Zusammenfassung
With Knowledge Graphs (KGs) at the center of numerous
applications such as recommender systems and question-answering,
the need for generalized pipelines to construct and continuously
update such KGs is increasing. While the individual steps that
are necessary to create KGs from unstructured sources (e.g.,
text) and structured data sources (e.g., databases) are mostly
well researched for their one-shot execution, their adoption for
incremental KG updates and the interplay of the individual steps
have hardly been investigated in a systematic manner so far. In
this work, we first discuss the main graph models for KGs and
introduce the major requirements for future KG construction
pipelines. Next, we provide an overview of the necessary steps
to build high-quality KGs, including cross-cutting topics such
as metadata management, ontology development, and quality
assurance. We then evaluate the state of the art of KG
construction with respect to the introduced requirements for
specific popular KGs, as well as some recent tools and
strategies for KG construction. Finally, we identify areas in
need of further research and improvement.
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