index

  3. Expert Systems with Applications

    3 publications · 102 citations

    3

    h-index

  4. IEEE Access

    2 publications · 37 citations

    2

    h-index

  5. 2

    h-index

1–5