---
_id: '66548'
abstract:
- lang: eng
text: "The Circular Economy is considered a key approach to addressing resource
scarcity, rising raw material prices, and the need for more resilient value chains.
However, its practical implementation is often hindered by the lack of suitable
and standardized metrics, as well as by high requirements for horizontal and vertical
data integration. This white paper illustrates, through selected Manufacturing-X
projects, how federated data ecosystems can help establish Circular Economy metrics
as an effective management instrument for growth, margin protection, and resilience.\r\nBased
on literature, industrial practice, and demonstrators, Circular Economy metrics
are structured into four groups: overarching assessment approaches, disassembly-related
indicators, lifetime-oriented metrics, and end-of-life and recycling-focused indicators.
Use cases from Construct-X, Decide4ECO, Fluid 4.0, Chem-X, and other Manufacturing-X
initiatives demonstrate the benefits of data-driven approaches for product, component,
and material loops. At the same time, they reveal a current lack of interoperable,
cross-industry standards for both metrics and data models.\r\nThe white paper
concludes that data ecosystems such as Manufacturing-X are a key enabler for scaling
circular business models. In particular, shared cross-sector frameworks for metrics,
standardized information models based for example on the Asset Administration
Shell, and the integration of circular metrics into existing systems and processes
are essential. The work presented therefore marks an important step toward a data-driven
and economically viable Circular Economy."
author:
- first_name: Jens
full_name: Pottebaum, Jens
id: '405'
last_name: Pottebaum
orcid: http://orcid.org/0000-0001-8778-2989
- first_name: Katrin
full_name: Dietrich, Katrin
last_name: Dietrich
- first_name: Lara
full_name: Schmidt, Lara
last_name: Schmidt
- first_name: Mostafa
full_name: Biglari, Mostafa
last_name: Biglari
- first_name: Michael-Georg
full_name: Schmidt, Michael-Georg
last_name: Schmidt
- first_name: Alessandro
full_name: Pistillo, Alessandro
last_name: Pistillo
- first_name: Nadja
full_name: Gravina, Nadja
last_name: Gravina
- first_name: Franziska
full_name: Schmidt, Franziska
last_name: Schmidt
citation:
ama: Pottebaum J, Dietrich K, Schmidt L, et al. Understanding the Value of Data
Ecosystems for Circular Economy Metrics. Manufacturing-X Guidance Board; 2026.
doi:10.24406/PUBLICA-9382
apa: Pottebaum, J., Dietrich, K., Schmidt, L., Biglari, M., Schmidt, M.-G., Pistillo,
A., Gravina, N., & Schmidt, F. (2026). Understanding the Value of Data
Ecosystems for Circular Economy Metrics. Manufacturing-X Guidance Board. https://doi.org/10.24406/PUBLICA-9382
bibtex: '@book{Pottebaum_Dietrich_Schmidt_Biglari_Schmidt_Pistillo_Gravina_Schmidt_2026,
place={Berlin}, title={Understanding the Value of Data Ecosystems for Circular
Economy Metrics}, DOI={10.24406/PUBLICA-9382},
publisher={Manufacturing-X Guidance Board}, author={Pottebaum, Jens and Dietrich,
Katrin and Schmidt, Lara and Biglari, Mostafa and Schmidt, Michael-Georg and Pistillo,
Alessandro and Gravina, Nadja and Schmidt, Franziska}, year={2026} }'
chicago: 'Pottebaum, Jens, Katrin Dietrich, Lara Schmidt, Mostafa Biglari, Michael-Georg
Schmidt, Alessandro Pistillo, Nadja Gravina, and Franziska Schmidt. Understanding
the Value of Data Ecosystems for Circular Economy Metrics. Berlin: Manufacturing-X
Guidance Board, 2026. https://doi.org/10.24406/PUBLICA-9382.'
ieee: 'J. Pottebaum et al., Understanding the Value of Data Ecosystems
for Circular Economy Metrics. Berlin: Manufacturing-X Guidance Board, 2026.'
mla: Pottebaum, Jens, et al. Understanding the Value of Data Ecosystems for Circular
Economy Metrics. Manufacturing-X Guidance Board, 2026, doi:10.24406/PUBLICA-9382.
