A New Blockchain Ecosystem for Trusted, Traceable and Transparent Ontological Knowledge Management

Papaioannou, Thanasis G.; Stankovski, Vlado; Kochovski, Petar; Simonet-Boulogne, Anthony; Barelle, Caroline; Ciaramella, Alberto; Ciaramella, Marco; Stamoulis, George D.

doi:10.1007/978-3-030-92916-9_8

Cited by 7 publications

(8 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, web content is arguably increasingly centralised and asymmetric in terms of the distribution of knowledge and power. Thus, blockchain technologies present themselves as potential next-generation enablers of service exchange and content management [66]. A semantically enriched blockchain software ecosystem based on decentralised applications may be helpful to address bias due to less access of specific demographic groups to these technologies.…”

Section: Bias Can Be Found In the Data Used To Construct Sw Technologiesmentioning

confidence: 99%

Semantic Web technologies and bias in artificial intelligence: A systematic literature review

Lobo

Daga

Alani

et al. 2023

View full text Add to dashboard Cite

Bias in Artificial Intelligence (AI) is a critical and timely issue due to its sociological, economic and legal impact, as decisions made by biased algorithms could lead to unfair treatment of specific individuals or groups. Multiple surveys have emerged to provide a multidisciplinary view of bias or to review bias in specific areas such as social sciences, business research, criminal justice, or data mining. Given the ability of Semantic Web (SW) technologies to support multiple AI systems, we review the extent to which semantics can be a “tool” to address bias in different algorithmic scenarios. We provide an in-depth categorisation and analysis of bias assessment, representation, and mitigation approaches that use SW technologies. We discuss their potential in dealing with issues such as representing disparities of specific demographics or reducing data drifts, sparsity, and missing values. We find research works on AI bias that apply semantics mainly in information retrieval, recommendation and natural language processing applications and argue through multiple use cases that semantics can help deal with technical, sociological, and psychological challenges.

show abstract

Section: Bias Can Be Found In the Data Used To Construct Sw Technologiesmentioning

confidence: 99%

Semantic Web technologies and bias in artificial intelligence: A systematic literature review

Lobo

Daga

Alani

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The next-generation ONTOCHAIN framework is a modular blockchain framework that leads to a more human-centered Internet that supports the values of openness, decentralization, inclusiveness, and the protection of privacy [ 21 ]. It delivers various real-world solutions, such as trustworthy web and social media, trustworthy crowdsensing and reputation management, distribution logistics, data management, and similar solutions via the use of multiple ledgers and semantic technologies.…”

Section: High-level Classification Of Reusable Smart Contractsmentioning

confidence: 99%

A Recommender System for Robust Smart Contract Template Classification

Gec

Stankovski²,

Lavbič³

et al. 2023

Sensors

View full text Add to dashboard Cite

IoT environments are becoming increasingly heterogeneous in terms of their distributions and included entities by collaboratively involving not only data centers known from Cloud computing but also the different types of third-party entities that can provide computing resources. To transparently provide such resources and facilitate trust between the involved entities, it is necessary to develop and implement smart contracts. However, when developing smart contracts, developers face many challenges and concerns, such as security, contracts’ correctness, a lack of documentation and/or design patterns, and others. To address this problem, we propose a new recommender system to facilitate the development and implementation of low-cost EVM-enabled smart contracts. The recommender system’s algorithm provides the smart contract developer with smart contract templates that match their requirements and that are relevant to the typology of the fog architecture. It mainly relies on OpenZeppelin, a modular, reusable, and secure smart contract library that we use when classifying the smart contracts. The evaluation results indicate that by using our solution, the smart contracts’ development times are overall reduced. Moreover, such smart contracts are sustainable for fog-computing IoT environments and applications in low-cost EVM-based ledgers. The recommender system has been successfully implemented in the ONTOCHAIN ecosystem, thus presenting its applicability.

show abstract

“…Thanasis et al [21] combine ontological knowledge and BCT to gain reliable service exchange and trustworthy content handling. It can be achieved by applying advanced knowledge management mechanisms for organizations such as health, economy, public services, energy and sustainability, news, media, entertainment, Industry 4.0 and tourism.…”

Section: B Organizationsmentioning

confidence: 99%

“…Also, a multi-layer method is developed for a semantically-enriched blockchain software ecosystem named ONTOCHAIN. It enables the development of trustworthy distributed applications [21]. System security can be increased and potential attacks prevented [27], even under an assumed attack of quantum computing [24].…”

Section: A Main Challengesmentioning

confidence: 99%