The widespread use of machine learning techniques and artificial intelligence algorithms has highlighted the strategic role of data.To acquire data for training algorithms and eventually empowering the digital transfo...The widespread use of machine learning techniques and artificial intelligence algorithms has highlighted the strategic role of data.To acquire data for training algorithms and eventually empowering the digital transformation,data marketplaces are often required to support and coordinate cross-organizational data transactions.However,the prior industry practices have suggested that the transaction costs in the data marketplaces are severely high,and the supporting infrastructure is far from mature.This paper proposes a data attributes-affected data exchange(DADE)conceptual model to understand the challenges and directions for developing data marketplaces.Specifically,our model framework is built upon two dimensions,data lifecycle maturity and data asset specificity.Based on the DADE model,we propose four approaches for developing data marketplaces and discuss future research directions with an overview of computational methods as potential technical solutions.展开更多
These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling data.However,online data trading poses challenges in terms of security and fairnes...These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling data.However,online data trading poses challenges in terms of security and fairness because the seller and the buyer may not fully trust each other.Therefore,in this paper,a blockchain-based secure and fair data trading system is proposed by taking advantage of the smart contract and matchmaking encryption.The proposed system enables bilateral authorization,where data trading between a seller and a buyer is accomplished only if their policies,required by each other,are satisfied simultaneously.This can be achieved by exploiting the security features of the matchmaking encryption.To guarantee non-repudiation and fairness between trading parties,the proposed system leverages a smart contract to ensure that the parties honestly carry out the data trading protocol.However,the smart contract in the proposed system does not include complex cryptographic operations for the efficiency of onchain processes.Instead,these operations are carried out by off-chain parties and their results are used as input for the on-chain procedure.The system also uses an arbitration protocol to resolve disputes based on the trading proof recorded on the blockchain.The performance of the protocol is evaluated in terms of off-chain computation overhead and on-chain gas consumption.The results of the experiments demonstrate that the proposed protocols can enable the implementation of a cost-effective data trading system.展开更多
Actual challenges with data in physical infrastructure include:1)the adversity of its velocity based on access and retrieval,thus integration;2)its value as its intrinsic quality;3)its extensive volume with a limited ...Actual challenges with data in physical infrastructure include:1)the adversity of its velocity based on access and retrieval,thus integration;2)its value as its intrinsic quality;3)its extensive volume with a limited variety in terms of systems;and finally,4)its veracity,as data can be modified to obtain an economical advantage.Physical infrastructure design based on Agile project management and minimum viable products provides benefits against the traditional waterfall method.Agile supports an early return on investment that promotes circular reinvesting while making the product more adaptable to variable social-economical environments.However,Agile also presents inherent issues due to its iterative approach.Furthermore,project information requires an efficient record of the aims,requirements,and governance not only for the investors,owners,or users but also to keep evidence in future health&safety and other statutory compliance.In order to address these issues,this article presents a Validation and Verification(V&V)model for data marketplaces with a hierarchical process;each data V&V stage provides a layer of data abstraction,value-added services,and authenticity based on Artificial Intelligence(AI).In addition,this proposed solution applies Distributed Ledger Technology(DLT)for a decentralised approach where each user keeps and maintains the data within a ledger.The presented model is validated in real data marketplace applications:1)live data for the Newcastle Urban Observatory Smart City Project,where data are collected from sensors embedded within the smart city via APIs;2)static data for University College London(UCL)—Real Estate—PEARL Project,where different project users and stakeholders introduce data into a Project Information Model(PIM).展开更多
This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech co...This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech companies into healthcare,the second will be the monetization of consumer data and the creation of health data marketplaces;and the third will be the growth of Asia as a leader in digital health.Big tech already has the advantage of a massive consiuner base,data and analytics which enable them to understand consumers;and complementary technologies,like wearables,that will drive the consumerization of healthcare.This expansion can happen quickly and already is creating challenges for regulators as they try to catch up.The vast volumes of data and the ability of technology such as blockchain to enable data owners to monetize their data,will lead to the development of health data marketplaces,which can connect and monetize data for data owners and make it available for scientific discovery.The developments in self-sovereign identity,will make it possible for individuals to monetize their health data in the future.Finally,we see the emergence of Asia as a powerhouse for the digital health of the future,with vast populations,mobile technology and increasing adoption of wearable devices.Consumer focused health care driven by data will change the institutional models of the past.展开更多
基金support from the National Natural Science Foundations of China(NSFC)[Grants No.91746302 and 71822201]National Engineering Laboratory for Big Data Distribution and Exchange Technologies.
