TUTORIAL

Accelerate your Knowledge Graph journey!

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Knowledge graphs are large networks of entities and their semantic relationships. They are a powerful tool that changes the way we do data integration, search, analytics, and context-sensitive recommendations. Knowledge graphs have been successfully utilized by the large Internet tech companies, with prominent examples such as the Google Knowledge Graph. Open knowledge graphs such as Wikidata make community-created knowledge freely accessible. On this tutorial page we try to bring knowledge graphs a little bit closer to end users and ease the onboarding process into the world of knowledge graphs and connected data.

Knowledge Graph Tutorials

"Getting Started" Tutorial

This tutorial provides an overview of metaphactory's out-of-the-box features for knowledge graph exploration and data discovery. By the time you are done, you will have learnt how to:

  • Load data into metaphactory
  • Search the dataset
  • Visualize and explore the dataset and capture discoveries about it

This tutorial will require 10 minutes during which you'll do lots of hands-on tasks with immediate results.

"Ontology Authoring" Tutorial

This tutorial will show you how to use the Ontology Catalog and Visual Ontology Editor available in metaphactory. By the time you are through with the tutorial, you will have learnt how to:

  • Manage ontologies as knowledge graph assets;
  • Visualize ontologies;
  • Create and edit ontologies.

This tutorial will require 10 minutes during which you’ll do lots of hands-on tasks with immediate results.

Audience

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Semantic Web novices who want to understand basic concepts and value adds delivered by knowledge graphs
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Educators such as lecturers and professors who want to introduce practical exercises into their own lectures
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Knowledge Graph practitioners who want to accelerate their projects - in the industry or in academia

Explore a Live Knowledge Graph

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The Wikimedia Foundation's Wikidata project aims at building a free linked database providing the data contained in Wikipedia in a structured, machine-processable format. Since the official launch of the Wikidata project in 2012, the Wikidata community has gathered and stored several hundred millions of cross-domain knowledge facts about persons, places, artifacts, terms, links to Wikipedia pages, and many more.

The Wikidata knowledge graph is a valuable resource for the community and metaphacts is working in close cooperation with the Wikimedia Foundation to help others utilize the knowledge that is created within the Wikidata project.

With our metaphactory demo instance hosted on top of Wikidata, we provide a generic platform that allows customers to access the Wikidata free corpus of structured knowledge and seamlessly integrate their enterprise data with open data, thus being able to contextualize their internal knowledge and develop own, customized applications on top. The system provides different search interfaces as entry points into Wikidata's knowledge base and visualizes search results based on a comprehensive HTML5-based templating approach.

 

Have a look at our public demo system to experience the power of the Wikidata knowledge graph. You can get started with these examples:

Rhein-Neckar Smart Data Meetup

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If you're interested in getting more value out of your data, then join our group of industry professionals and academics!

In this group, we discuss all issues relevant to data integration, linked data, open data and extracting knowledge from data, with a particular emphasis on knowledge graphs, semantic technologies, graph databases, and so forth. We are happy to talk about smart data both on the (open) Web and within enterprise networks.

Get started today!