Ontotext, a provider of enterprise knowledge graph and semantic database engines, has updated Ontotext Metadata Studio (OMDS), a tool designed for knowledge graph enrichment through text analytics of unstructured documents.

Version 3.8 aids in the creation, evaluation, and quality improvement of text analytics services. With more intuitive and effective search solution capabilities, enhancement to OMDS removes the difficulties users face when exposing semantic search over their documents, especially when they are working with their own, custom reference domain models.

"Ontotext Metadata Studio was purposefully designed to enable users to quickly and efficiently find the exact documents they need at all times, no matter how elaborate the search criteria, to ensure a user-friendly experience,” said Borislav Ankov, product owner of Metadata Studio at Ontotext.

“This latest version allows users to navigate through complex business scenarios seamlessly with a combination of full-text search and specific domain-related filters, whether it's a combination of gene and protein in life sciences, a specific product with unique features in product information management, or a CV with a particular set of skills. Equally important is that documents are now discoverable through a person's own tailored domain models, regardless of what the business domain is which further supports user self-service." 

New features and updates with Version 3.8 include:

• Enhanced domain model search interface transforms the reference annotation schema into a user-friendly search interface, allowing seamless exploration and retrieval of content based on the preferred domain data model. Users can now effortlessly find and utilize the rich and extensive data models they have created and take advantage of various object classes such as documents, concepts, annotations, and the intricate relationships between them.

• Knowledge graph enrichment and extension enables users to reuse their domain models for more than just search and exploration. These models can be leveraged for advanced analytics and quality management, enhancing the enrichment and extension of the knowledge graph. The corpus-wide full-text search capabilities, combined with annotation schema filters, allow for sophisticated search queries that can identify priority documents for human review, additional metadata enrichment, or correcting automated extraction errors.

• Advanced search capabilities support all types of searches. The solution allows users to conduct simple searches such as identifying documents containing specific text as well as complex queries that filter documents based on the presence or absence of certain text and combinations of metadata objects and property values. This advanced search functionality supports efficient content discovery and knowledge graph extension.

• Improved usability and workflow efficiency enables users to organize content effortlessly by moving documents between corpora or deleting them from the database. Users can also rerun the latest analytics configurations without manual setup, saving valuable time and effort.

https://www.ontotext.com/products/ontotext-metadata-studio/