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Article Dans Une Revue Transactions on Graph Data and Knowledge Année : 2023

How does knowledge evolve in open knowledge graphs?

Daniele Dell'Aglio
Katja Hose
Matteo Lissandrini

Résumé

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.
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hal-04373234 , version 1 (04-01-2024)

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Axel Polleres, Romana Pernisch, Angela Bonifati, Daniele Dell'Aglio, Daniil Dobriy, et al.. How does knowledge evolve in open knowledge graphs?. Transactions on Graph Data and Knowledge, 2023, 1 (1), pp.11:1-11:59. ⟨10.4230/TGDK.1.1.11⟩. ⟨hal-04373234⟩
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