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https://ceur-ws.org/Vol-3355/preface.pdf
Preface for the 1st International Workshop on
Semantic Industrial Information Modelling (SemIIM)
Arild Waaler1 , Evgeny Kharlamov2,1 , Baifan Zhou1 and Dongzhuoran Zhou2,1
1
SIRIUS Centre, Department of Informatics, University of Oslo, Norway
2
Bosch Center for AI, Germany
Abstract
SemIIM2022 was a full-day workshop that took place on 30th May 2022 in Hersonissos, Greece, co-
located with the 19th edition of the Extended Semantic Web Conference (ESWC2022). This workshop
invited industrial as well as academic keynotes, industrial panellists and papers covering the challenges
and solutions for addressing industrial information modelling, including methods and practices of
representing concepts, relationships, constraints, rules and operations to specify data semantics for a
chosen domain of interest. The workshop gathered the interested community and discussed the latest
approaches for challenges both from the perspectives of academia and industry.
1. Introduction
Information Modelling (IM) has been under the spotlight of both academia and industry for
decades [1, 2]. Important aspects of IM include methods and practices of representing concepts,
relationships, constraints, rules and operations to specify data semantics for a chosen domain
of interest. As a response to the IM challenge a number of modelling paradigms and languages
arose and they range from ERM [3], UML [4], ORM [5] to OWL [6] and Knowledge Graphs [7]
and come with a wide range of systems to support the life cycle of information models [8, 9].
Despite the past success, existing approaches and systems for IM fail to cope with new
challenges of overwhelming global industrial digitalization that requires advanced information
models and aims at fully computerized, software-driven, automation of production processes
and enterprise-wide integration of software components [10, 11, 12, 13, 14]. Such trend and the
technological and industrial developments that come with it are an important part of Industry
4.0 and industrial Internet of Things [15]. It requires IM that, for example, allows to capture the
functionality of and information flow between different assets in a plant, such as equipment
and production processes. Moreover, it requires IM and models that are based on ISA and
IEC standards and have a number of desirable properties, e.g., reusable, explainable, scalable,
simulatable etc [16, 17]. Such IM should allow for seamless data sharing and integration e.g.,
via data market places and across value chains [18, 19].
SemIIM’22: 1st International Workshop on Semantic Industrial Information Modelling, 30th May 2022, Hersonissos,
Greece, co-located with 19th Extended Semantic Web Conference (ESWC 2022)
$ arild@ifi.uio.no (A. Waaler); evgeny.kharlamov@de.bosch.com (E. Kharlamov); baifanz@ifi.uio.no (B. Zhou);
dongzhuoran.zhou@de.bosch.com (D. Zhou)
© 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)
These new challenges require new theory, methodology, best practice, systems and this
should be developed, shared, and discussed by a wire range of stakeholders. Therefore, we
initiated the 1st International Workshop on Semantic Industrial Information Modelling (SemIIM)
to provide a venue for the community of industrial information modelling.
2. The SemIIM2022 Workshop
The 1st International Workshop on Semantic Industrial Information Modelling (SemIIM) aims at
gathering researchers and practitioners who work on addressing these challenges with the help
of semantic technologies. We in particular invited IM experts who are excited and committed
to push the frontiers of IM further and support modern industry in its current technological
transformation. In our workshop we welcomed novel methods, systems, solutions, experience,
and practice for semantic industrial information modelling.
The workshop included the following sessions:
2.1. Industrial Keynote
The Industrial Keynote was given by Jean-Charles Leclerc at TotalEnergies on the topic: “Bridg-
ing Industrial Ecosystems Around Standardized Semantic Information Models”
As emphasized in the European Green Deal and in the New Industrial Strategy for Europe,
developing new standards, coupled with increased efforts of international standardization bodies,
will be essential to boost industry’s competitiveness and build a sustainable and more inclusive
future. Recent European H2020 projects and clusters, Joint Industrial Projects in industry and
advanced standards of Standardization Development Organizations converge towards new
ways of using standards to enable integration of data and applications, thus enabling new
ways of working all along the products’ and plants’ life cycle and ecosystem. In this talk, the
speaker elaborated in the context of developing an industrial ecosystem and real interoperability
conditions:
• A necessary common framework for information management and its genericity, based
on ISO15926-14 ontology for an efficient formal and concretes disambiguation of con-
cepts then ISO15926-4 PCA (more than 60000 concrete classes) for our Multi-Energies
Company business objects references URI mappings, then we addd additional standards
such ISO/IEC81346 for systems, ILAP and ISO15926-13, for dynamic aspects of quality
configuration management against roles and activities all along Life-Cycle Information.
• An agreed methodology required for the alignment of internal reference data, models and
technical repositories with external ontologies-based standards, such as ISO 15926-14/-4,
and other future SMARTs (Standards Machine Applicable Readable and Transferable),
digitalized according to common principles and rules for the provision of consistent
digital specifications, and configurations management.
• A concrete illustration thanks to a set of tools enabling industry standards visualization,
manipulation, and mapping/linking to enterprise data. All these operations based on
capabilities offered by the W3C semantic web standards are necessary for a real and
manageable interoperability and for delivering the real value of incoming digital twins.
• We illustrated our point with the ongoing TotalEnergies initiative of Reference Data
Domain business objects alignment exercise to feedback our experience outcomes and
provide some way forward and lessons learned perspectives.
