17. July 2023
From September 20 to 22, 2023, the SEMANTiCS Conference – the leading European conference on Linked Data, Semantic AI and Data Science – will once again take place in Leipzig. An inspiring program for experts, decision-makers and researchers invites you to exchange ideas about new technologies, innovations and company implementations.
As a Gold Sponsor, PANTOPIX will once again be on site with an exhibition stand and two exciting presentations. Together with Klaus Müller and Andreas Pawlik from ZEISS Microscopy, Maximilian Gärber, Partner and Technical Consultant at PANTOPIX, will give an insight into our pioneering project.
In addition, Dr. Martin Ley, Partner and Consultant at PANTOPIX, and Johann Wagner, Knowledge Engineer, will report on the creation of a knowledge model in the pharmaceutical industry.
We are looking forward to an exchange at our stand: many colleagues will be on site in Leipzig and are looking forward to getting to know each other and an exciting event with new input on semantic technologies.
We have answered a few questions about semantics and AI-powered applications. Read the interview here.
Our expert lectures
21.09.2023 | 11.45 a.m.
Intelligent Service Agent at ZEISS
Speakers: Andreas Pawlik, ZEISS Digital Partners, Maximilian Gärber, PANTOPIX
We present the intelligent service agent that was implemented at Zeiss. This is a knowledge graph-based recommendation service that guides service technicians to the location where they are needed. The agent is fed from various data sources, from technical documentation to spare parts lists and maintenance reports. The presentation illustrates the project from data acquisition to data enrichment and machine learning to predictive maintenance.
22.09.2023 | 11.00 a.m.
Knowledge Models as Silver Bullet for Quality Intelligence
Speakers: Dr. Martin Ley and Johann Wagner, PANTOPIX
In many highly regulated industries, especially in the pharmaceutical industry, controlled vocabularies are state of the art. In addition, companies usually provide their own terminology. Both internal and standard vocabularies can refer to different concepts and are subject to change over time.
This situation often makes it a Herculean task to compare labels and/or concepts, update vocabularies, track changes and finally use controlled vocabularies for downstream processes such as information retrieval and information provision. For example, a content management system may contain tags from previous versions of the vocabulary, and users need to de-reference these labels or track their lifecycle.
In this presentation, we will show how we solved these challenges for an industrial partner in the pharmaceutical industry with its high demands on data quality and the validation of systems and processes. We will show how we combined public and self-created ontologies, integrated vocabularies from different sources and integrated versioning mechanisms based on PROV-O into our knowledge model. In addition, we show how a query module is integrated into the customer’s workflows, which forms the basis for future applications such as autoclassification, information retrieval and intelligent information provision.