文摘The widespread use of machine learning techniques and artificial intelligence algorithms has highlighted the strategic role of data.To acquire data for training algorithms and eventually empowering the digital transformation,data marketplaces are often required to support and coordinate cross-organizational data transactions.However,the prior industry practices have suggested that the transaction costs in the data marketplaces are severely high,and the supporting infrastructure is far from mature.This paper proposes a data attributes-affected data exchange(DADE)conceptual model to understand the challenges and directions for developing data marketplaces.Specifically,our model framework is built upon two dimensions,data lifecycle maturity and data asset specificity.Based on the DADE model,we propose four approaches for developing data marketplaces and discuss future research directions with an overview of computational methods as potential technical solutions.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2022R1I1A3063257)supported by Electronics and Telecommunications Research Institute(ETRI)grant funded by the Korean Government[22ZR1300,Research on Intelligent Cyber Security and Trust Infra].
文摘These days,data is regarded as a valuable asset in the era of the data economy,which demands a trading platform for buying and selling data.However,online data trading poses challenges in terms of security and fairness because the seller and the buyer may not fully trust each other.Therefore,in this paper,a blockchain-based secure and fair data trading system is proposed by taking advantage of the smart contract and matchmaking encryption.The proposed system enables bilateral authorization,where data trading between a seller and a buyer is accomplished only if their policies,required by each other,are satisfied simultaneously.This can be achieved by exploiting the security features of the matchmaking encryption.To guarantee non-repudiation and fairness between trading parties,the proposed system leverages a smart contract to ensure that the parties honestly carry out the data trading protocol.However,the smart contract in the proposed system does not include complex cryptographic operations for the efficiency of onchain processes.Instead,these operations are carried out by off-chain parties and their results are used as input for the on-chain procedure.The system also uses an arbitration protocol to resolve disputes based on the trading proof recorded on the blockchain.The performance of the protocol is evaluated in terms of off-chain computation overhead and on-chain gas consumption.The results of the experiments demonstrate that the proposed protocols can enable the implementation of a cost-effective data trading system.
文摘Actual challenges with data in physical infrastructure include:1)the adversity of its velocity based on access and retrieval,thus integration;2)its value as its intrinsic quality;3)its extensive volume with a limited variety in terms of systems;and finally,4)its veracity,as data can be modified to obtain an economical advantage.Physical infrastructure design based on Agile project management and minimum viable products provides benefits against the traditional waterfall method.Agile supports an early return on investment that promotes circular reinvesting while making the product more adaptable to variable social-economical environments.However,Agile also presents inherent issues due to its iterative approach.Furthermore,project information requires an efficient record of the aims,requirements,and governance not only for the investors,owners,or users but also to keep evidence in future health&safety and other statutory compliance.In order to address these issues,this article presents a Validation and Verification(V&V)model for data marketplaces with a hierarchical process;each data V&V stage provides a layer of data abstraction,value-added services,and authenticity based on Artificial Intelligence(AI).In addition,this proposed solution applies Distributed Ledger Technology(DLT)for a decentralised approach where each user keeps and maintains the data within a ledger.The presented model is validated in real data marketplace applications:1)live data for the Newcastle Urban Observatory Smart City Project,where data are collected from sensors embedded within the smart city via APIs;2)static data for University College London(UCL)—Real Estate—PEARL Project,where different project users and stakeholders introduce data into a Project Information Model(PIM).
文摘This commentary shows the exponential growth of digital health and the accompanying explosion of health data.It discusses three major shifts in the global health landscape.The first will be the move of the big tech companies into healthcare,the second will be the monetization of consumer data and the creation of health data marketplaces;and the third will be the growth of Asia as a leader in digital health.Big tech already has the advantage of a massive consiuner base,data and analytics which enable them to understand consumers;and complementary technologies,like wearables,that will drive the consumerization of healthcare.This expansion can happen quickly and already is creating challenges for regulators as they try to catch up.The vast volumes of data and the ability of technology such as blockchain to enable data owners to monetize their data,will lead to the development of health data marketplaces,which can connect and monetize data for data owners and make it available for scientific discovery.The developments in self-sovereign identity,will make it possible for individuals to monetize their health data in the future.Finally,we see the emergence of Asia as a powerhouse for the digital health of the future,with vast populations,mobile technology and increasing adoption of wearable devices.Consumer focused health care driven by data will change the institutional models of the past.
