Querying in the Age of Graph Databases and Knowledge Graphs

TL;DR

This paper provides a conceptual overview of data management tasks, data models, and query languages in graph databases and knowledge graphs, highlighting their importance in representing and managing knowledge effectively.

Contribution

It offers a comprehensive conceptual map of the data management tasks, models, and query languages relevant to graph databases and knowledge graphs.

Findings

Graphs are the preferred method for representing knowledge.

Graph databases and knowledge graphs are key solutions for managing graph data.

The paper maps out the core data management tasks and query languages for graphs.

Abstract

Graphs have become the best way we know of representing knowledge. The computing community has investigated and developed the support for managing graphs by means of digital technology. Graph databases and knowledge graphs surface as the most successful solutions to this program. The goal of this document is to provide a conceptual map of the data management tasks underlying these developments, paying particular attention to data models and query languages for graphs.