2.2. Academic Keynote
The Academic Keynote was given by Hedi Karray at National Engineering Scholar of Tarbes on
the topic: “Semantic Industrial Models - State of the Art From an Academic Perspective”
Ontology has been touted as a solution to interoperability and a formal knowledge repre-
sentation in an evolving collaborative industrial domain [20, 21, 22, 23]. However, even where
ontologies are used in industry, they are often embedded as components in larger proprietary
systems. Moreover, such ontologies were in almost all cases developed without any heed to
reuse existing ontology or apply lessons learned from past initiatives. Most of the common
concerns for reusing existing ontology are regarding lack of consensus among models, limited
coverage of domains, and ambiguity in the semantic definitions of the concepts of those ontolo-
gies. Furthermore, such disagreement among ontologies arises because most of them do not
adhere to a suitable top-level ontology and often built without following a standard ontology
development methodology. Consequently, adopting these ontologies rather increases the risk
and uncertainty of the project in place of saving time and effort. The presentation addresses
different layers of ontologies interoperability and will introduce some examples of ambiguity for
each of the layers. The speaker introduced how these interoperability issues may be mitigated
by stratification of ontologies.
2.3. Industrial Panel
The industrial panel was on the topic: “Semantic Industrial Information Modelling - Dream vs
Reality (Mitigating the Gap for Industry)” given by the following panellists:
• Marcel Fröhlich, Director Services at Eccenca
• Daniel Herzig, Chief Operating Officer at Metaphacts
• Vladimir Alexiev, Chief Data Architect at Ontotext
• Irlan Grangel Gonzalez, Activity Manager at Bosch Corporate Research
• Maja Miličić Brandt, Senior Key Expert at Siemens
• Claude Fauconnet & Jean-Charles Leclerc, Innovation & Standards Lead at TotalEnergies
Panel goal: The panel brought together researchers and two kinds of industry representatives:
1. technology providers (of semantic solutions) and
2. semantic technology consumers such as Siemens, Bosch and Total that rely on ontologies
and KGs to model equipment, processes, etc and put such models in production [24].
There is still a gap between what research and technology providers offer to industry
today and the actual industrial needs. During the panel it was discussed whether such
gap indeed exists and how to mitigate it.
Panel format:
• Each panelist had 10 min to give a short presentation of her/his organisation (3-5 min),
thoughts / pitch on the topic of the panel (5-7 min).
• Then, we had 1h for question answering and discussions (questions from panellists to
each other, questions from the audience, questions from the moderators).
• We had short presentations grouped in 2 sessions - first 3 talks of technology adopters
and then 3 talks of technology providers.
2.4. Workshop Papers
Seven papers were submitted. The reviews were hosted at EasyChair. Each paper received
at least three reviews from reviewers with different background and status. Six papers were
accepted. Two of the accepted papers were regular papers and four were short papers. The
following papers were accepted for publication and presented at the workshop
• Regular papers:
– Towards Models of Conceptual and Procedural Operator Knowledge [25]
– Ontoflow: A User-Friendly Ontology Development Workflow [26]
• Short papers:
– Towards Addressing Requirements to Identification Posed by the Digital Transfor-
mation [27]
– SparTDD - A SPARQL Based Thing Description Directory [28]
– Towards a Visualisation Ontology for Data Analysis in Industrial Applications [29]
– Industrial Geological Information Capture with GeoStructure Ontology [30]
3. Organizing Committee
• Arild Waaler, University of Oslo, Norway
• Evgeny Kharlamov, Bosch Center for AI / University of Oslo, Germany
• Baifan Zhou, University of Oslo, Norway
• Dongzhuoran Zhou (Web Chair), Bosch Center for AI / University of Oslo, Germany
4. Program Committee
• Ahmet Soylu, Oslo Metropolitan University, Norway
• Arild Waaler, University of Oslo, Norway
• Baifan Zhou, University of Oslo, Norway
• Dongzhuoran Zhou, Bosch Center for AI / University of Oslo, Germany
• Dumitru Roman, SINTEF AS / University of Oslo, Norway
• Ernesto Jiménez-Ruiz, University of London, United Kingdom
• Evgeny Kharlamov, Bosch Center for AI / University of Oslo, Germany
• Gong Cheng, Nanjing University, China
• Irlan Grangel Gonzalez, Bosch Corporate Research, Germany
• Jiaoyan Chen, University of Oxford, United Kingdom
• Kavitha Srinivas, IBM Research, United States
• Maryna Waszak, SINTEF AS, Norway
• Muhammad Yahya, National University of Ireland, Ireland
• Vincenzo Cutrona, University of Applied Sciences and Arts of Southern Switzerland,
Switzerland
• Yuanwei Qu, University of Oslo, Norway
• Yulia Svetashova, Causaly, United Kingdom
• Zhuo Chen, Zhejiang University, China
• Zhuoxun Zheng, Bosch Center for AI / Oslo Metropolitan University, Germany
Acknowledgements
This publication is supported by the European Commission H2020 projects Dome 4.0 (Grant
Agreement No. 953163), OntoCommons (Grant Agreement No. 958371), and DataCloud (Grant
Agreement No. 101016835) and the SIRIUS Centre, Norwegian Research Council project number
237898. We gratefully acknowledge the economic support from The Research Council of
Norway and Equinor ASA through Research Council project “308817 - Digital wells for optimal
production and drainage” (DigiWell).
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