Using Queries as Schema-Templates for Graph Databases

From International Center for Computational Logic

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Using Queries as Schema-Templates for Graph Databases

Stephan MennickeStephan Mennicke,  Jan-Christoph KaloJan-Christoph Kalo,  Wolf-Tilo BalkeWolf-Tilo Balke
Stephan Mennicke, Jan-Christoph Kalo, Wolf-Tilo Balke
Using Queries as Schema-Templates for Graph Databases
Datenbank-Spektrum, 18(2):89-98, May 2018
  • KurzfassungAbstract
    In contrast to heavy-handed ER-style data models in relational databases, knowledge graphs (or graph databases) capture entity semantics in terms of entity relationships and properties following a simple collect-as-you-go model. While this allows for a more flexible and dynamically adaptable knowledge representation, it comes at the price of more complex querying: with varying degrees of information sparsity, it will gradually become more difficult to figure out what an entity actually represents. Thus, matching the intended schema as specified by a query against actually occurring entity patterns in the graph database needs severe attention on a conceptual level. In this article, we analyze graph patterns as schema information from a graph pattern matching perspective. We argue that every query consists of a mixture of conceptual information (how entities are structured) together with evaluation information (further dependencies and constraints on data) and that this mixture is not always easy to divide. To arrive at truly schema-aware graph query processing, we propose several matching mechanisms, each mandating a specific semantic meaning of the graph pattern, and discuss their practical applicability.
  • Forschungsgruppe:Research Group: Wissensbasierte Systeme
The final publication is available at Springer via http://dx.doi.org/10.1007/s13222-018-0286-9.
@article{MKB2018,
  author    = {Stephan Mennicke and Jan-Christoph Kalo and Wolf-Tilo Balke},
  title     = {Using Queries as Schema-Templates for Graph Databases},
  journal   = {Datenbank-Spektrum},
  volume    = {18},
  number    = {2},
  publisher = {Springer},
  year      = {2018},
  month     = {May},
  pages     = {89-98},
  doi       = {10.1007/s13222-018-0286-9}
}