=Paper=
{{Paper
|id=Vol-3291/paper1
|storemode=property
|title=Decentralized Digital Twins of Circular Value Networks - A Position Paper
|pdfUrl=https://ceur-ws.org/Vol-3291/paper1.pdf
|volume=Vol-3291
|authors=Eva Blomqvist,Mikael Lindecrantz,Fenna Blomsma,Patrick Lambrix,Ben De Meester
|dblpUrl=https://dblp.org/rec/conf/esws/BlomqvistLBLM22
}}
==Decentralized Digital Twins of Circular Value Networks - A Position Paper==
https://ceur-ws.org/Vol-3291/paper1.pdf
Decentralized Digital Twins of Circular Value
Networks - A Position Paper
Eva Blomqvist1 , Mikael Lindecrantz2 , Fenna Blomsma3 , Patrick Lambrix1,4 and
Ben De Meester5
1
Linköping University, Department of Computer and Information Science, 58183 Linköping, Sweden
2
Ragn-Sells AB, Sweden
3
Universität Hamburg, Fakultät für Wirtschafts- und Sozialwissenschaften Sozialökonomie Betriebswirtschaftslehre,
Rentzelstraße 7, 20146 Hamburg, Germany
4
University of Gävle, Department of Building Engineering, Energy Systems and Sustainability Science
5
IMEC - Ghent University - IDLab | Faculty of Engineering and Architecture | Department of Electronics and Information
Systems, Technologiepark-Zwijnaarde 122, 9052 Ghent, Belgium
Abstract
Circular economy aims at reducing value loss and avoiding waste, by circulating material or product
parts before they become waste. Today, lack of support for sharing data in a secure, quality assured, and
automated way is one of the main obstacles that industry actors point to when attempting to create new
circular value networks. Together with using different terminologies and not having explicit definitions of
the concepts that appear in data, this makes it very difficult to create new ecosystems of actors in Europe
today. A solution to these challenges needs to leverage open standards for semantic data interoperability
in establishing a shared vocabulary (ontology network) for data documentation, as well as create a
decentralized digital platform that enables collaboration in a secure and confidentiality-preserving
manner. This vocabulary can then be used to construct digital twins of circular value networks to further
enable open collaboration. Once defined, the blueprints of these digital twins will be reusable as templates
and can be reused with a different set of actors, or used within a different industry domain. This vision
includes a number of open research problems, including the development of ontologies that need to model
a wide range of different materials and products, not only providing vertical interoperability but also
horizontal interoperability, for cross-industry value networks. As well as transdisciplinary research on
methods to find, analyse and assess new circular value chain configurations, and form their decentralized
digital twins. The solutions will allow for automation of planning, management, and execution of circular
value networks, at a European scale, and beyond. Thereby supporting the acceleration of the digital
and green transitions, automating the discovery and formation of new collaborations in the circular
economy.
Keywords
Circular Economy, Semantic Web, Ontology, Value Networks, Digital twins
Third International Workshop On Semantic Digital Twins (SeDiT 2022) Co-located with the 19th European Semantic
Web Conference (ESWC 2022), Hersonissos, Greece - 29 May 2022
Envelope-Open eva.blomqvist@liu.se (E. Blomqvist); Mikael.Lindecrantz@ragnsells.com (M. Lindecrantz);
fenna.blomsma@uni-hamburg.de (F. Blomsma); patrick.lambrix@liu.se (P. Lambrix); ben.demeester@ugent.be
(B. De Meester)
GLOBE https://evablomqvist.se/ (E. Blomqvist); https://digistate.io/ (M. Lindecrantz);
https://www.ida.liu.se/~patla00/index.shtml (P. Lambrix); https://ben.de-meester.org/#me (B. De Meester)
© 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
1. Introduction
Semantic interoperability of data is one of the biggest barriers towards data sharing in the
Circular Economy (CE). However, we argue that Semantic Web technologies can provide the
technical foundations for information flows that will transform European Industry towards a
CE, by means of digitalisation and data sharing. By leveraging open standards for semantic
data interoperability and establishing a shared network of ontologies for data documentation,
as well as implementing a decentralized digital platform that enables collaboration in a secure
and confidentiality-preserving manner this will allow for automation of discovery, planning,
management, and execution of cross-industry circular value networks. Combined with auto-
mated access control policies for data privacy and confidentiality, this enables automation while
protecting company-internal data, and allows data sharing at the right level of granularity.
