An incentive mechanism for data sharing based on blockchain with smart contracts

© 2020 Data sharing techniques have progressively drawn increasing attention as a means of significantly reducing repetitive work. However, in the process of data sharing, the challenges regarding formation of mutual-trust relationships and increasing the level of user participation are yet to be solved. The existing solution is to use a third party as a trust organization for data sharing, but there is no dynamic incentive mechanism for data sharing with a large number of users. Blockchain 2.0 with smart contract has the natural advantage of being able to enable trust and automated transactions between a large number of users. This paper proposes a data sharing incentive model based on evolutionary game theory using blockchain with smart contract. The smart contract mechanism can dynamically control the excitation parameters and continuously encourages users to participate in data sharing

Motives and Incentives for Data Sharing in Industrial Data Ecosystems: An Explorative Single Case Study

The increasing connectivity of the business world leads to economic value being created less and less by one company alone, but rather through the exchange and combination of data by various actors in so-called data ecosystems. However, many companies are not yet willing to participate in data ecosystems because they do not see the added value of their participation. This is partly because the motives of data providers do not match the incentives offered to share their data. So far, there are only very few studies that deal with this issue in detail. Therefore, we close this research gap by adopting a conceptual model to the issue of motives and incentives for data sharing and applying it to the industrial data ecosystem Catena-X in a single case study. Through the case study analysis, we can identify seven different motives and eight incentives for data sharing

Blockchain as a learning tool: Analyzing transaction speeds at various gas limits in computer assembly simulations

The study explores an Ethereum blockchain-based data-sharing system for a computer assembly simulation game, emphasizing the relationship between gas limits and transaction speeds. The research integrates smart contracts for secure data storage of scores and player profiles. A significant challenge identified was the complexity of blockchain's variable transaction speeds for the average user. The research investigated how different gas limits affected transaction times, with experiments conducted across three networks. Results show that a gas limit of 200,000 to 300,000 resulted in transaction speeds of approximately 30 seconds. Increasing the gas limit to 400,000 to 500,000 reduced transaction times to 15-30 seconds, while a limit of 600,000 to 700,000 led to speeds below 15 seconds. These findings suggest a direct correlation between higher gas limits and quicker transaction validations. The research concludes that investing in higher gas can significantly reduce transaction times, presenting a trade-off between cost and speed in blockchain data-sharing for educational simulation media

Scalable and Socially Inspired Blockchain Architecture for the Organic Food Supply Chain

Organic food supply chains are faced with heavy pressure to increase their output to meet the global demand. This confronts various challenges including scandals, adulteration, contamination, and growing regulations. As an alternative to third-party certification, Participatory Guarantee Systems (PGS) are popular community-based quality assurance system that integrates the social verification context into the organic certification process. As PGS is a local community-driven system, it has inherent limitations in the scalability of reaching consensus as the size of participants increases. The organic food industry has the potential to grow globally therefore, an appropriate scalable consensus mechanism is needed to deal with community-level consensus as an alternative to the existing PGS system. Blockchain architecture with hybrid consensus mechanisms seems to be the potential solution to address the trust and scalability issues in the organic food supply chain. This paper proposes a socially inspired hybrid blockchain architecture for the organic food supply chain to address the scalability issues via hybridizing two consensuses’ mechanisms with the combined advantages of Proof of Authority (PoA) and Federated Byzantine Agreement (FBA). In the proposed architecture, much eminent aspect of community-level trust is integrated into the consensus process. Furthermore, this paper presents a concept-level validation as a qualitative analysis of the proposed architecture based on experts’ opinions. Concept-level validation of the proposed model acknowledged that, in the context of social verification, the credibility of the organic products would be enhanced, and hybridization of the consensuses would mitigate the scalability issues

