Table of contents:



What are the OntoCommons demonstrators?

The demonstrators are a list of use cases that will be used to prove the effectiveness of the OntoCommons Ontology Commons EcoSystem (OCES) and provide insights on the use of standardised ontologies to resolve issues with material sciences and manufacturing data documentation, data re-use and cross-domain interoperability.


Demonstrators' contribution to the project's objectives

The demonstrators will contribute to the harmonisation of at least 10 existing ontologies and initiate the development of at least 3 new domain (or sub-domains) ontologies.

A strong interaction between demonstrators and ontology developers will be paramount in order to build a set of Top Rerefence and Middle-Level Ontologies that will be beneficial to the overall European community.


Demonstrators' contribution to the project's expected impacts

  • Standardised and FAIR intra- and cross-domain data documentation 
    Based on wide-ranging stakeholder involvement, the demonstrators will contribute to achieve an ontology-based data documentation across NMBP domains. 
  • Facilitate uptake of the project's results
    Standardised data documentation and uptake of the project's results will be shown in the various demonstrators.
  • Improved ability to build interoperable software solutions in materials and manufacturing domains
    The demonstrators will serve as references for the uptake of ontology-based software.


Demonstrators' contribution to ontologies standardisation

Current standards can be in the way of innovative procurement of new materials in manufacturing. The OntoCommons demonstrators will ensure alignment on emerging standards to explore the opportunities of a more dynamic, ontology-based system to support faster innovation. 


OntoCommons Demonstrators

OntoCommons aims to deliver: 

  • A predefined set of initial 11 demonstrators ranging through the NMBP work programme domains are proposed by the OntoCommons consortium in order to speed up the process of definition of the OCES.
  • Community proposed demonstrators (Community Demonstrators) up to a maximum of 10 will be added during the first year of the project following stakeholder consultations.
  • Demonstrators based on existing H2020 projects that share the same objectives of OntoCommons and expressed commitment to merge their efforts and resources.

OntoCommons predefined 11 Demonstrator cases



  • Use case description: During the detailed design of an assembly plant, different domains engage in a design process, being impacted and impacting the design process of other domains. A trade needs to be done between these domains, to find the most suitable design of the plant.
  • Use case goal: Overcoming bottlenecks concerning interoperability and data standardisation. Enabling different collaborative engineering of different domains.
  • Industry domain: Aerospace, Manufacturing.
  • Proposer: Airbus / UiO


  • Use case description: Automation in manufacturing, e.g., of microchips at the Bosch Salzgitter factory, requires monitoring, analyses, and control of various processes and machines. This boils down to the integration of numerous (possibly dynamic) data sets that range from sensor data generated by machines at the factory’s shop floor to specifications of processes and legacy SAP data. Such data integration is a challenging problem and one of the approaches that Bosch takes in addressing it is by developing a unified Industry 4.0 information model in the form of an ontology that is based on the IEC 62264 international standard and has two levels. The upper-level ontology, called Bosch I4.0 Core Ontology, reflects the main part of IEC 62264. The core ontology is rather generic. Therefore, in a concrete data integration scenario, the core ontology is accompanied by domain-specific ontologies to capture machines, materials, and processes specific to the scenario. Then, the ontologies are mapped to the datasets of the scenario and the data can be accessed in a uniformed fashion and either queried directly or extracted and shipped to applications for, e.g., analytics, KPI computation. 
  • Use case goal: To show how the use of standardized ontologies can significantly simplify the data integration problem behind an analytical scenario at a Bosch factory. The analytics is needed as a part of the overall goal of factory automation. To enable integration of heterogeneous factory‐wide data for analytics of factory machines and processes, their monitoring and control. 
  • Industry domain: Manufacturing
  • Proposer: Bosch



  • Use case description: Capturing of all relevant chemical, manufacturing requirements and mechanical properties related to each manufacturing grade. Such a manufacturing grade ontology will have a complex definition. The manufacturing grade must-have reference to upper ontology resources such as chemical elements, crystalline structures and units of measure. For purchase companies typically issue material specifications or material data sheets (MDS), containing specializations of standard industrial grades material and test requirements. Semantic representation of MSD will be done in a similar as semantic representation of standard grades. MDS semantics can enable collaboration between organisations and be the foundation for machine supported QC. 
  • Use case goal: Compare material grades as listed in EN, ISO or ASTM standards. The reasoned engine will determine which are the same and which are specializations of another standard material grade based on their semantic definition.
  • Industry domain: Process industry.
  • Proposer: Sirius ‐ Aibel AS



  • Use case description: The use case will shorten the time and the number/size of experiments required to identify the behaviour of a material or combination of them (e.g. metal, coating, lubricant) with respect to specific operating conditions. Tribomat will perform a federated search and look in available data sources (open, or under license agreements,…) including databases, articles, etc. for past experiments that can support the request.
  • Use case goal: Federation/aggregation of tribology testing results for the tribological characterization of materials and their degradation properties under consistent operating conditions.
  • Industry domain: Manufacturing – at various sectors (e.g. Automotive, Aerospace, Energy, …)
  • Proposer: Tekniker 


