- [Instructor] I would like to give you
a simple definition of the term knowledge graph.
A knowledge graph is a machine readable representation
of a knowledge domain, which can be read and processed
by humans as well as by machines.
The human user receives the results of the knowledge graph
as a textual or visual representation of the relationships,
for example, in a diagram.
Knowledge graphs are also often visualized
using graph diagram.
This is the example of a knowledge graph
that contains scientific information about COVID-19.
Data of different sources is linked together
in order to analyze research publications' statistical data
and patents.
In this example, we see the knowledge graph
of a geology domain, which for example,
displays information about the rock type marble
in text form.
In addition, the information is displayed in a map
that shows the location.
In this example, we see the knowledge graph
for geoscience from Austria.
It contains a controlled vocabulary about types of rocks
and locations in Austria.
We can find information about the rock type marble,
and the knowledge graph can be visualized
as network, diagram or as a map,
which shows the location of the rock type.
An important feature of knowledge graphs
is that they can be used for data analytics.
This allows automated evaluation and use of knowledge.
For example, for machine learning
or for the automated classification of content.
The origins of the knowledge graph technology
are more than 20 years old.
In 1997, the RDF format was standardized.
In 2004, the Web Ontology Language.
And in 2008, the query language SPARQL followed.
In 2012, Google presented its knowledge graph technology.
The JSON-LD format was published in 2014.
And since 2019, Microsoft has presented several services
in the knowledge management area, for example,
Microsoft Graph, SharePoint Syntex and Viva Topics.