Industry

In this presentation we describe the data processing workflow and querying approach of an online, customer-facing application for the interactive sizing of automation solutions from Festo, a global leader in factory automation.

Graph Neural Networks (GNNs) have emerged as a mature AI approach used by companies for Knowledge Graph enrichment via text processing for news classification, question and answer, search result organization, and much more. During this presentation we will discuss the advantages of GNNs for text classification and relationship extraction for Enterprise Knowledge Graphs.

Do you need a Data Mesh? Are you missing the boat without a Data Fabric? Maybe you “just” need a Data Catalog? There’s an ever-increasing list of terms associated with various technologies, patterns, and concepts meant to help you make sense of your organization’s data.

The Semantic Web provides a graph-based organisation of knowledge that has become popular in enterprises under the term enterprise knowledge graphs. It allows a lot of flexibility for modeling as well as combining data sets by linking graphs together, which has the potential to solve enterprise data heterogeneity problems in a bottom-up and flexible manner.

This presentation shows the challenges a large engineering contractor has with the diversity of the data handled in constructing process plants. Fluor discusses how they have joined a cooperation of 80 companies to design a data model, and to help author an ISO standard based on semantic web technologies.

The COVID-19 pandemic is a showcase for a data-driven society. Hence, the German government was aiming to provide free access to COVID-19 data to all citizens. However, making the corresponding data accessible by non-experts is not easy due to local characteristics and time-dependent metrics (e.g., the data is only collected on district level).

Ontologies are one of the main ingredients for building Knowledge Graphs. As part of our mission, eccenca develops and deploys Enterprise Knowledge Graphs based on eccenca Corporate Memory for its customers. In this talk, we will give an overview of eccenca's Ontology Engineering process. The presentation outlines how ontologies are developed, tested, and utilized.

How can you find information in heterogeneous sources, available at different locations and managed by different owners? In the Dutch Digital Heritage Network (NDE) we are working on a distributed solution for this: the Network of Terms. We encourage our institutions to assign standardized terms to their digital heritage.

In this presentation we describe how we developed modules and pipelines for the industrial processing of data and content from a machine learning project in the legal domain. Lawyers’ work is far from being digitized. They need to deal with large amounts of printed documents of various types (e.g. letters, contracts, invoices, orders, offers, court documents).

Many industries and organisations face challenges with complexity. Many Firms in Financial Services are overwhelmed by complexity - complex, clients, products and markets, legacy technologies, acquisitions, regulations - and on top of it all, change as a constant.