Ontotext announced Ontotext Platform 3.4 for better search and aggregation in knowledge graphs. Key to the Ontotext Platform is the declarative approach for access and management of large-scale knowledge graphs (KG). This allows engineering teams to define specific GraphQL interfaces to read and write data over parts of a knowledge graph and let the Platform implement an efficient translation of GraphQL to SPARQL.
Ontotext Platform 3.4 combines GraphDB, Elasticsearch and GraphQL by enabling the definition, automatic synchronization and querying of indices to boost the performance of specific queries. The Workbench front-end tool of the Platform features a new generic search interface for KG exploration and navigation. The new version of the Semantic Object service delivers better performance to execute big and data-intensive GraphQL queries on top of GraphDB.
The new Semantic Search Service enables software engineers to easily accomplish some of the capabilities over a knowledge graph that are most required by SMEs such as Full-text Search (FTS), Auto-complete/typeahead (related concepts and controlled vocabulary), Auto-suggest (related keywords and phrases), Faceted search, complex dashboards using different statistical and/or bucket aggregations, etc. The provided GraphQL endpoint will enable users not only to search in the data but also to retrieve the data for the result list directly from Elasticsearch.