Abstract
Trusted open data can be used for auditing, accountability, business development, or as an anti-corruption mechanism. Metadata information can address provenance concerns, and trust issues can somehow be mitigated by digital signatures. Those approaches can trace the data origin, but usually lack information about the transformation process. Creating trust in an open data service through technology can reduce the need for third-party certifications, and creating a distributed consensus mechanism capable of validating all the transformations can guarantee that the datasets are reliable and easy to use. This work aims to leverage blockchain technologies to track open data transformations, allowing consumers to verify the data using a distributed ledger, and providing a mechanism capable of publishing trusted transformed data without relying on third-party certifications. To validate the proposed approach, use cases for data transformation will be used. The consensus protocol must be capable of validating the transformations according to a predefined algorithm, the provider must be capable of publishing verifiable transformed data, and the consumer should be able to check if a dataset originated by a transformation is legit.
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Tavares, B., Correia, F.F., Restivo, A. (2020). Trusted Data Transformation with Blockchain Technology in Open Data. In: Herrera-Viedma, E., Vale, Z., Nielsen, P., Martin Del Rey, A., Casado Vara , R. (eds) Distributed Computing and Artificial Intelligence, 16th International Conference, Special Sessions. DCAI 2019. Advances in Intelligent Systems and Computing, vol 1004. Springer, Cham. https://doi.org/10.1007/978-3-030-23946-6_28
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DOI: https://doi.org/10.1007/978-3-030-23946-6_28
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