Details
Original language | English |
---|---|
Title of host publication | Event Analytics across Languages and Communities |
Publisher | Springer Nature |
Pages | 111-122 |
Number of pages | 12 |
ISBN (electronic) | 9783031644511 |
ISBN (print) | 9783031644504 |
Publication status | Published - 2025 |
Abstract
Collecting and integrating event information in a knowledge graph enables the analysis of major societal events, their interdependencies with other events and actors and their perception and impact. While existing cross-domain knowledge graphs such as Wikidata and DBpedia also contain event knowledge, they are typically limited regarding the diversity of event representations and types. In this chapter, we first describe EventKG-a knowledge graph of multilingual event-centric information bringing together heterogeneous event information from different sources. Since the thorough understanding of events further demands the availability of context information in different modalities, we then present the Open Event Knowledge Graph (OEKG), which extends the coverage and modality of EventKG by integrating several of the event-related datasets presented in this book and opens up several possibilities for cross-lingual, event-centric open analytics. Through several statistics, example queries and applications, we show the versatility and the applicability of EventKG and OEKG for event analytics across languages and communities.
ASJC Scopus subject areas
- Computer Science(all)
- General Computer Science
- Social Sciences(all)
- General Social Sciences
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Event Analytics across Languages and Communities. Springer Nature, 2025. p. 111-122.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Collection and Integration of Event-Centric Information in Cross-Lingual Knowledge Graphs
AU - Gottschalk, Simon
N1 - Publisher Copyright: © The Author(s) 2025. All rights reserved.
PY - 2025
Y1 - 2025
N2 - Collecting and integrating event information in a knowledge graph enables the analysis of major societal events, their interdependencies with other events and actors and their perception and impact. While existing cross-domain knowledge graphs such as Wikidata and DBpedia also contain event knowledge, they are typically limited regarding the diversity of event representations and types. In this chapter, we first describe EventKG-a knowledge graph of multilingual event-centric information bringing together heterogeneous event information from different sources. Since the thorough understanding of events further demands the availability of context information in different modalities, we then present the Open Event Knowledge Graph (OEKG), which extends the coverage and modality of EventKG by integrating several of the event-related datasets presented in this book and opens up several possibilities for cross-lingual, event-centric open analytics. Through several statistics, example queries and applications, we show the versatility and the applicability of EventKG and OEKG for event analytics across languages and communities.
AB - Collecting and integrating event information in a knowledge graph enables the analysis of major societal events, their interdependencies with other events and actors and their perception and impact. While existing cross-domain knowledge graphs such as Wikidata and DBpedia also contain event knowledge, they are typically limited regarding the diversity of event representations and types. In this chapter, we first describe EventKG-a knowledge graph of multilingual event-centric information bringing together heterogeneous event information from different sources. Since the thorough understanding of events further demands the availability of context information in different modalities, we then present the Open Event Knowledge Graph (OEKG), which extends the coverage and modality of EventKG by integrating several of the event-related datasets presented in this book and opens up several possibilities for cross-lingual, event-centric open analytics. Through several statistics, example queries and applications, we show the versatility and the applicability of EventKG and OEKG for event analytics across languages and communities.
UR - http://www.scopus.com/inward/record.url?scp=105002629265&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-64451-1_6
DO - 10.1007/978-3-031-64451-1_6
M3 - Contribution to book/anthology
AN - SCOPUS:105002629265
SN - 9783031644504
SP - 111
EP - 122
BT - Event Analytics across Languages and Communities
PB - Springer Nature
ER -