TY - GEN
T1 - Digital Infrastructures for Compliance Monitoring of Circular Economy
T2 - Requirements for Interoperable Data Spaces
AU - Hofman, Wout
AU - Rukanova, B.D.
AU - Tan, Y.
AU - Bharosa, Nitesh
AU - Ubacht, J.
AU - Rietveld, Elmer
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2024
Y1 - 2024
N2 - The transition towards a circular economy (CE) will require data sharing across different platforms and data spaces of parties operating in a variety of supply chains. From a circular economy compliance monitoring perspective, beyond the access to mandatory data that governments will receive, authorities may benefit from accessing additional business data from the source on a voluntary basis, which is challenging. While platforms and data spaces solve a great deal of complexity and interoperability within their realm, platform, and data space interoperability is still challenging. In the logistics domain, efforts have been made to overcome these issues of data sharing across logistics platforms with a Semantic data sharing architecture developed by the CEF FEDeRATED Action, at the heart of which is a semantic model aligning other semantic models for logistics. In this paper, we take the Semantic data sharing architecture as a point of departure and examine the opportunities and limitations that it has for CE monitoring, and how it relates to other developments in the EU and beyond. Many of these developments acknowledge the need for data access across heterogeneous systems and – processes of actors; others add security and trust to data sharing that goes all the way to the level to cover legal obligations. The goal of this paper is to gain further insights into how data sharing across multiple platforms and data spaces enables circular economy monitoring, where government organizations would need to address the issue of how they would interface with, and access data that resides in multiple platforms and data spaces. We found that the various models can be aligned on some architecture principles that promote interoperability across dimensions (e.g. federation, keeping data at the source), yet they still differ on other dimensions (e.g. data model and semantics, as well as how they address issues of identification, authentication and authorization). We suggest further efforts towards developing meta-level agreements and standardization for data space interoperability and we propose further research directions on that topic.
AB - The transition towards a circular economy (CE) will require data sharing across different platforms and data spaces of parties operating in a variety of supply chains. From a circular economy compliance monitoring perspective, beyond the access to mandatory data that governments will receive, authorities may benefit from accessing additional business data from the source on a voluntary basis, which is challenging. While platforms and data spaces solve a great deal of complexity and interoperability within their realm, platform, and data space interoperability is still challenging. In the logistics domain, efforts have been made to overcome these issues of data sharing across logistics platforms with a Semantic data sharing architecture developed by the CEF FEDeRATED Action, at the heart of which is a semantic model aligning other semantic models for logistics. In this paper, we take the Semantic data sharing architecture as a point of departure and examine the opportunities and limitations that it has for CE monitoring, and how it relates to other developments in the EU and beyond. Many of these developments acknowledge the need for data access across heterogeneous systems and – processes of actors; others add security and trust to data sharing that goes all the way to the level to cover legal obligations. The goal of this paper is to gain further insights into how data sharing across multiple platforms and data spaces enables circular economy monitoring, where government organizations would need to address the issue of how they would interface with, and access data that resides in multiple platforms and data spaces. We found that the various models can be aligned on some architecture principles that promote interoperability across dimensions (e.g. federation, keeping data at the source), yet they still differ on other dimensions (e.g. data model and semantics, as well as how they address issues of identification, authentication and authorization). We suggest further efforts towards developing meta-level agreements and standardization for data space interoperability and we propose further research directions on that topic.
KW - Data spaces
KW - Platforms
KW - Interoperability
KW - Circular economy
KW - Monitoring
KW - Government
UR - http://www.scopus.com/inward/record.url?scp=85189311611&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-54053-0_24
DO - 10.1007/978-3-031-54053-0_24
M3 - Conference contribution
SN - 978-3-031-54052-3
T3 - Lecture Notes in Networks and Systems (LNNS)
SP - 332
EP - 351
BT - Advances in Information and Communication - Proceedings of the 2024 Future of Information and Communication Conference FICC
A2 - Arai, Kohei
PB - Springer
ER -