Data trust framework using blockchain and smart contracts

Lack of trust is the main barrier preventing more widespread data sharing. The lack of transparent and reliable infrastructure for data sharing prevents many data owners from sharing their data. Data trust is a paradigm that facilitates data sharing by forcing data controllers to be transparent about the process of sharing and reusing data. Blockchain technology has the potential to present the essential properties for creating a practical and secure data trust framework by transforming current auditing practices and automatic enforcement of smart contracts logic without relying on intermediaries to establish trust. Blockchain holds an enormous potential to remove the barriers of traditional centralized applications and propose a distributed and transparent administration by employing the involved parties to maintain consensus on the ledger. Furthermore, smart contracts are a programmable component that provides blockchain with more flexible and powerful capabilities. Recent advances in blockchain platforms toward smart contracts' development have revealed the possibility of implementing blockchain-based applications in various domains, such as health care, supply chain and digital identity. This dissertation investigates the blockchain's potential to present a framework for data trust. It starts with a comprehensive study of smart contracts as the main component of blockchain for developing decentralized data trust. Interrelated, three decentralized applications that address data sharing and access control problems in various fields, including healthcare data sharing, business process, and physical access control system, have been developed and examined. In addition, a general-purpose application based on an attribute-based access control model is proposed that can provide trusted auditability required for data sharing and access control systems and, ultimately, a data trust framework. Besides auditing, the system presents a transparency level that both access requesters (data users) and resource owners (data controllers) can benefit from. The proposed solutions have been validated through a use case of independent digital libraries. It also provides a detailed performance analysis of the system implementation. The performance results have been compared based on different consensus mechanisms and databases, indicating the system's high throughput and low latency. Finally, this dissertation presents an end-to-end data trust framework based on blockchain technology. The proposed framework promotes data trustworthiness by assessing input datasets, effectively managing access control, and presenting data provenance and activity monitoring. A trust assessment model that examines the trustworthiness of input data sets and calculates the trust value is presented. The number of transaction validators is defined adaptively with the trust value. This research provides solutions for both data owners and data users’ by ensuring the trustworthiness and quality of the data at origin and transparent and secure usage of the data at the end. A comprehensive experimental study indicates the presented system effectively handles a large number of transactions with low latency

Diseño y desarrollo de una arquitectura de Internet de las Cosas de nueva generación orientada al cálculo y predicción de índices compuestos aplicada en entornos reales