For putting this in place a forthcoming EU-funded project, Onto-DESIDE, will develop a
technology for allowing data sharing about materials and products at a global scale, see Fig. 1.
This paper describes the overall vision, and research position from which this project starts,
which has also partly been developed in the Swedish Vinnova-project CIRCLA. Since access to
verifiable information is central, well-established open standards for secure and confidentiality-
preserving information sharing are core components. Ownership and storage of data should
remain with the data producer; hence a decentralized approach is necessary. Metadata and
structures for transforming data into information (semantic descriptions, i.e. ontologies) will
be open, and comply with FAIR principles, to enable the highest possible degree of semantic
interoperability and automation in data sharing. For sensitive data, methods allowing for proof
of existence of the data can be used, where proofs can be shared while actual data is kept private.
Equality, democracy, and ethics are key aspects in collaboration and data sharing, and aspects
that will be central in developing the details of the data sharing architecture.
Another aspect is to address the use of these technologies in a business context, and study
the circular economy as a complex system to develop integrated tools and methods for further
enhancing CE. Although the importance of various ‘flows’ - namely: resource flows, information
flows, value flows, and energy flows - has been widely acknowledged within the transformation
to CE, so far they have not been integrated or linked into a single framework or approach
[1]. Without such integration or linking it is currently not possible to make robust designs of
circular value networks, and to conduct value network coordination towards implementation
and operation within industry. Moreover, this should result in robust value networks that are
profitable, equitable, and invite long-term collaborations and partnerships. Therefore, apart
from the solutions needing to be technically feasible, there is also a need to explore how such
value networks can be designed and developed, using the ontologies for data documentation
and data sharing, but considering the interplay of resource, information, value and energy flows,
i.e considering how the value network will behave as a system. Four core components that
need to be explored are envisioned:
• A network of ontologies for data documentation, that allows for semantic interoper-
ability and supports flexible, automated, decentralised data sharing between industry
actors.
• An open circularity platform, i.e. a secure and confidentiality-preserving decentralized
data sharing platform allowing the creation of digital twins of circular value flows, by
Figure 1: The Onto-DESIDE concept – From requirements, via shared vocabularies, to a shared data
space for discovery and execution of new circular value flows, and new business models, demonstrated
and evaluated in concrete industry use cases.
enabling FAIR sharing of data between industry actors, facilitating the initiation of new
collaborations in the circular economy.
• Methods to find, analyse, and assess new circular value chain configurations opened
up by considering resource, information, value, and energy flows as an integral part of
transitioning to a circular metabolism within industrial systems through co-design and
co-creation.
• Validation - demonstrating and quantifying the potential for increased retainment of
value when applying the above outcomes in cross-border and cross-industry sector circular
value networks in Europe.
In this paper the focus is on the technological aspects, and in particular those related to
Semantic Digital Twins. Hence, next, two of the key concepts underpinning the Onto-DESIDE
vision are introduced in more detail, including the state of the art in each area, to establish the
novelty and excellence of the research direction. The key concepts, corresponding to the first
two core components listed above, are: (1) an ontology network for data documentation, and (2)
the “digital twin” in circular economy facilitated by the open circularity platform. The concepts
are explained, as well as the vision of how to advance the state of the art of these key concepts.
2. Ontologies for data documentation
Ontologies have been applied in many domains, and are widely understood as a key technology
to address semantic interoperability. An ontology network [2] is a set of interrelated ontologies,
built using a modular architecture, in order to separate concerns and allow for ontology use
and reuse at the right level of granularity and expressivity. Standard ontology networks exist
in several domains, such as the Semantic Sensor Networks (SOSA/SSN) ontology network [3],
which is a W3C and OGC standard, or SAREF1 as an alternative for smart applications, and the
OBO Foundry [4] in biomedicine, emerging as a de-facto standard in the biomedical field.
No similar effort, or standard, as the ones mentioned above exist neither in the overall CE
domain, nor in the more specific sub-domains facilitating semantic interoperability of typical
CE data categories, such as information about materials, products, capabilities etc. There are
general ontologies for products, such as the widely used GoodRelations [5], also integrated with
schema.org, which is targeted at the online retail market, as well as domain-specific product
ontologies, e.g. specifically for construction, or manufacturing industry. However, none of
these are built with CE requirements in focus, and do not target product reuse, refurbishing,
recycling etc. Similarly, many ontologies have been proposed to model organisations, from
the generic W3C standard ORG-ontology [6], to ontologies focusing on specific business use
cases. Still, none of these fully cover the requirements of the CE, for forming and executing
new circular value networks.
