How Does Knowledge Evolve in Open Knowledge Graphs?

Axel Polleres, Romana Pernisch*, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, Stefania Dumbrava, Lorena Etcheverry, Nicolas Ferranti, Katja Hose, Ernesto Jiḿenez-Ruiz, Matteo Lissandrini, Ansgar Scherp, Riccardo Tommasini, Johannes Wachs

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Openly available, collaboratively edited Knowledge Graphs (KGs) are key platforms for the collective management of evolving knowledge. The present work aims t o provide an analysis of the obstacles related to investigating and processing specifically this central aspect of evolution in KGs. To this end, we discuss (i) the dimensions of evolution in KGs, (ii) the observability of evolution in existing, open, collaboratively constructed Knowledge Graphs over time, and (iii) possible metrics to analyse this evolution. We provide an overview of relevant state-of-the-art research, ranging from metrics developed for Knowledge Graphs specifically to potential methods from related fields such as network science. Additionally, we discuss technical approaches - and their current limitations - related to storing, analysing and processing large and evolving KGs in terms of handling typical KG downstream tasks.
Original languageEnglish
Article number11
Journal Transactions on Graph Data and Knowledge (TGDK)
Volume1
Issue number1
Number of pages59
DOIs
Publication statusPublished - 19 Dec 2023

Keywords

  • Knowledge Graph
  • Knowledge graph embedding

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