Ontotext Demo Day is a 4-hour virtual event showcasing product updates and new offerings. Save the date and learn about the new GraphDB 10 cluster, the new Metadata Studio and our tooling for data reconciliation and semantic tagging!
Several vertical solutions will be presented: from Target discovery (Pharma) to Transparency graph (Energy) and Company graph (Financial Services). The latter demonstrates bootstrapping of a proof-of-value knowledge graph, which leverages an existing ontology (FIBO) and third-party reference data (GLEI) to smarten up proprietary data.
The event is suitable for a wide range of personas:
Expect to see new features and major improvements in deployment and migration, in the Connectors, in license handling and the GraphDB 10 crown jewel – cluster management based on Raft consensus algorithm, quorum-based voting and leader election.
Suitable for: Current & Future Users of GraphDB
Suitable for: Information & Solution Architects
Go on a walkthrough of some key OMDS features that enable:
Suitable for: NLP Engineers, Data Scientists, Non-Technical SME, Knowledge Workers, Business Analysts
Watch us clean up a tabular dataset with OntoRefine, set up a project-specific reconciliation service on top of an existing knowledge graph and use it from the OntoRefine project to match strings in the source data to entities in the knowledge graph. The enriched data will then be converted to RDF, using the Visual RDF Mapper, and imported into the existing knowledge graph in the GraphDB repository.
Suitable for: GraphDB Users, ETL Enthusiasts, Graph Data Scientists
Go on a walkthrough of some key Tag Essentials features such as easy use of tagging functionality from scratch, making use of existing third party tagging functionality and evaluating the quality of that tagging according to your guidelines and standards. The entry-level, out-of-the-box functionality enables the bootstrapping of a text analysis offering without relying on the complex, and usually expensive, prerequisites for creating such offerings.
Suitable for: Non-Technical SMEs & Taxonomists (who want to bootstrap tagging functionality against their own taxonomy from scratch)
Although graphs are the best place for your semantic model, reference data, annotations and entity records, they are not the most effective structure to store such data. Learn how semantic mapping and transformation are a great introduction to the added value provided by the graph modeling on top of “traditional” relational data.
Suitable for: Information & Solution Architects, Developers (who consider a switch to graph technologies)
Learn how you can unlock relevant information and insights in both structured and unstructured reference data sources, mapped and managed in a central knowledge graph. This makes it easy to extract information about any entity and context of interest in seconds. It’s also easy to apply customizable algorithmic and visual analytics on top of the data model for in-depth insights and critical decision support.
Suitable for: Pharma & BioTech Researchers, Data Analysts, Scientists
Tune in to learn how we have implemented a number of advanced validations over fundamental electricity data such as Energy Identification Code files, power plant data and specific market data. Find out how knowledge graphs can help ENTSO-E and national electricity authorities (Transmission System Operators, TSO) diagnose data quality problems and improve data collection procedures and legislation.
Suitable for: Data Scientists, Network Engineers, Data Architects & Analysts