Abstract: The creation and maintenance of knowledge graphs is commonly based on the generation and use of several types of artefacts, including ontologies, declarative mappings and different types of scripts and data processing pipelines, sample queries, APIs, etc. All of these artefacts need to be properly maintained so that knowledge graph creation and maintenance processes are sustainable over time, especially in those cases where the original data sources change frequently. It is not uncommon to have situations where ontologies are governed by an organisation or group of organisations, while mappings and data processing pipelines are handled by other organisations or individuals, using different sets of principles. This causes mismatches in the knowledge graphs that are generated, including the need to update all the associated artefacts (declarative mappings, sample queries, APIs, etc.) so as to keep up to date to changes in the ontologies, or in the underlying data sources. In this talk we will discuss several of the challenges associated to the maintenance of all of these artefacts in real-world knowledge graph scenarios, so as to provide some light into how we could set up a complete knowledge graph governance model that may be used across projects and initiatives.

Abstract: Industry 4.0 is a more than a 10-year-old vision of digitalised, adaptive and resilient industry based on converged IT/OT technologies breaching the gap between engineering and computer science. Over the year an understanding of gaps between different information domains across product and equipment lifecycle and supply chain emerged. Asset Administration Shell (AAS) concept was created to close this gap by implementing Digital Twin concepts for industrial applications. In this talk, I will give a brief introduction into AAS information model, implementations and present some selected pilots and demonstrators making use of this technology.