Ontotext Platform 3.3 Streamlines the Building of Knowledge Graph Lenses and GraphQL Interfaces

The new version of the Platform introduces a web-based administration tool that enables engineering teams to generate, enrich, validate and manage knowledge graph schemas

SOFIA, Bulgaria, Nov. 20, 2020 /PRNewswire/ -- Ontotext Platform 3.3 comes with a major new component included - Ontotext Platform Workbench - the web-based administration interface to the platform. It simplifies the work of the subject matter experts by lowering the burden of knowing all platform configuration endpoints and commands and streamline the adoption process by introducing an intuitive graphical interface.

One of the most important features of Ontotext Platform Workbench is the ability to generate, validate and manage schemas using a wizard that guides the user through the process step by step.

During the process of generating a schema the new Platform Playground allows the user to enrich the schema, validate it, correct errors and warnings and save the new schema.

Ontotext Platform allows you to have multiple schemas so that one can easily create different versions, representing different views over the knowledge graph, and use them to generate specific GraphQL end-points.

Based on users permissions, which can be defined in the platform, they will be able to view, activate, update or delete a schema using the Schema Registry or the Platform Playground. For the current active schema the user can write and execute GraphQL queries and mutations using the integrated GraphQL development tool.

Schemas, comprised of declarative definitions of semantic objects, are at the heart of the zero-code approach for access and management of knowledge graphs in Ontotext Platform 3. These schemas act like a lens to focus on specific parts of a large-scale knowledge graph, enabling querying and updates via GraphQL interfaces. This makes it easier for application developers to access knowledge graphs without tedious development of back-end APIs or complex SPARQL. The underlying Semantic Object service implements an efficient GraphQL to SPARQL translation as well as a generic configurable security model. Data can be modified and validated against configured data shapes with simplicity and ease.

In earlier versions the setup of the Platform license required some technical skills, and often users without a strong IT operations background had difficulties configuring the license in the docker compose file. With the new version all users can use the Workbench and set up the license much easier and avoid issues related to license path, operation system specifics and others.

Ontotext Platform makes data management and analytics work in synergy, enabling enterprises to connect, manage and share knowledge models and data, as well as to customize and apply analytics in order to link documents to graphs, extract new facts, classify and recommend content. The platform enables organizations to build, use and evolve knowledge graphs as a hub for data, metadata and content. Ontotext Platform builds on top of and extends the capabilities of Ontotext GraphDB - the leading database engine for management of knowledge graphs. It incorporates a set of databases and search engines and provides the operations infrastructure, APIs and tools needed for a variety of applications.

In the recent Gartner's Hype Cycle of Artificial Intelligence 2020, includes Ontotext as one of the exemplar vendors list for knowledge graphs. Ontotext is also on the list of vendors supporting knowledge graph capabilities in their "2021 Planning Guide for Data Analytics and Artificial Intelligence" report.

About Ontotext

Ontotext is a global leader in enterprise knowledge graph technology and semantic database engines. Ontotext employs big knowledge graphs to enable unified data access and cognitive analytics via text mining and integration of data across multiple sources. Ontotext GraphDBтм engine and Ontotext Platform power business critical systems in the biggest banks, media, market intelligence agencies, car and aerospace manufacturers.

Ontotext technology and solutions are spread wide across the value chain of the most knowledge intensive enterprises in financial services, publishing, healthcare, pharma, manufacturing and public sectors. Leveraging AI and cognitive technologies, Ontotext helps enterprises get competitive advantage, by connecting the dots of their proprietary knowledge and putting in the context of global intelligence.

As member W3C, EDMC, ODI, STI, Linked Data Benchmark Council and DBPedia foundation, Ontotext supports the development of the next generation technology trends and standards. With hundreds of scientific publications and thousands of citations and followers, Ontotext's thought leadership extends to text analytics, semantic search and reasoning.

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