A core part of the needed ontology network is related to materials models, which can be used
to describe both virgin materials, product parts during a product life cycle, as well as recycled
materials. Interoperability in materials science is traditionally achieved mainly via file-based
exchange involving specific formats and, at best, some partial metadata, which is not always
guided by an ontology. Examples of such efforts includes the Materials Genome Initiative2 , and
the API-based effort of Open Databases Integration for Materials Design (OPTIMADE)3 [7]. A
recent approach is the Novel Materials Discovery (NOMAD) [8]. However, none of these efforts
use ontologies to provide semantic interoperability.
Nevertheless, also in the materials science domain, recently, an awareness has emerged
regarding the importance of semantic interoperability and FAIR principles for data storage and
management [9]. Two ontologies representing general materials domain knowledge are ChEBI
[10] and EMMO [11]. EMMO is an upper ontology, currently developed by the European Mate-
rials Modelling Council, aiming at developing a standard representational ontology framework,
but several sub-domain of materials modelling are still not covered, and the ontology aims at
being an upper ontology for other ontologies to extend. Recently, in our research we have also
developed and published the Materials Design Ontology (MDO) [12], an ontology guided by the
schemas of OPTIMADE but intended to provide a semantic interoperability layer in materials
science. In summary, the few ontologies that exist have been developed focusing on representing
either very general materials domain knowledge, or specific narrow sub-domains. In addition,
there is a need to align to current ongoing efforts, such as the IOF4 and OntoCommons5 , but
although it is important to be compatible with these perspectives, in particular upper ontologies,
none of these have their focus on the specific cross-domain and cross-industry aspects of CE.
Hence, to solve the general challenges of circular value networks there is a need to align and
refer to specific other ontologies for more granular representation of certain details within one
domain, but keeping the core models generic.
1
https://saref.etsi.org/
2
https://www.mgi.gov/
3
https://www.optimade.org/
4
https://www.industrialontologies.org/
5
https://ontocommons.eu/
The work needed is hence to, based on es-
tablished technologies and standards (i.e. us-
ing the W3C standard OWL6 for ontology
representation), develop and evaluate an on-
tology network for data documentation tar-
geting the cross-industry domain of circular
economy. A number of additional challenges
not present in any existing efforts will have
to be addressed, including the need to cover
a wide range of different materials and prod-
ucts, as well as the need not only for vertical
interoperability of ontologies but also a min-
imal level of horizontal interoperability, for
cross-industry value networks. These are ex-
tremely challenging requirements, where so-
lutions then need to be demonstrated through
Figure 2: Conceptual illustration of the ontol-
thorough evaluation in industry use cases.
ogy network architecture which will
To ensure scalability and separation of con-
realize the challenging requirements
cerns in the ontology network, a layered on-
of both vertical and horizontal interop-
tology network architecture (e.g. inspired by
erability, as well as reusability of value
SOSA/SSN) should be used, as illustrated in
flow digital twin blueprints. Inner cir-
Fig. 2, where a set of core Ontology Design
cles represent more fundamental con-
Patterns (ODPs) will act as the basic modelling
cepts, that are reused (e.g. through im-
templates for a set of core ontology modules,
porting) by the ontologies of the outer
defining the common concepts shared by sev-
circles, hence further specialising the
eral industry domains and use cases. Another
fundamental concepts.
challenge is to achieve the right level of ax-
iomatization for each module, making it on
one hand highly reusable, but on the other hand also usable for data integration and reasoning.
In the figure, the overall architecture is illustrated, where the outer layers import modules from
the inner layers, and extend these by specializing and adding axiomatization and alignments.
3. “Digital twins” in CE - An open circularity platform
While semantic interoperability, and ontology-based data documentation, are essential enablers
for large scale CE, it is not enough in itself. Semantically described data also need to be put into
use, in automated processes. Today, there is limited data collaboration within industry domains
and even less across domains, consequently new circular value networks are only created
between known actors that have a certain degree of comfort working together [13] - limiting
the possibilities of more high value circulation scenarios. Open collaboration could remedy this,
but data and ontologies cannot solve the problem alone. To facilitate open collaboration in a
data driven circular economy a new entity is needed; the digital twin of circularity.
6
https://www.w3.org/OWL/
Here we rely on the digital twin definition provided by the Digital Twin Consortium7 , part of
the international standards organization, the Object Management Group8 . The definition states
that a digital twin:
• Is a synchronized virtual representation of real-world entities and processes.