  • Use case description: Facilitate the interoperability of platforms and services within an open European Virtual Marketplace Framework, involving tools and ontologies from the Allotrope Framework 
    and NMBP materials modelling marketplace projects.
  • Use case goal: Supporting interoperability within the European Virtual Marketplace Framework: An interoperability framework including materials modelling marketplaces, open translation environments, data marketplaces, open innovation platforms, and business decision support systems from the NMBP line of projects, employing tools and ontologies from the Virtual Materials Marketplace (VIMMP) project and the Allotrope Framework.
  • Industry domain: Nanotechnologies, Advanced Materials, Biotechnology, and Advanced Manufacturing and Processing (NMBP).
  • Proposer: STFC and GCL


  • Use case description: OAS as a very agile company with a very strong position on the national and international market is more and more oriented towards product customisation and services around their products, i.e. building Product Service Systems (PSS). OAS has identified a need to extend its systems to CPS based systems allowing product/process optimisation as an integral part of a customised turn‐key PSS solution.
  • Use case goal: OAS has long proven experience in weighting and logistics technology usage, to boost logistics, production and to assure quality, in combining materials handling and weighting, in integrating weighing, dosing, mixing, logistics and control to form a unified system. 
  • Industry domain: Equipment industry 
  • Proposer: OAS A.G. Germany



  • Use case description: Measurement of different feedstocks, correlation with other feedstocks quality and correlation with the quality of produced components.
  • Use case goal: Evaluation and quality assurance of feedstock for further processing.
  • Industry domain: Quality assurance of powder blends.
  • Proposer: Fraunhofer IFAM 
IRES NANO-MATERIALS - Occupational Exposure assessment for polymer-based additive manufacturing (AM) 
production processes. 



  • Use case description: Performance of a series of field measurements in order to characterise the airborne particle number concentration (PNC) that results from additive manufacturing activities. 
  • Use case goal: Evaluate levels of exposure within the workplace, in order to conduct a health risk assessment. Specify the influence of process parameters on emissions. 
  • Industry domain: Chemical, process engineering involving nano (in lab, pilot and industrial scale).
  • Proposer: IRES.


  • Use case description: Performance of a series of field measurements in order to characterise the airborne particle number concentration (PNC) that results from additive manufacturing activities.
  • Use case goal: Minimization of a number of experiments, cost reduction, accessibility Workflow Optimization, Quality Assurance, Data exploitation (e.g. interoperability on relevant methodologies, transfer learning etc.).
  • Industry domain: Surface and coatings, (nano)composites, thin films, organic/inorganic, 2D materials.
  • Proposer: IRES.



  • Use case description: The use case uses several data sources: customers/users’ descriptions of problematic issues, reports from technicians, data collected from machines’ sensors, machinery design.
  • Use case goal: Standardize the terminology of the maintenance process, focusing in particular on the diagnosis of technical malfunctioning, and leveraging on the knowledge extracted from service information flows and repair records.
  • Industry domain: Equipment Industry
  • Proposer: CNR



  • Use case description: For the implementation of the project Halcor will contribute with raw material input data coming from its Casting plant, process data attached to products and kept in Halcor’s Traceability and Manufacturing Execution Systems, material and technical specifications per production step. Collecting and pre‐assessing data required, participating in the design and testing of data ontologies, verifying the successful project completion will be the main part of Halcor’s tasks.
  • Use case goal: Semantic representation of technical documentation throughout Halcor's entire value chain in order to achieve data harmonization, data interoperability and interconnectivity.
  • Industry domain: Manufacturing.
  • Proposer: ELVAHALCOR and the University of Oslo.



  • Use case description: The manufacturing planning process needs to be at least partly automated to flexibly react upon low volume production orders. 
    The decision of whether an available machine is capable of performing a required production step can be automated by reasoning over explicit machine capability descriptions expressed in terms of ontologic vocabularies about the background knowledge captured in domain ontologies. This technique is also referred to as skill matching, with an analogy of machine capabilities to human skills. To successfully introduce this and other AI‐based methods into production for making machines more autonomous, techniques of explanation are required to establish transparency on AI‐based decision making. 
  • Use case goal: To show how the use of ontologies and reasoning can significantly improve flexibility in manufacturing, as well as increase transparency and trust of AI systems by using methods for explaining AI‐based decision‐making.
  • Industry domain: Manufacturing.
  • Proposer: Siemens AG.


Additional Demonstrators committed to OntoCommons

A list of the EU projects already committed to OntoCommons, with their respective demonstrator cases, is shown in the following table. The list is expected to increase during the project. 

Name Domain Project
Materials and Nano-Materials Synthesis Materials Modelling SimDOME (EMMO-based Open Simulation Platform)
Molecular Spectroscopy Materials Modelling and Characterization SimDOME (EMMO-based Open Simulation Platform)
Chemical Kinetics Chemistry SimDOME (EMMO-based Open Simulation Platform)
Post-launch analysis of pouch detergents Materials Modelling OntoTrans (EMMO-based Open Translation Platform)
Detergent pouch system Product development OntoTrans (EMMO-based Open Translation Platform)
Composite prepreg Materials development OntoTrans (EMMO-based Open Translation Platform)
Section mill Process control OntoTrans (EMMO-based Open Translation Platform)
AI-based predictive maintenance of wind farm AI, Big Data, modelling, machine learning for industry 4.0 IoTWINS (H2020 Big Data innovation action)
Wide-scale smart grid management in a smart city environment AI, Big Data, modelling, machine learning for industry 4.0 IoTWINS (H2020 Big Data innovation action)




Do you have a demonstrator that describes the OntoCommons Ontology Commons EcoSystem (OCES)? We'd be keen to hear from you!

Apply to the open call and become the new OntoCommons Demonstrators