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  • Knowledge Graph Applications
  • Text Analysis for Content Management
  • Connected Inventory

Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model

  • Benefits
  • KG Applications Map
  • Main Applications

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Showcase Demonstrator
White PaperKnowledge Graphs in the Enterprise: The Story Behind the Hype

Interlink your organization’s data and content by using knowledge graph powered natural language processing with our Content Management solutions.

  • Features
  • Case Studies
  • Showcase Demonstrators

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Showcase Demonstrator
White PaperText Analysis for Content Management

Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.

  • Typical Data Assets
  • Case Studies

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Case Study
Case StudyA KG-Powered Connected Inventory for a Global Bank

  • Healthcare & Life Sciences
  • Financial Services
  • Industry
  • Media & Publishing
  • Public Sector
  • Retail

Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more

  • Business Applications
  • Case Studies
  • LinkedLife Data Inventory
  • Showcase Demonstrators
  • News, Events & Blog Posts

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Target DiscoveryIdentify New Drug Targets Or Promising Drug Repurposing Candidates Quickly And Easily

Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more

  • Business Applications
  • Case Studies
  • Showcase Demonstrators
  • GraphDB with FIBO Training
  • News, Events & Blog Posts

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WhitepaperExplore the Finacial Industry Business Ontology (FIBO) with GraphDB

 

Connect and model industry systems and processes for deeper data-driven insights in:

  • Manufacturing
  • Automotive Industry
  • Energy
  • Building Automation
  • Infrastructure
  • Aerospace & Defense
  • Business Applications
  • Case Studies
  • Showcase Demonstrators
  • News, Events & Blog Posts

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Showcase Demonstrator
Energy Transparency Knowledge Graph

 

Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.

  • Business Applications
  • Case Studies
  • Showcase Demonstrators
  • News, Events & Blog Posts

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White PaperSmarter Content with a Dynamic Semantic Publishing Platform

 

Unlock the potential for new intelligent public services and applications for Government, Defence Intelligence, etc.

  • Business Applications
  • Case Studies
  • Clients Services
  • News, Events & Blog Posts

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Case StudyUK Parliament’s Data Service Are Powered by Ontotext’s GraphDB

Connect and improve the insights from your customer, product, delivery, and location data. Gain a deeper understanding of the relationships between products and your consumers’ intent.

  • Benefits
  • Business Applications

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Blog PostKnowledge Graphs for Retail

 

  • Ontotext GraphDB
  • Ontotext Platform
  • Ontotext Metadata Studio
  • Ontotext Refine

Link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.

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Download GraphDB

  • Release Notes
  • Quick Start Guide
  • Documentation

Organize your information and documents into enterprise knowledge graphs and make your data management and analytics work in synergy.

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  • Request a License
  • Release Notes
  • Quick Start Guide
  • Documentation

Integrate and evaluate any text analysis service on the market against your own ground truth data in a user friendly way.

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  • Get In Touch
  • Installation
  • Configuration
  • Release Notes

Turn strings to things with Ontotext’s free application for automating the conversion of messy string data into a knowledge graph.

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  • Download Now
  • Installation
  • Release Notes
  • Data Loading
  • RDF-izing Tabular Data

Knowledge Hub

Fundamentals

  • Fundamentals
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  • Fundamentals

    What is Text Analysis?

    Text Analysis is about parsing texts in order to extract machine-readable facts from them. The purpose of Text Analysis is to create sets of structured data out of heaps of unstructured, heterogeneous documents.

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  • Fundamentals

    What is Metadata?

    Metadata represents data about data and enriches the data with information that makes it easier to find, use and manage. Semantic metadata helps computers to interpret data by adding references to concepts in a knowledge graph.

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  • Fundamentals

    How-to: GraphDB Fundamentals in 10 steps

    GraphDB Fundamentals builds the basis for working with graph databases that utilize the W3C standards and particularly GraphDB. It is a training class delivered in a series of ten videos that will accompany you in your first steps of using triplestore graph databases.

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  • Fundamentals

    What is SPARQL?

    SPARQL enables users to query information from databases or any data source that can be mapped to RDF. The SPARQL standard is designed and endorsed by the W3C and helps users and developers focus on what they would like to know instead of how a database is organized.

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  • Fundamentals

    Relational vs Property Graphs vs RDF Databases at a Glance

    How to choose the best data management solution? Here is a quick comparison between some of the major players in the game: Relational databases, Property graphs and RDF databases.

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  • Fundamentals

    What is an RDF Triplestore?

    The RDF triplestore is a type of graph database that stores semantic facts in RDF. It stores data as a network of objects with materialized links between them. Being very flexible and cost-effective, it is the preferred choice for managing highly interconnected data.

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  • Fundamentals

    What is Semantic Annotation?

    Semantic annotation is the process of attaching additional information to various concepts (e.g., people, things, places, organizations, etc.) in a given text or any other content. Unlike classic text annotations, which are for the reader’s reference, semantic annotations are used by machines.

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  • Fundamentals

    What Is Semantic Search?

    Semantic search bridges the language gap between humans and machines, and takes us further on our quest for meaningful information and knowledge discovery.

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  • Fundamentals

    What is Semantic Data Integration?

    Semantic data integration is the process of combining data from disparate sources and consolidating it into meaningful and valuable information through the use of Semantic Technology. With Ontotext’s semantic integration tools, users can quickly design data processing jobs and integrate massive amounts of data.

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