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ViSDM 1.0: Vision Sovereignty Data Marketplace a Decentralized Platform for Crowdsourcing Data Collection and Trading
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0001-6895-4503
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0002-5235-5335
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-4814-4428
Bonseyes Community Association, Switzerland.
2023 (English)In: ACM International Conference Proceeding Series, Association for Computing Machinery (ACM), 2023, p. 374-383Conference paper, Published paper (Refereed)
Abstract [en]

The demand for large-scale diverse datasets is rapidly increasing due to the advancements in AI services impacting day-to-day life. However, gathering such massive datasets still remains a critical challenge in the AI service engineering pipeline, especially in the computer vision domain where labeled data is scarce. Rather than isolated data collection, crowdsourcing techniques have shown promising potential to achieve the data collection task in a time and cost-efficient manner. In the existing crowdsourcing marketplaces, the crowd works to fulfill consumer-defined requirements where in the end consumer gains the data ownership and the crowd is compensated with task-based payment. On the contrary, this work proposes a blockchain-based decentralized marketplace named Vision Sovereignty Data Marketplace (ViSDM), in which the crowd works to fulfill global requirements & holds data ownership, the consumers pay a certain data price to perform a computing task (model training/testing), the data price is distributed among the crowd in a one-to-many manner through smart contracts, thus allowing the crowd to gain profit from each consumer transaction occurring on their data. The marketplace is implemented as multiple smart contracts and is evaluated based on blockchain-transaction gas fees for the stakeholder interaction & by running scenarios-based simulations. Furthermore, discussions address the challenges included in maintaining data quality and the future milestones towards deployment. © 2023 Owner/Author.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2023. p. 374-383
Keywords [en]
Blockchain, Computer Vision, Crowdsourcing, Data Marketplaces, Smart Contracts, Commerce, Data acquisition, Large dataset, Block-chain, Critical challenges, Data collection, Data ownership, Decentralised, Labeled data, Large-scales, Massive data sets, Services engineering, Smart contract
National Category
Information Systems
Identifiers
URN: urn:nbn:se:bth-25507DOI: 10.1145/3582515.3609556Scopus ID: 2-s2.0-85174318507ISBN: 9798400701160 (print)OAI: oai:DiVA.org:bth-25507DiVA, id: diva2:1808441
Conference
3rd ACM Conference on Information Technology for Social Good, GoodIT 2023Lisbon6 September through 8 September 2023
Part of project
HINTS - Human-Centered Intelligent Realities
Funder
Knowledge Foundation, 20220068EU, Horizon 2020, 101015848Available from: 2023-10-31 Created: 2023-10-31 Last updated: 2023-10-31Bibliographically approved

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Daliparthi, Venkata Satya Sai AjayMomen, NurulTutschku, Kurt

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