• Uses real-time and historical data to represent the past and present and simulate predicted
futures.
• Transforms businesses by accelerating holistic understanding, decision-making, and effec-
tive action, and is motivated by outcomes, tailored to use cases, powered by integration,
built on data and guided by domain knowledge.
The concept of digital twins has been put to use for many use cases and in many industries
[14] and the fundamental theory behind the concept is not a new thing. For instance, one
study [15] explored the usage of digital twins in the context of a circular value network for
remanufacturing in the construction industry. But, the idea of constructing digital twins of
circular value networks, with the value network itself, and related ‘flows’, as the objects in
focus, is a novel idea and has not been explored before.
If digital twins are built upon shared ontologies, i.e. the ontology network, once defined,
their blueprints are also reusable as templates for a certain type of circular value network,
and could at minimal effort be shared with a different set of actors or used within a different
industry domain to instantiate new value networks. Previous work that implements such ideas
are for example the sectoral circular economy business model patterns within manufacturing
companies [16]. Another example, this time from the construction industry, is the concept
of making use of Building Information Models (BIM), and BIM objects, to explore the notion
of generic capabilities [17]. The vision is for Onto-DESIDE to develop these ideas further, by
viewing the digital twin as a form of design pattern [18], essentially blueprints of executable
circular value flows applicable in various domains, which is a novel idea. In addition, the use
of ontologies to describe such blueprints for digital twins of circular value flows is also both
challenging, but promising and novel.
Instead of having each industry domain creating their own circular interconnections over time,
however, we argue that the core logic of circularity should be common and manifested in a digital
entity that translates between industry domains. Existing Circular Economy standardization
efforts, such as ISO WD590049 and TC32310 , have begun to address this, but standards also
need to be operationalized technically, which is targeted here. By enabling translations between
domains, the need for central repositories of information is also reduced, every organization
will keep and manage their own data. By building on well established standards for semantically
describing, interlinking and sharing data, collaboration is made secure and scalable. Every
circular digital twin will share the same fundamental definitions, and functionality is increased
through detailing and populating the data documentations with increased granularity, i.e.
specialisations of the ontology network and the circularity blueprint, rather than by adding
7
https://www.digitaltwinconsortium.org/initiatives/the-definition-of-a-digital-twin.htm
8
https://www.omg.org/
9
https://www.iso.org/standard/80648.html
10
https://www.iso.org/committee/7203984.html
complexity through constructing new case-by-case solutions. On its own, the twin represents
value to stakeholders by providing the technical infrastructure for making data exchange in
complex circular eco-systems manageable, and reusable.
Technically, the digital twin idea will be implemented as an open circularity platform using
existing, and emerging, Web technologies, such as RML for semantically annotating and trans-
forming heterogeneous data sources [19], Solid for building decentralized applications based on
Linked Data principles [20], and incorporating validation and verification methods that provide
proofs of data authenticity [21]. Given a commonly understood ontology, the following three
challenges provides a novel decentralized solution:
• Semantic interpretation of existing data, so that actors can rely on existing infrastructure;
• A decentralized network to publish and retrieve semantically annotated data, behind a
layer of authentication and authorization, so that actors can share their data with only
those partners they are comfortable with;
• A verification method so that collaborating actors can trust the data they are using.
The objective of the platforms is to demonstrate that ontology-based decentralized data
sharing can operationalise the idea of a decentralized digital twin, maximally taking advantage
of existing IT infrastructures and standards - without compromising access control and trust.
4. Summary and Outlook
The employment of semantic ontologies and linked data together with the concept of digital
twins to enable open data collaboration in the context of circular economy is a novel idea, and the
vision of the Onto-DESIDE project. The project will provide a test bed for exploring and verifying
these novel research topics related to the combination of circular economy and digital twins.
Industry use cases, in the domains of textile, electronics, and construction, that make use of real
business data, will ensure that results are relevant and usable in an operational context, across
industry domains. This also provides a good empirical basis for further research on the topics
of digital twins and semantic data in the context of the circular economy transition. Next steps
in research towards these goals include the development of the envisioned ontology network,
including identification of core issues in cross-industry applications of the circular economy,
detailing and operationalization of the digital twin concept and its reusable blueprints, using
Semantic Web technologies, as well as in parallel develop the methods for finding, analysing
and assessing circular value chain configurations in a business ecosystem.
We envision that the thinking and concepts that we present in this paper, as well as what is
to be explored in the Onto-DESIDE project, open up for new ideas and paths of research that
are needed to facilitate a green transition at scale.
