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. It’s not just about tech - each of these are about cultural and process change - and at their core, what all of these ideas have in common is that they’re all based off of a Knowledge Graph, operating at several layers of abstraction (sometimes simultaneously).
Social media as infrastructure for public discourse provide valuable information that needs to be preserved. Several tools for social media harvesting exist, but still only fragmented workflows may be formed with different combinations of such tools. On top of that, social media data but also preservation-related metadata standards are heterogeneous, resulting in a costly manual process.
Question-answering (QA) systems are able to provide fast, precise and comprehensive answers to natural language questions. This technology is already widely adopted and now rapidly gaining importance in the business environment, where the most obvious added value of a conversational AI platform is improving the customer experience. In this talk, we present QAnswer, a platforms that allows the construction of Question Answering Systems on top of RDF Knowledge Graphs. The focus is on domain-specific use cases that demonstrate how this solution creates added value for an enterprise.