Data and Data Competencies for a Circular Economy – Data-driven enablement of the digital circular economy

Editors: Mohammad Chehadé¹, Raphaela Kell¹, Samira Khodaei Dolouei¹, Annalisa Nolte², Kathrin Greiff², Zhihong Dou², Ali Nazeri³, Christiane Plociennik³, Mahdi Rezapour³, Abdullah Farrukh³, Anina Kusch⁴, Annika Pruhs⁴, Juliano Araujo⁴, Tobias Viere⁴, Andre Bröcker⁵, Lara Baumanns⁵, Jakob Deich⁵, Tobias Meisen⁵, André Pomp⁵, Holger Berg (Project Lead)⁶, Julia Reinhard⁶, Martin Perau⁶, Helen Brüggmann⁶

¹ Center for Circular Economy (CCE), RWTH Aachen University (Germany)
² Chair of Anthropogenic Material Cycles (ANTS), RWTH Aachen University (Germany)
³ Design of Human-Machine Systems, German Research Center for Artificial Intelligence (DFKI) (Germany)
⁴ Institute for Industrial Ecology (INEC), Pforzheim University (Germany)
⁵ Institute for Technologies and Management of Digital Transformation, University of Wuppertal (Germany)
⁶ Wuppertal Institute for Climate, Environment, and Energy (Germany)

 

Keywords: Circular Economy, Data Competencies, Data-Driven Technologies, Digital Infrastructures, Digital Product Passport, Ecodesign for Sustainable Products, Data Culture, Sustainability Analytics, Circular Business Models, Life Cycle Assessment (LCA), Circularity Metrics

 

Summary for the Editors

This Special Issue bridges the digital and circular transformation pathways toward a circular economy, through data and data competencies. It brings together research excellence, practical implementation, and policy innovation—a hallmark of the DACE initiative and a strong fit for the Journal for Circular Economy’s interdisciplinary mission. It will stimulate academic discourse and offer data-driven, applicable insights for circular transitions across sectors and regions.

 

Aim of the Special Issue

The proposed Special Issue explores data competencies, data-science-based methods and application of data driven technologies as enablers of the circular economy (CE). In an era of resource scarcity, increasing environmental pressure, demanding but also enabling regulations (such as the Ecodesign for Sustainable Products Regulation and its ensuing Digital Product Passport), and increasing competition, data-driven circularity has become a critical field of innovation and policy action.

 

Data competencies, include data collection, data management, data analysis, data application as well as data sharing and publishing. Although crucial enablers of data-driven circularity, they , remain underexplored as ofyet. The Special Issue therefore invites contributions that address this often overlooked but essential dimension of circular transformation. We hence invite scientific and practice-oriented [HB1.1] contributions that investigate how CE data competency including analytical tools, and digital technologies can be used to plan, monitor, understand and accelerate circular transformation across sectors.

 

Target audience:

- Researchers in circular economy, sustainability, and data science.

- Industry and SMEs exploring CE implementation.

- Policymakers and public sector actors working on CE monitoring and governance.

 

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Thematic Focus

The Special Issue focuses on data competencies and data utilization in the circular economy, highlighting the role of data science and digitalization in enabling this systemic transformation. Contributions should address one or more of the following focal areas:

• • Measuring and enhancing data competencies and capacities needed for a data-driven CE.
• • Application of data-science methods (AI, machine learning, data mining, simulation) for circular processes.
• • Integration of CE data spaces, Digital Product Passports, and Life Cycle Tools (LCA, MFA).
• • CE indicators and metrics for monitoring circularity.
• • Governance and interoperability of CE data systems.
• • Competencies and capacities needed for a data-driven CE.

Key questions for authors

Authors may consider questions such as:

• • What specific data competencies (among these data collection, management, analysis, application, sharing, publishing) are required to enable circular economy (CE) strategies?
• • Which types of data are essential for implementing and measuring circular strategies (e.g., the 10R framework)?
• • How can data-science methods support the design, evaluation, and scaling of CE systems?
• • What competencies are needed in research, policy, and business to manage CE data effectively for the given purposes?
• • How can data improve the monitoring, evaluation, and reporting of CE policies, business models, or industrial systems?
• • What can be learned from practical CE implementations using data-driven approaches?

Tracks and Topics

Track 1 – Systematization of Circular Economy Data Competencies

Theoretical and conceptual foundations of CE data competencies, data management, taxonomies, reference models, and frameworks for data-based circular value creation.

Target group: Researchers working on modelling, structuring, and systematizing CE processes.

Track 2 – Data Science in the Circular Economy

Data-science methods, tools, and competences for analysing and optimizing CE systems.

Topics: AI and machine learning for resource prediction, data governance, interoperability, and use cases from practice, development and transfer of CE data competencies.

Target group: Data scientists, engineers, and technically oriented CE professionals.

Track 3 – Implementing Circular Business Models and Processes

Empirical and practice-oriented studies on the implementation, scaling, and digitalization of circular business models.

Topics: Data-supported decision-making, CE indicators, regulatory and economic frameworks, industrial case studies.

Target group: Practitioners, entrepreneurs, policy advisors, innovators.

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Contribution Types

Submissions are invited in the following formats:

- Research articles (theory-based or empirical)

- Practice reports and case studies

- Method-related papers (data models, analytical frameworks, tools)

- Conceptual papers (strategic and forward-looking perspectives)

All contributions must have a clear connection to Circular Economy data. Empirical work with practical relevance is highly encouraged.

Expected Value for the Community

This Special Issue provides:

• An overview of the state of the art in data science for circular economy

• Insights and recommendations for real-world applications and industrial use cases

• Identification of research gaps and future competence needs

Selected papers will also be invited for presentation at the DACE Summit (Aachen, 2026).

Submission and Review Process

Abstract Deadline: 15.02.2026

Notification of Acceptance (Abstract): 15.03.2026

Full Paper Deadline: 15.06.2026

Review Results: 15.08.2026

Revised manuscript deadline: 29.08.2026 (Hard deadline)

Final decision on acceptance: 15.10.2026 (Hard deadline

Length: 6,000–8,000 words

Format: Word (Your Paper Your Way)

Language: English

Review Process: Double-blind peer review

DACE Summit 2026 (optional)

 

All word counts exclude tables, illustrations, and references.

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Formatting Requirements

Manuscripts must be submitted in accordance with the journal’s formatting requirements in addition to using this template as the special issue does not follow Your Paper Your Way. All article text submissions must be made in Word.

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Submission Guidelines

Manuscripts should be prepared in accordance with the journal’s author guidelines. Submissions will undergo double-blind peer review. Both conceptual and empirical papers are welcome.

 

Manuscripts should be submitted via the journal’s online system , selecting “Special Issue: Data and Data Competencies for a Circular Economy – Data-driven enablement of the digital circular economy”.

 

All submissions must adhere to the Journal of Circular Economy’s guidelines and terms including publication fees.

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Contact

For inquiries and submissions, please contact: [email protected] and [email protected].