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Ruben Verborgh

Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid

Jonni Hanski, Pieter Heyvaert, Ben De Meester, Ruben Taelman, and Ruben Verborgh

When interacting with government institutions, citizens may often be asked to provide a number of documents to various officials, due to the way the data is being processed by the government, and regulation or guidelines that restrict sharing of that data between institutions. Occasionally, documents from third parties, such as the private sector, are involved, as the data, rules, regulations and individual private data may be controlled by different parties. Facilitating efficient flow of information in such cases is therefore important, while still respecting the ownership and privacy of that data. Addressing these types of use cases in data storage and sharing, the Solid initiative allows individuals, organisations and the public sector to store their data in personal online datastores. Solid has been previously applied in data storage within government contexts, so we decided to extend that work by adding data processing services on top of such data and including multiple parties such as citizen and the private sector. However, introducing multiple parties within the data processing flow may impose new challenges, and implementing such data processing services in practice on top of Solid might present opportunities for improvement from the perspective of the implementer of the services. Within this work, together with the City of Antwerp in Belgium, we have produced a proof-of-concept service implementation operating at the described intersection of public sector, citizens and private sector, to manage social benefit allocation in a distributed environment. The service operates on distributed Linked Data stored in multiple Solid pods in RDF, using Notation3 rules to process that data and SPARQL queries to access and modify it. This way, our implementation seeks to respect the design principles of Solid, while taking advantage of the related technologies for representing, processing and modifying Linked Data. This document will describe our chosen use case, service design and implementation, and our observations resulting from this experiment. Through the proof-of-concept implementation, we have established a preliminary understanding of the current challenges in implementing such a service using the chosen technologies. We have identified topics such as verification of data that should be addressed when using such an approach in practice, assumptions related to data locations and tight coupling between our logic between the rules and program code. Addressing these topics in future work should help further the adoption of Linked Data as a means to solve challenges around data sharing, processing and ownership such as with government processes involving multiple parties.

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Published in 2023 in Joint Proceedings of ESWC 2023 Workshops and Tutorials.

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@inproceedings{hanski_dmkg_2023,
  author = {Hanski, Jonni and Heyvaert, Pieter and De Meester, Ben and Taelman, Ruben and Verborgh, Ruben},
  title = {Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid},
  booktitle = {Joint Proceedings of ESWC 2023 Workshops and Tutorials},
  editor = {Alam, Mehwish and Trojahn, Cassia and Hertling, Sven and Pesquita, Catia and Aebeloe, Christian and Aras, Hidir and Azzam, Amr and Cano, Juan and Domingue, John and Gottschalk, Simon and Hartig, Olaf and Hose, Katja and Kirrane, Sabrina and Lisena, Pasquale and Osborne, Francesco and Rohde, Philipp and Steels, Luc and Taelman, Ruben and Third, Aisling and Tiddi, Ilaria and T\"urker, Rima},
  year = 2023,
  month = may,
  series = {CEUR Workshop Proceedings},
  volume = 3443,
  issn = {1613-0073},
  url = {https://ceur-ws.org/Vol-3443/ESWC_2023_DMKG_paper_2204.pdf},
}

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ACM
Jonni Hanski, Pieter Heyvaert, Ben De Meester, Ruben Taelman, and Ruben Verborgh. 2023. Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid. In Joint Proceedings of ESWC 2023 Workshops and Tutorials (CEUR Workshop Proceedings).
APA
Hanski, J., Heyvaert, P., De Meester, B., Taelman, R., & Verborgh, R. (2023). Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid. In M. Alam, C. Trojahn, S. Hertling, C. Pesquita, C. Aebeloe, H. Aras, A. Azzam, J. Cano, J. Domingue, S. Gottschalk, O. Hartig, K. Hose, S. Kirrane, P. Lisena, F. Osborne, P. Rohde, L. Steels, R. Taelman, A. Third, … R. Türker (Eds.), Joint Proceedings of ESWC 2023 Workshops and Tutorials (Vol. 3443).
IEEE
J. Hanski, P. Heyvaert, B. De Meester, R. Taelman, and R. Verborgh, “Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid,” in Joint Proceedings of ESWC 2023 Workshops and Tutorials, 2023, vol. 3443.
LNCS
Hanski, J., Heyvaert, P., De Meester, B., Taelman, R., Verborgh, R.: Distributed Social Benefit Allocation using Reasoning over Personal Data in Solid. In: Alam, M., Trojahn, C., Hertling, S., Pesquita, C., Aebeloe, C., Aras, H., Azzam, A., Cano, J., Domingue, J., Gottschalk, S., Hartig, O., Hose, K., Kirrane, S., Lisena, P., Osborne, F., Rohde, P., Steels, L., Taelman, R., Third, A., Tiddi, I., and Türker, R. (eds.) Joint Proceedings of ESWC 2023 Workshops and Tutorials (2023).
MLA
Hanski, Jonni, et al. “Distributed Social Benefit Allocation Using Reasoning over Personal Data in Solid.” Joint Proceedings of ESWC 2023 Workshops and Tutorials, edited by Mehwish Alam et al., vol. 3443, 2023.

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