[ES] El Internet de las Cosas (IoT) ha experimentado un gran crecimiento en los últimos años. El incremento en el número de dispositivos, una mayor miniaturización de la capacidad de computación y las técnicas de virtualización, han favorecido su adopción en la industria y en otros sectores. Asimismo, la introducción de nuevas tecnologías (como la Inteligencia Artificial, el 5G, el Tactile Internet o la Realidad Aumentada) y el auge del edge computing preparan el terreno, y formulan los requisitos, para lo que se conoce como Internet de las Cosas de Nueva Generación (NGIoT). Estos avances plantean nuevos desafíos tales como el establecimiento de arquitecturas que cubran dichas necesidades y a la vez resulten flexibles, escalables y prácticas para implementar servicios que aporten valor a la sociedad. En este sentido, el IoT puede resultar un elemento clave para el establecimiento de políticas y la toma de decisiones. Una herramienta muy útil para ello es la definición y cálculo de indicadores compuestos, que representan un impacto en un fenómeno real a través de un único valor. La generación de estos indicadores es un aspecto promovido por entidades oficiales como la Unión Europea, aunque su automatización y uso en entornos de tiempo real es un campo poco explorado. Este tipo de índices deben seguir una serie de operaciones matemáticas y formalidades (normalización, ponderación, agregación¿) para ser considerados válidos. Esta tesis doctoral plantea la unión de ambos campos en alza, proponiendo una arquitectura de Internet de las Cosas de nueva generación orientada al servicio de cálculo y predicción de indicadores compuestos. Partiendo de la experiencia del candidato en proyectos de investigación europeos y regionales, y construyendo sobre tecnologías open source, se ha incluido el diseño, desarrollo e integración de los módulos de dicha arquitectura (adquisición de datos, procesamiento, visualización y seguridad) como parte de la tesis. Dichos planteamientos e implementaciones se han validado en cinco escenarios diferentes, cubriendo cinco índices compuestos en entornos con requisitos dispares siguiendo una metodología diseñada durante este trabajo. Los casos de uso están centrados en aspectos de sostenibilidad en entornos urbano y marítimo-portuario, pero se ha destacado que la solución puede ser extrapolada a otros sectores ya que ha sido diseñada de una manera agnóstica. El resultado de la tesis ha sido, además, analizado desde el punto de vista de transferencia tecnológica. Se ha propuesto la formulación de un producto, así como una posible financiación en fases de madurez más avanzadas y su potencial explotación como elemento comercializable[CA] La Internet de les Coses (IoT) ha experimentat un gran creixement en els últims anys. L'increment en el nombre de dispositius, una major miniaturització de la capacitat de computació i les tècniques de virtualització, han afavorit la seua adopció en la indústria i en altres sectors. Així mateix, la introducció de noves tecnologies (com la Intel·ligència Artificial, el 5G, la Internet Tàctil o la Realitat Augmentada) i l'auge del edge computing preparen el terreny, i formulen els requisits, per al que es coneix com a Internet de les Coses de Nova Generació (NGIoT). Aquests avanços plantegen nous desafiaments com ara l'establiment d'arquitectures que cobrisquen aquestes necessitats i resulten, alhora, flexibles, escalables i pràctiques per a implementar serveis que aporten valor a la societat. Ací, el IoT pot resultar un element clau per a l'establiment de polítiques i la presa de decisions. Una eina molt útil en aquest sentit és la definició i càlcul d'indicadors compostos, que representen un impacte en un fenomen real a través d'un únic valor. La generació d'aquests indicadors és un aspecte promogut per entitats oficials com la Unió Europea, encara que la seua automatització i ús en entorns de temps real és un camp poc explorat. Aquest tipus d'índexs han de seguir una sèrie d'operacions matemàtiques i formalitats (normalització, ponderació, agregació¿) per a ser considerats vàlids. Aquesta tesi doctoral planteja la unió de tots dos camps en alça, proposant una arquitectura d'Internet de les Coses de nova generació orientada al servei de càlcul i predicció d'indicadors compostos. Partint de l'experiència del candidat en projectes d'investigació europeus i regionals, i construint sobre tecnologies open source, s'ha inclòs el disseny, desenvolupament i integració dels mòduls d'aquesta arquitectura (adquisició de dades, processament, visualització i seguretat) com a part de la tesi. Aquests plantejaments i implementacions s'han validat en cinc escenaris diferents, cobrint cinc índexs compostos en entorns amb requisits dispars seguint una metodologia dissenyada durant aquest treball. Els casos d'ús estan centrats en aspectes de sostenibilitat en entorns urbà i marítim-portuari, però s'ha destacat que la solució pot ser extrapolada a altres sectors ja que ha sigut dissenyada d'una manera agnòstica. El resultat de la tesi ha sigut, a més, analitzat des del punt de vista de transferència tecnològica. S'ha proposat la formulació d'un producte, així com un possible finançament en fases de maduresa més avançades i la seua potencial explotació com a element comercialitzable[EN] The Internet of Things (IoT) has experienced tremendous growth in recent years. The increase in the number of devices, greater miniaturization of computing capacity and virtualization techniques have favored its adoption in industry and other sectors. Likewise, the introduction of new technologies (such as Artificial Intelligence, 5G, Tactile Internet or Augmented Reality), together with the rise of edge computing, are paving the way, and formulating the requirements, for what is known as the Next Generation Internet of Things (NGIoT). These advances pose new challenges such as the establishment of proper architectures that meet those needs and, at the same time, are flexible, scalable, and practical for implementing services that bring value to society. In this sense, IoT could be a key element for policy and decision making. A very useful tool for this is the definition and calculation of composite indicators, which represent an impact on a real phenomenon through a single value. The generation of these indicators is an aspect promoted by official entities such as the European Union, although their automation and use in real-time environments is a rather uncharted research field. This type of indexes must follow a series of mathematical operations and formalities (normalization, weighting, aggregation...) to be considered valid. This doctoral thesis proposes the union of both fields, proposing a new generation Internet of Things architecture oriented to the calculation and prediction of composite indicators. Based on the candidate's experience in European and regional research projects, and building on open source technologies, the design, development and integration of the modules of such architecture (data acquisition, processing, visualization and security) has been included as part of the thesis. These approaches and implementations have been validated in five different scenarios, covering five composite indexes in environments with disparate requirements following a methodology designed during this work. The use cases are focused on sustainability aspects in urban and maritime-port environments, but it has been highlighted that the solution can be extrapolated to other sectors as it has been designed in an agnostic way. The result of the thesis has also been analyzed from the point of view of technology transfer. A tentative product definition has been formulated, as well as a possible financing in more advanced stages of maturity and its potential exploitation as a marketable elementLacalle Úbeda, I. (2022). Diseño y desarrollo de una arquitectura de Internet de las Cosas de Nueva Generación orientada al cálculo y predicción de índices compuestos aplicada en entornos reales [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19063