Knowledge Graph Exploration: Where Are We and Where Are We Going? (Invited Article)

Matteo Lissandrini, Torben Bach Pedersen, Katja Hose, Davide Mottin

Abstract:

Knowledge graphs (KGs) represent facts in the form of subject-predicate-object triples and are widely used to represent and share knowledge on the Web. Their ability to represent data in complex domains augmented with semantic annotations has attracted the attention of both research and industry. Yet, their widespread adoption in various domains and their generation processes have made the contents of these resources complicated. We speak of knowledge graph exploration as of the gradual discovery and understanding of the contents of a large and unfamiliar KG. In this paper, we present an overview of the state-of-the-art approaches for KG exploration. We divide them into three areas: profiling, search, and analysis and we argue that, while KG profiling and KG exploratory search received considerable attention, exploratory KG analytics is still in its infancy. We conclude with an overview of promising future research directions towards the design of more advanced KG exploration techniques.
Taxonomy of KG Exploration techniques and their positioning on the spectrum of features. Top KG Exploration, leaves: Summarization/Profiling, Exploratory Analytics, Exploratory search.
The taxonomy of KG Exploration techniques that we propose and their mapping on the interactivity/ domain-knowledge requirements spectrum.

Cite:

and
Knowledge Graph Exploration: Where Are We and Where Are We Going?.”
SIGWEB Newsletter (1-8).

article{LissandriniKGE20,
author = {Lissandrini, Matteo and Pedersen, Torben Bach and Hose, Katja and Mottin, Davide},
title = {Knowledge Graph Exploration: Where Are We and Where Are We Going?},
year = {2020},
issue_date = {Summer 2020},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
number = {Summer 2020},
issn = {1931-1745},
url = {https://doi.org/10.1145/3409481.3409485},
doi = {10.1145/3409481.3409485},
journal = {SIGWEB Newsl.},
month = jul,
articleno = {4},
numpages = {8}
}