Responding to these challenges, the OntoTrans project has developed and tested the Open Translation Environment (OTE). OTE is aligned with, adapts and builds on recent advances in semantic and AI technologies, which are fast becoming a de facto ‘standard’ for building ‘data centric’ knowledge management systems across different industries.
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(öffnet in neuem Fenster)) journal publications, conference presentations, social media and the software components are available via public repositories such as github.
