Details
| Original language | English |
|---|---|
| Pages (from-to) | 1390-1397 |
| Number of pages | 8 |
| Journal | Proceedings of the VLDB Endowment |
| Volume | 18 |
| Issue number | 5 |
| Publication status | E-pub ahead of print - 1 Sept 2025 |
| Event | 51st International Conference on Very Large Data Bases, VLDB 2025 - London, United Kingdom (UK) Duration: 1 Sept 2025 → 5 Sept 2025 |
Abstract
Knowledge graphs (KGs) play a crucial role in the integration and organization of heterogeneous data and knowledge, enabling advanced data analytics and decision-making across various industries. This vision paper addresses critical challenges in managing KGs, emphasizing their relevance in integrating information from disparate sources. We propose the concept of knowledge graph ecosystems and life cycles to systematically manage tasks, e.g., data integration, standardization, continuous updates, efficient querying, and provenance tracking. By adopting our approach, organizations can enhance the accuracy, consistency, and reliability of KGs, thus improving knowledge management, enabling the extraction of valuable insights, and ensuring transparency and accountability.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science (miscellaneous)
- Computer Science(all)
- General Computer Science
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In: Proceedings of the VLDB Endowment, Vol. 18, No. 5, 01.09.2025, p. 1390-1397.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - From Genesis to Maturity
T2 - 51st International Conference on Very Large Data Bases, VLDB 2025
AU - Geisler, Sandra
AU - Chaves-Fraga, David
AU - Lenzerini, Maurizio
AU - Cappiello, Cinzia
AU - Dimou, Anastasia
AU - Rula, Anisa
AU - Celino, Irene
AU - Iglesias-Molina, Ana
AU - Van Assche, Dylan
AU - Welten, Sascha
AU - Vidal, Maria Esther
N1 - Publisher Copyright: © 2025, VLDB Endowment. All rights reserved.
PY - 2025/9/1
Y1 - 2025/9/1
N2 - Knowledge graphs (KGs) play a crucial role in the integration and organization of heterogeneous data and knowledge, enabling advanced data analytics and decision-making across various industries. This vision paper addresses critical challenges in managing KGs, emphasizing their relevance in integrating information from disparate sources. We propose the concept of knowledge graph ecosystems and life cycles to systematically manage tasks, e.g., data integration, standardization, continuous updates, efficient querying, and provenance tracking. By adopting our approach, organizations can enhance the accuracy, consistency, and reliability of KGs, thus improving knowledge management, enabling the extraction of valuable insights, and ensuring transparency and accountability.
AB - Knowledge graphs (KGs) play a crucial role in the integration and organization of heterogeneous data and knowledge, enabling advanced data analytics and decision-making across various industries. This vision paper addresses critical challenges in managing KGs, emphasizing their relevance in integrating information from disparate sources. We propose the concept of knowledge graph ecosystems and life cycles to systematically manage tasks, e.g., data integration, standardization, continuous updates, efficient querying, and provenance tracking. By adopting our approach, organizations can enhance the accuracy, consistency, and reliability of KGs, thus improving knowledge management, enabling the extraction of valuable insights, and ensuring transparency and accountability.
UR - http://www.scopus.com/inward/record.url?scp=105005139866&partnerID=8YFLogxK
U2 - 10.14778/3718057.3718067
DO - 10.14778/3718057.3718067
M3 - Conference article
AN - SCOPUS:105005139866
VL - 18
SP - 1390
EP - 1397
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 5
Y2 - 1 September 2025 through 5 September 2025
ER -