Earlier this year, the Semantic Layer Symposium in Munich brought together industry leaders, data scientists, and Knowledge Management (KM) experts to explore cutting-edge developments in data integration and AI-driven insights. This groundbreaking event fostered lively discussions on the future of semantic layers, knowledge management, and the role of AI in transforming data practices. We’re excited to release these discussions for viewing, offering insights from top voices in the field and paving the way for innovative applications of semantic layer technology.

In this presentation, Daniel Canter, Head of Knowledge Management at ASML, outlines the company’s challenges and approaches in developing an effective semantic layer for knowledge management. ASML, a leader in semiconductor manufacturing, has experienced rapid growth, with 60% of its workforce joining within the last four years. This influx of talent has created a fragmented landscape where information is difficult to locate, knowledge is siloed, and terminology varies across departments.

To address these complexities, Canter emphasizes ASML’s three primary knowledge management objectives: facilitating content accessibility, fostering person-to-person connections, and ensuring content relevance at the point of need. He explains that ASML’s unstructured data is vast and disorganized, making it challenging for employees to find critical information efficiently. A semantic layer, therefore, is essential to structure and connect data across departments and systems, enhancing the company’s ability to automate processes and support performance.

Canter introduces ASML’s strategy to build a centralized, AI-driven semantic layer. This layer will harmonize language across the organization, enabling clear term definitions and bridging disparate systems and data sources. By aligning on taxonomy and integrating both structured and unstructured data, ASML aims to reduce the time employees spend searching for information, increase productivity, and ultimately support innovation in their manufacturing processes. The project, which holds the potential to significantly enhance productivity and reduce employee frustration, is also projected to generate substantial cost savings.