Research

USPs

Sure, I can help you with that. Here is a list of the main USPs of the products on this website:

Ontotext Platform: A platform for organizing and analyzing information and documents into enterprise knowledge graphs. It allows you to:
- Connect and publish complex enterprise knowledge with a semantic graph database
- Customize and apply analytics to link documents to graphs, extract new facts, classify and recommend content
- Access data via GraphQL to ease application development
- Generate semantic metadata and extract knowledge from unstructured documents
- Efficiently generate SPARQL queries without writing and optimizing complex queries
- Integrate applications, including non-semantic sources, using federation, schema stitching and data virtualization
- Adopt developer friendly tooling and user interfaces
- Use authorization and authentication for controlling information access
- Scale data, query and transaction loads via integration with ElasticSeach and MongoDB
- Run a cloud-agnostic deployment with Kubernetes
Ontotext GraphDB: A leading RDF database for knowledge graphs, which makes it easy to:
- Link diverse data, perform inferencing at scale and search semantic knowledge
- Support ontologies, reasoning and semantic integration
- Preserve the information metadata, source and provenance
- Put all data into the right context to enable deep data and analytics
- Employ the most robust database engine for knowledge graphs, featuring reasoning, semantic similarity and ranking
Ontotext Workbench: A manual annotation tool that enables organizations to:
- Integrate and evaluate any text analysis service on the market against their own ground truth data
- Create custom annotation schemas and workflows
- Manage annotation projects and teams
- Export annotated data in various formats
Ontotext DataLift: A free application for automating the conversion of messy string data into a knowledge graph. It allows you to:
- Import data from CSV, JSON or XML files
- Define mapping rules using a graphical interface or SPARQL queries
- Apply transformations and enrichments to the data
- Export the resulting knowledge graph in RDF format

I hope this helps you understand the products on this website better. 😊