Graph-based Data Integration

Graph-Based Data Integration is a data integration framework that utilizes graph structures to represent and interconnect heterogeneous data sources, distinguished by its reliance on nodes, edges, and graph operations to model relationships and enable unified access, querying, and analysis across distributed datasets.

69

Publications

5K

Citations

222

Authors

109

Institutions

Publications per year

2017–2026

38

Authors

222

  1. JP
    Jong-Eun Park

    Wellcome Sanger Institute, United Kingdom

    2 publications · 1K citations

    2

    h-index

  2. KP
    Krzysztof Polański

    Wellcome Sanger Institute, United Kingdom

    2 publications · 1K citations

    2

    h-index

  3. KB
    Kerstin B. Meyer

    University of Cambridge, United Kingdom

    2 publications · 1K citations

    2

    h-index

  4. AS
    Andy Seaborne

    Hewlett-Packard (United States), United States

    2 publications · 993 citations

    2

    h-index

  5. XF
    Xiaowen Feng

    Zhejiang University, China

    2 publications · 515 citations

    2

    h-index

1–5 of 222

Venues

  1. Bioinformatics

    4 publications · 1.2K citations

    4

    h-index

  2. Semantic Web

    2 publications · 43 citations

    2

    h-index

  3. Genome biology

    2 publications · 570 citations

    2

    h-index

  4. bioRxiv (Cold Spring Harbor Laboratory)

    Repository · 2 publications · 68 citations

    2

    h-index

  5. Journal of Computing in Civil Engineering

    2 publications · 101 citations

    2

    h-index

1–5