Semantic data sharing and pricing in web 3.0 using blockchain
Web 3.0 represents an advanced internet framework that combines technologies such as blockchain and semantic communication to enable decentralized, transparent data exchange. While semantic communication reduces redundancy by transmitting contextual meaning rather than raw data and existing systems lack a cohesive integration strategy, further, the centralized models struggle with efficient semantic sharing and valuation. The work proposed integration framework of semantic web communication with blockchain to enhance reliable web 3.0 data sharing. A novel “Proof of Semantic” mechanism tackles data integrity issues, ensuring only high-quality semantic inputs. The approach also elucidates the implementation of the bottleneck method and state channels. The computational load is optimized using a semantic shared protocol across the web. Further, a hierarchical Stackelberg game model optimizes semantic pricing, balancing stakeholder incentives. Evaluations confirm the framework’s efficacy, achieving reduction in network load without compromising accuracy compared to conventional approaches.
Authors
- Hanumantha Rao Battu
- Onur Osman (ORCID: https://orcid.org/0000-0001-7675-7999)
- Srihari Babu Gole (ORCID: https://orcid.org/0000-0003-0163-1413)
- V. Sitharamulu (ORCID: https://orcid.org/0000-0002-3419-1074)
- Jawad Rasheed (ORCID: https://orcid.org/0000-0003-3761-1641)
- G. Sucharitha
Institutions
- İstanbul Sabahattin Zaim Üniversitesi (TR)
- Applied Science Private University (JO)
- Deccan College of Medical Sciences (IN)
- İstanbul Nişantaşı Üniversitesi (TR)
- Istanbul Medipol University (TR)
- Advanced Numerical Research and Analysis Group (IN)
- Istanbul University (TR)
- Koneru Lakshmaiah Education Foundation (IN)
- GITAM University (IN)
Publication Details
- Journal
- Discover Computing
- Published
- 2025-12-02
- DOI
- https://doi.org/10.1007/s10791-025-09822-9
- Primary Topic
- Blockchain Technology Applications and Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00