The document discusses semantic technology, focusing on its definitions in linguistics and philosophy, as well as its applications in information technology. It describes how ontologies represent knowledge within a domain and the advantages of using directed graphs for knowledge representation. The text also highlights the importance of the semantic web and its driving forces, including linked open data and the usage of knowledge graphs by Google for enhancing search results.

1. Semantic technology
In nutshell
Heimo Hänninen 22.10.2013

2. You said semantic - are you a linguist?
In Linguistics
• Phonology = systematic organization of
sounds in languages
• Morphology = the identification, analysis
and description of the structure of a given
language
• Semantics = the study of meaning of
words and sentences
• Pragmatics = studies the ways in which
context contributes to meaning (e.g. irony,
politicians language)
Philosophy
• Ontology = is the philosophical study of
the nature of being, becoming, existence,
or reality
Semantic technology (IT)
• Ontology = formally represents knowledge
as a set of concepts within a domain, and
the relationships between those concepts
• Semantics = encodes meanings separately
from data and content files, and separately
from application code (often utilize
computational linguistics)

3. Directed graph – a Lego blog of semtech
• Set of nodes connected by edges, where the edges have a
direction associated with them.
• These expressions are known as triples in RDF terminology:
subject  predicate  object.
• The concept is better suited for certain knowledge
representation than relational model.
Heimo
This picture
Has created

4. Creating ontology: using directed graph
ASPEN, an industry-leading Advanced
Service Platform for Ethernet Networks
A-2200
Access
Aspen
A-2200
Service
platform
Access
is a type of product
contains a product
is a type of product
Ethernet
Networks
is applicable for

5. Format of data may change – semantics are
retained. Example:
Table Network transformed:
1. Create access to DB
2. Engine analyses Network table and then
3. Transforms data and context as graph and then
4. Merges related data from other sources
Network
System Node Node
Function
Alpha Node-A Access
Alpha Node-B Billing
Beta Node-X Authorize
Alpha
System
Node-B
Node-A
Billing
Network
contains
is type of
contains
contains
has function
Alarm
triggered by

6. Search on ontology – instead of system
integarations
With semantic technology the integration of information is easier
and a lot cheaper to do since:
• harmonized model across systems, organizations and data
processes can be created “above the system space” without
complex data integrations
• semantic engine comes with content analysis capabilities
• semantic engine comes with query capabilities, which enables
fast and effective search style data integration
• semantic engine often provides an inferring tool for reasoning
(what if –analysis etc.)

7. W3C: Semantic Web: Data on the Web
Machine-processable, global
Web standards:
• Assigning unambiguous
names (URI)
• Expressing data, including
metadata (RDF)
• Capturing ontologies (OWL)
• Query, rules, transformations,
deployment, application
spaces, logic, proofs, trust

8. Semantic web today
Key driving forces are:
1. Linked Open Data as concept for “hyper data”
2. http://schema.org/ for SEO and
3. Programmable Web as a global API for cloud age.
Of course more to come…
Google search has been using knowledge graphs for more than
a year to bring up “things – not just strings” in the search results
(thanks to Freebase integration). Read more.