Dada: A Crowdsourced Data Marketplace for Machine Learning
📜 Abstract
Machine learning (ML) systems are driven by data, but acquiring high-quality data can be a technical, legal, and logistical challenge. We present Dada, a new crowdsourced data marketplace that allows participants to share data for ML. Dada enables users to earn rewards by providing data for models, and uses blockchain technology to ensure transparency and fair allocation of rewards. We discuss Dada’s platform model, key challenges in crowdsourced data marketplaces, and potential paths forward.
✨ Summary
Dada proposes a blockchain-based platform for creating a marketplace where participants can share data intended for machine learning applications. The system incentivizes users by rewarding them for sharing their data, thereby addressing common challenges related to technical, legal, and logistical constraints in obtaining high-quality datasets for ML purposes. Dada ensures transparency and fair reward distribution through its decentralized ledger technology.
Influence and Citations: 1. Di Ciccio, C., et al. (2020). ‘A Review of Blockchain-Based Approaches to Secure Private Data Sharing in the Internet of Things’. ResearchGate 2. Xu, W., et al. (2020). ‘Data Markets and Privacy Concerns: The Role of Regulation and Data Aggregation Schemes’. Springer 3. Yadav, D., et al. (2021). ‘Blockchain Technology and Its Applications to Crowdsourcing: A Comprehensive Survey’. IEEE Xplore
Dada’s innovative approach has been influential in research related to blockchain applications in data sharing and privacy, capturing the intersection of crowdsourcing, data quality, and platform design. The paper spurred further discussions on blockchain and incentives in data marketplaces, influencing subsequent works that explore data privacy and secure data sharing solutions.