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Towards a Decentralized Infrastructure for Data Marketplaces: Narrowing the Gap between Academia and Industry
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-0223-8907
Foundation for Research and Technology Hellas, Heraklion, Greece.
Foundation for Research and Technology Hellas, Heraklion, Greece.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0003-4516-7317
Number of Authors: 42022 (English)In: DE 2022: Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022, Association for Computing Machinery (ACM) , 2022, p. 49-56Conference paper, Published paper (Refereed)
Abstract [en]

One big challenge for Industry 4.0 is leveraging the large amount of data that remain unused after collection. A variety of commercial data marketplaces have emerged in recent years to tackle this task. Despite their different business models and target markets, such marketplaces share a number of common issues that slow the growth of the industry, including data discovery, transparency, data privacy and data valuation. Many academic designs have been proposed to address these issues, yet most of them remain unimplemented, due to complexity or inefficiency. We argue that these issues can be addressed with a combination of blockchain-based infrastructure, privacy-preserving computing and machine learning-based valuation metrics. Furthermore, we discuss key enabling technologies in each of these areas that are feasible to deploy at scale and could thus be implemented in real-world marketplaces in the near future. We select such technologies based on their current maturity and their industrial prominence.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2022. p. 49-56
National Category
Economics and Business Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-333510DOI: 10.1145/3565011.3569060ISI: 001061595500008Scopus ID: 2-s2.0-85144828585OAI: oai:DiVA.org:kth-333510DiVA, id: diva2:1785397
Conference
1st ACM International Workshop on Data Economy, DE 2022, co-located with ACM CoNEXT 2022, Rome, Italy, Dec 9 2022
Note

Part of ISBN 9781450399234

QC 20230802

Available from: 2023-08-02 Created: 2023-08-02 Last updated: 2023-10-09Bibliographically approved

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