Acknowledgments
Thanks to all partners in the forthcoming Onto-DESIDE consortium for their contributions to
the vision, and the EC for providing funding of this future research (GA under negotiation).
Developing this vision was also partly funded by the Swedish Vinnova-project CIRCLA (Dnr.
2021-04323).
References
[1] F. Blomsma, M. Tennant, R. Ozaki, Making sense of circular economy oriented innovation: from
idea to implementation, J. Business, Strategy and the Environment (forthcoming).
[2] Ontology Engineering in a Networked World, Springer, Berlin, Heidelberg, 2012.
[3] A. Haller, K. Janowicz, S. J. Cox, M. Lefrançois, K. Taylor, D. Le Phuoc, J. Lieberman, R. García-Castro,
R. Atkinson, C. Stadler, The modular ssn ontology: A joint w3c and ogc standard specifying the
semantics of sensors, observations, sampling, and actuation, Semantic Web 10 (2019) 9–32.
[4] B. Smith, M. Ashburner, C. Rosse, J. Bard, W. Bug, W. Ceusters, L. J. Goldberg, K. Eilbeck, A. Ireland,
C. J. Mungall, et al., The obo foundry: coordinated evolution of ontologies to support biomedical
data integration, Nature biotechnology 25 (2007) 1251–1255.
[5] M. Hepp, Goodrelations: An ontology for describing products and services offers on the web, in:
International conference on knowledge engineering and knowledge management, Springer, 2008,
pp. 329–346.
[6] The organization ontology - w3c recommendation 16 january 2014, 2014. URL: http://www.w3.org/
TR/vocab-org/.
[7] C. W. Andersen, R. Armiento, E. Blokhin, et al., Optimade, an api for exchanging materials data,
Scientific Data 8 (2021) 217. doi:10.1038/s41597- 021- 00974- z .
[8] C. Draxl, M. Scheffler, The nomad laboratory: from data sharing to artificial intelligence, Journal of
Physics: Materials 2 (2019) 036001.
[9] P. Lambrix, R. Armiento, A. Delin, H. Li, FAIR Big Data in Materials Design, in: Encyclopedia of
Big Data Technologies, Springer, 2022.
[10] K. Degtyarenko, P. De Matos, M. Ennis, J. Hastings, M. Zbinden, A. McNaught, R. Alcántara,
M. Darsow, M. Guedj, M. Ashburner, Chebi: a database and ontology for chemical entities of
biological interest, Nucleic acids research 36 (2007) D344–D350.
[11] Documentation on materials modelling ontology in uml - emmc csa deliverable 2.7, 2019.
[12] H. Li, R. Armiento, P. Lambrix, An ontology for the materials design domain, in: International
Semantic Web Conference, Springer, 2020, pp. 212–227.
[13] G. Bressanelli, F. Adrodegari, M. Perona, N. Saccani, Exploring how usage-focused business models
enable circular economy through digital technologies, Sustainability 10 (2018) 639.
[14] A. Fuller, Z. Fan, C. Day, C. Barlow, Digital twin: Enabling technologies, challenges and open
research, IEEE access 8 (2020) 108952–108971.
[15] Z. Chen, L. Huang, Digital twin in circular economy: Remanufacturing in construction, in: IOP
Conference Series: Earth and Environmental Science, volume 588, IOP Publishing, 2020, p. 032014.
[16] M. P. Pieroni, T. C. McAloone, D. C. Pigosso, Circular economy business model innovation: Sectorial
patterns within manufacturing companies, Journal of cleaner production 286 (2021) 124921.
[17] L. A. Akanbi, L. O. Oyedele, K. Omoteso, M. Bilal, O. O. Akinade, A. O. Ajayi, J. M. D. Delgado, H. A.
Owolabi, Disassembly and deconstruction analytics system (d-das) for construction in a circular
economy, Journal of cleaner production 223 (2019) 386–396.
[18] A. Gangemi, V. Presutti, Ontology design patterns, in: Handbook on ontologies, Springer, 2009, pp.
221–243.
[19] A. Dimou, M. Vander Sande, P. Colpaert, R. Verborgh, E. Mannens, R. Van de Walle, Rml: a generic
language for integrated rdf mappings of heterogeneous data, in: LDOW, 2014.
[20] S. C. Group., Solid technical reports, 2021.
[21] D. Burnett, G. Noble, B. Zundel, D. Longley, M. Sporny, Verifiable credentials data model 1.0, 2019.