Periodic Reporting for period 3 - OntoTRANS (Ontology driven Open Translation Environment)
Okres sprawozdawczy: 2023-04-01 do 2024-07-31
The objectives of OntoTrans have been to strengthen the use of so-called "translation" as a router supporting end users to get to relevant data and models, improve decision making processes and preserve/re-use knowledge by:
1. representing manufacturing process challenges in a standard ontological form as technical and business user cases
2. connecting user cases with existing appropriate information sources i.e. available data and materials modelling solutions
3. recommending consistent materials modelling workflow options
4. supporting simulation and validation activities
5. providing semantic results interpretation to facilitate sharing and re-use of user cases and results
Figure 1 Translation steps
The integration of a wide range of data sources as well as models is considered future critical for more agile and sustainable product development and use throughout the entire materials life cycle. It is aligned with the drive for a digital society that assists in developing a circular economy and addresses societal needs. OntoTrans, due to its ontological foundation, delivers deep digitalisation of innovation challenges and provides efficient information and knowledge management. It becomes a place for information exchange on key issues concerning materials innovation in industrial applications. Materials and process modelling become integrated together with experimentation, characterisation, and machine learning (ML) as knowledge sources of emerging digital R&D systems and will therefore contribute to delivering on the promises of AI applications in R&D.
OTE provides the end user with easier access not only to a wide range of data, but also to models, enabling “what-if” scenarios to be explored. The description of the data is mapped onto an ontology as a reference ‘standard’. The Elementary Multiperspective Material Ontology" (EMMO), co-developed by OntoTrans, is the framework that supports expressing innovation challenges in human and machine readable form. They are stored in the OTE knowledge base (OntoKB), which connects the various data sources and models. OntoTrans has built new data integration and pipelining systems to ease the flow of information between different stakeholders. End user applications were built for four industrial innovation challenges. They provide advanced search and data analytics capabilities to speed up the process of choosing and developing materials.
The OTE software architecture has been collaborative developed and refined. It provides a detailed view on the OTE components and their functional responsibilities and shows how these map onto the translation process. Regarding the development of specific OTE components, the following is noted:
(a) As semantic foundation, the EMMO ontology at the top and middle level has been advanced up to a release candidate version. The parts of EMMO dealing with models, workflows, validation and verification, and the representation of materials and materials processes have been further developed and alignments with other ontologies reported on.
(b) Knowledge base (OntoKB and OntoRec) has been released with APIs and flexibility to use different types of triple store.
(c) Interfaces to all types of sources of information have been released, including interfaces to materials databases (via Optimade), simulation platforms, marketplaces and to specific data sources required for the application cases.
(d) OTEAPI, a flexible and modular system for data documentation and dataflow orchestration has been released. It facilitates seamless information transfer between heterogeneous computer systems, while simultaneously ensuring the information is accurately interpreted and understood.
(e) Exploratory Search System: The ESS has been enhanced with a more solid back-end implementation and integration with OTE tools and with the GUI
(f) Data analytics implementation in the end user applications
(g) Graphical interface, wizard: A GUI and wizard for executing the application cases has been developed and released in its final form to the industrial partners.
Figure 2 OTE Architecture
Interaction with other projects, in particular Open Innovation Platforms that also utilise ontologies has been very close, facilitated by regular meetings, EMMC Task Groups and joint workshops.
The results of the OntoTrans are already being exploited in other EU-funded projects, such as MatCHMaker and OpenModel, and a commercial exploitation of the EMMO developments and the OTE concept is planned by project partners in a “Semantic Materials” initiative. The project results have been disseminated via an overview paper (see https://zenodo.org/records/13304677) journal publications, conference presentations, social media and the software components are available via public repositories such as github.
The project ambition is to be a blueprint for R&D digitalisation of research intensive, high-value-add industries in Europe. Key to that is a strong semantic basis. OntoTrans progressed beyond the state-of-the-art with the following innovations:
- "Semantic Materials" , a conceptualisation framework and ontology f(EMMO) able to capture all aspects of chemistry, materials and manufacturing innovation challenges and related data. A conceptualisation methodology has been developed and is already used also in other projects as a starting point for implementation of the concepts in an ontology.
- Knowledge base systems and recommendation system
- Data pipelining and interfaces providing flexible data documentation and dataflow orchestration
- Robust exploratory search system with connection to ontologies and ready for industrial applications
- End user application workflows and implementations.
OntoTrans OTE provides industry an effective means to widely benefit from a data- and model-driven approach for a better understanding of processing, properties and characterisation from chemistry to application performance. This will subsequently cut cost and time by avoiding unnecessary experiments, better targeting and reduced usage of expensive and dangerous materials. Furthermore, the ability to invest resources in a more targeted and effective way will be increased. OntoTrans is synergistic with developments in semantic technologies, AI and industry digitalisation, leading to smarter decisions and efficient use of resources.