A Decentralized Provenance Network for Linked Open Data

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Datum
2019
Herausgeber:innen
Qiao, Miao
Dragoni, Mauro
Autor:innen
Kirstein, Fabian
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With the growing availability of Linked Open Data (LOD) and the consequential generation of derived and aggregated data, the need for trustworthy, reproducible and accessible provenance informa- tion has increased. Yet, no consistent mechanism has been established to manage provenance data of LOD on a global dataset-level. Decentralized networks and peer-to-peer mechanisms have made their revival in the last years with blockchain and similar distributed ledger technologies. We propose a novel approach to track and store provenance information for LOD on a dataset-level by sharing an immutable, common state between data providers. The basic architecture will not disrupt existing methodologies and standards for publishing LOD, but will be transparently integrated into existing ecosystems as an additional layer to foster broad acceptance. We will investigate the application of emerging blockchain technologies and established Linked Data specifications for building this decentralized anchor of truth. We are actively involved in the design and implementation of LOD and Open Data platforms and will evaluate our approach in real-world scenarios regarding feasibility, governance, scalability and usability.

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Kirsten, F. (2019). A Decentralized Provenance Network for Linked Open Data. In M. Qiao & M. Dragoni (Hrsg.), Proceedings of the Doctoral Consortium at ISWC 2019. https://ceur-ws.org/Vol-2548/paper-10.pdf