short: J. Pottebaum, K. Dietrich, L. Schmidt, M. Biglari, M.-G. Schmidt, A. Pistillo,
N. Gravina, F. Schmidt, Understanding the Value of Data Ecosystems for Circular
Economy Metrics, Manufacturing-X Guidance Board, Berlin, 2026.
date_created: 2026-07-20T19:06:41Z
date_updated: 2026-07-20T19:13:06Z
department:
- _id: '152'
doi: 10.24406/PUBLICA-9382
has_accepted_license: '1'
keyword:
- Circular Economy
- Circular Economy Metrics
- Manufacturing-X
- Data Ecosystems
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
place: Berlin
publication_status: published
publisher: Manufacturing-X Guidance Board
status: public
title: Understanding the Value of Data Ecosystems for Circular Economy Metrics
type: report
user_id: '405'
year: '2026'
...
---
_id: '66072'
abstract:
- lang: eng
text: Data Spaces are establishing themselves as a decentralized alternative for
sovereign data sharing across organizations. However, their adoption faces significant
challenges, particularly the lack of proven business models that encourage participation
and value creation. A data space business model captures value differently than
either traditional business models or platform business models. This paper addresses
this challenge by developing the Data Space Canvas, a structured framework for
designing and aligning business models in data spaces consisting of nine building
blocks. The canvas was developed following the design science research methodology.
The modular and role-specific structure of the Data Space Canvas facilitates shared
understanding and supports business model development across participants. This
research contributes a practical tool that enables organizations to conceptualize,
communicate, and refine their role and business model in data spaces.
author:
- first_name: Julian
full_name: Zerbin, Julian
id: '51711'
last_name: Zerbin
orcid: 0009-0001-1003-7558
- first_name: Christian
full_name: Koldewey, Christian
id: '43136'
last_name: Koldewey
orcid: https://orcid.org/0000-0001-7992-6399
- first_name: Roman
full_name: Dumitrescu, Roman
id: '16190'
last_name: Dumitrescu
citation:
ama: 'Zerbin J, Koldewey C, Dumitrescu R. The Data Space Canvas: A Framework For
Structuring Business Models In Data Spaces. In: ECIS 2026 Proceedings.
; 2026.'
apa: 'Zerbin, J., Koldewey, C., & Dumitrescu, R. (2026). The Data Space Canvas:
A Framework For Structuring Business Models In Data Spaces. ECIS 2026 Proceedings.
The 34th European Conference on Information System (ECIS), Mailand.'
bibtex: '@inproceedings{Zerbin_Koldewey_Dumitrescu_2026, title={The Data Space Canvas:
A Framework For Structuring Business Models In Data Spaces}, booktitle={ECIS 2026
Proceedings}, author={Zerbin, Julian and Koldewey, Christian and Dumitrescu, Roman},
year={2026} }'
chicago: 'Zerbin, Julian, Christian Koldewey, and Roman Dumitrescu. “The Data Space
Canvas: A Framework For Structuring Business Models In Data Spaces.” In ECIS
2026 Proceedings, 2026.'
ieee: 'J. Zerbin, C. Koldewey, and R. Dumitrescu, “The Data Space Canvas: A Framework
For Structuring Business Models In Data Spaces,” presented at the The 34th European
Conference on Information System (ECIS), Mailand, 2026.'
mla: 'Zerbin, Julian, et al. “The Data Space Canvas: A Framework For Structuring
Business Models In Data Spaces.” ECIS 2026 Proceedings, 2026.'
short: 'J. Zerbin, C. Koldewey, R. Dumitrescu, in: ECIS 2026 Proceedings, 2026.'
conference:
end_date: 2026-06-17
location: Mailand
name: The 34th European Conference on Information System (ECIS)
start_date: 2026-06-14
date_created: 2026-06-29T07:40:42Z
date_updated: 2026-10-13T08:03:06Z
department:
- _id: '563'
keyword:
- data ecosystems
- business model
- design science
- resource orchestration theory
- data sharing
language:
- iso: eng
main_file_link:
- url: 'https://aisel.aisnet.org/ecis2026/datasc_isresearch/datasc_isresearch/4 '
publication: ECIS 2026 Proceedings
publication_status: published
quality_controlled: '1'
status: public
title: 'The Data Space Canvas: A Framework For Structuring Business Models In Data
Spaces'
type: conference
user_id: '51711'
year: '2026'
...