Details
| Original language | English |
|---|---|
| Title of host publication | The ACM Web Conference 2023 |
| Subtitle of host publication | Companion of the World Wide Web Conference, WWW 2023 |
| Pages | 1422-1423 |
| Number of pages | 2 |
| ISBN (electronic) | 9781450394161 |
| Publication status | Published - 30 Apr 2023 |
| Event | 2023 World Wide Web Conference, WWW 2023 - Austin, United States Duration: 30 Apr 2023 → 4 May 2023 |
Abstract
Knowledge Graphs have become a foundation for sharing data on the web and building intelligent services across many sectors and also within some of the most successful corporations in the world. The over centralisation of data on the web, however, has been raised as a concern by a number of prominent researchers in the field. For example, at the beginning of 2022 a €2.7B civil lawsuit was launched against Meta on the basis that it has abused its market dominance to impose unfair terms and conditions on UK users in order to exploit their personal data. Data centralisation can lead to a number of problems including: lock-in/siloing effects, lack of user control over their personal data, limited incentives and opportunities for interoperability and openness, and the resulting detrimental effects on privacy and innovation. A number of diverse approaches and technologies exist for decentralising data, such as federated querying and distributed ledgers. The main question is, though, what does decentralisation really mean for web data and Knowledge Graphs? What are the main issues and tradeoffs involved? These questions and others are addressed in this workshop.
Keywords
- Decentralisation, Distributed Ledgers, Federated Querying, Knowledge Graphs, Personal Data Policy, Personal Data Stores, Trust, Web Data
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
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The ACM Web Conference 2023 : Companion of the World Wide Web Conference, WWW 2023. 2023. p. 1422-1423.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Trusting Decentralised Knowledge Graphs and Web Data at the Web Conference
AU - Domingue, John
AU - Third, Aisling
AU - Vidal, Maria Esther
AU - Rohde, Philipp
AU - Cano, Juan
AU - Cimmino, Andrea
AU - Verborgh, Ruben
PY - 2023/4/30
Y1 - 2023/4/30
N2 - Knowledge Graphs have become a foundation for sharing data on the web and building intelligent services across many sectors and also within some of the most successful corporations in the world. The over centralisation of data on the web, however, has been raised as a concern by a number of prominent researchers in the field. For example, at the beginning of 2022 a €2.7B civil lawsuit was launched against Meta on the basis that it has abused its market dominance to impose unfair terms and conditions on UK users in order to exploit their personal data. Data centralisation can lead to a number of problems including: lock-in/siloing effects, lack of user control over their personal data, limited incentives and opportunities for interoperability and openness, and the resulting detrimental effects on privacy and innovation. A number of diverse approaches and technologies exist for decentralising data, such as federated querying and distributed ledgers. The main question is, though, what does decentralisation really mean for web data and Knowledge Graphs? What are the main issues and tradeoffs involved? These questions and others are addressed in this workshop.
AB - Knowledge Graphs have become a foundation for sharing data on the web and building intelligent services across many sectors and also within some of the most successful corporations in the world. The over centralisation of data on the web, however, has been raised as a concern by a number of prominent researchers in the field. For example, at the beginning of 2022 a €2.7B civil lawsuit was launched against Meta on the basis that it has abused its market dominance to impose unfair terms and conditions on UK users in order to exploit their personal data. Data centralisation can lead to a number of problems including: lock-in/siloing effects, lack of user control over their personal data, limited incentives and opportunities for interoperability and openness, and the resulting detrimental effects on privacy and innovation. A number of diverse approaches and technologies exist for decentralising data, such as federated querying and distributed ledgers. The main question is, though, what does decentralisation really mean for web data and Knowledge Graphs? What are the main issues and tradeoffs involved? These questions and others are addressed in this workshop.
KW - Decentralisation
KW - Distributed Ledgers
KW - Federated Querying
KW - Knowledge Graphs
KW - Personal Data Policy
KW - Personal Data Stores
KW - Trust
KW - Web Data
UR - http://www.scopus.com/inward/record.url?scp=85159624843&partnerID=8YFLogxK
U2 - 10.1145/3543873.3589756
DO - 10.1145/3543873.3589756
M3 - Conference contribution
AN - SCOPUS:85159624843
SN - 978-1-4503-9419-2
SP - 1422
EP - 1423
BT - The ACM Web Conference 2023
T2 - 2023 World Wide Web Conference, WWW 2023
Y2 - 30 April 2023 through 4 May 2023
ER -