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Graeme Wood
General Manager Marketing
Enhancing Business Insights
by Liberating your Data
Agenda
• General Introduction of Semantic Software
• Welcome and Introduction to IoT and Big Data
• Introduction to Semantic Computing concepts
• Benefits of Semantic Computing to Government
• Q&A
• Close
Who is Semantic Software
• An Australian Company with HQ in North Sydney
• Owned by over one hundred and thirty private investors
• Developed a Semantic Interoperability Platform
• Created a strong and strategic patent portfolio that has patents &
patent applications in Australia and the United States
• Implemented a training division called Semantic Academy for the
delivery of technical workshops, executive presentations and training
modules for Tertiary Institutions
Evolution of the World Wide Web
Semantic Software 4
Current Data Issues
• CURRENT DATA ISSUES
• Rigid Data Structures
• Distributed Data Sources
• Unstructured Data
• Limited Context , Meaning, Sources
• Growth of Social Collaboration
• Resource Requirements to Manage
How many devices record information?
How much Information does the bank use
to manage clients needs?
How Integrated is Data in Government ?
Internet of Things (IoT)
• The IoT is a giant network of connected
“things” (which also includes people).
• The relationship will be between people-
people, people-things, and things-things.
• ISSUES
• Security
• Technology & Interoperability
• Privacy, IP and Data Sharing
• “Data lake” Storage Requirements
• Unstructured data
• Data interoperability
• Meaningful Analysis of Data
Internet of Things (IoT)
Internet of Things & Cognitive Computing
• IoT is already overwhelming data analytics
• Driving the need for cognitive computing
• Cognitive computing requires
• A semantic knowledge base for meaning
• Natural Language Processing to ingest unstructured data
• Algorithmic methods to make propositions
• Machine Learning to improve propositions
Semantic Software 11
Agenda
• General Introduction of Semantic Software
• Welcome and Introduction to IoT and Big Data
• Introduction to Semantic Computing concepts
• Benefits of Semantic Computing to Government
• Q&A
• Close
Evolution of Data Mining Technologies
What is Semantic Computing
• Semantic Computing is at the core of Cognitive Computing processes, and is
enhanced by other Artificial Intelligence techniques such as Natural Language
Processing and Machine Learning
• Semantic Computing is the facilitator of key IT Tools of the future providing
INTEROPERABILITY and CONTEXT
• The Key elements that engage with Semantic Computing include:
• Internet of Things (IoT)
• Big Data & Analytics
• Cloud Computing
• Collaborative /Social Media
Concepts in Semantic Computing
“I got a great shot
of an elephant at a
zoo.”
Semantic Software 16
Concepts in Semantic Computing – RDF Resources
• Data is transformed into granular facts describing “Resourses”
• These facts are expressed in Subject–Predicate–Object form, called Triples
• Subjects and Objects are Resources
• The Resource Description Framework (RDF) defines the above
• Example:
• “I got a great shot of an elephant at a zoo.”
• Nouns = I, shot, elephant, zoo
• Verbs = got, shot
• Preposition = of, at, are
• RDF Triples generated:
• I got a shot
• I shot an elephant
• I was at the zoo
• An elephant was at the zoo
• The shot occurred at the zoo Semantic Software 17
Concepts in Semantic Computing - Ontologies
• An Ontology is a dataset of “rules” that describe a domain of knowledge
• They use RDF formats
Semantic Software 18
Zoo Ontology FOAF Ontology Photography
Ontology
A zoo houses
animals
I means a person Cameras make
photos
Elephants are
animals
People is the plural
of person
A shot is a photo
People take photos
Semantic Web Stack
• "The Semantic Web is
an extension of the
current web in which
information is given
well-defined meaning,
better enabling
computers and people
to work in
cooperation."
-- Tim Berners-Lee
The “Intelligent” Web
Semantic Software 21
Professor Sir Tim Berners-Lee
(inventor of WWW and Semantic
Web)”
• 1999 “we don’t know how to
do trust, security and proof
• In 2006, TBL and colleagues:
"This simple idea...remains
largely unrealized".
• Rust, security and proof
recently reaffirmed as
“unrealized technologies”
Agenda
• General Introduction of Semantic Software
• Welcome and Introduction to IoT and Big Data
• Introduction to Semantic Computing concepts
• Benefits of Semantic Computing to Government
• Q&A
• Close
Example of Relationship Finder Query
.
25
• Monetary: profit / loss, assets / liabilities, equity
• Law and Jurisdiction
• Government, regulatory environment
• Contracts, agreements, commitments
• Products and Services
• Other e.g. geopolitical, logistics
Key areas for decision making that Semantic Computing supports
Semantic Computing in Finance
• customer-focus
• risk management
• increase flexibility
• combining disparate sources
• regulatory reporting
• insider trading controls
• data governance
• accessing information quickly
Benefits of Semantic Computing to Government
• Comprehensive Interaction with the Public
• Supports Policy Development
• Supports Integrated National Security
• Manages Risk, Governance and Compliance
Semantic Computing in Government
Treatment
Plan/Workflo
w Options
Drugs/
Gene
Interactions
Wearable
Diagnostic
Support
Reduce
Excessive
Payouts
Membershi
p
Engagemen
t
Reduce
Claim Fraud
Correlate
Diverse Data
Sources
Exploit
Specialist
Ontologies
Expanded
Govt
Access and
Sharing
Tailor
Holistic
Treatment
Providers
Payers
Research
Expanded
Analytic
Tasks
Personal
Patient
Files
Consumers
Semantic Computing in Healthcare
• forecast patient behaviour
• provide preventive care
• impact of infections on patients
• identify high volume service users
• determine the probability of readmission
• improve response rates
• identify cardiac failure risk
Semantic Computing in Healthcare
Treatment
Plan/Workflo
w Options
Drugs/
Gene
Interactions
Wearable
Diagnostic
Support
Reduce
Excessive
Payouts
Membershi
p
Engagemen
t
Reduce
Claim Fraud
Correlate
Diverse Data
Sources
Exploit
Specialist
Ontologies
Expanded
Govt
Access and
Sharing
Tailor
Holistic
Treatment
Providers
Payers
Research
Expanded
Analytic
Tasks
Personal
Patient
Files
Consumers
NAVY ENERGY
Case Study : US Navy

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Semantic Computing Executive Briefing

  • 1. Graeme Wood General Manager Marketing Enhancing Business Insights by Liberating your Data
  • 2. Agenda • General Introduction of Semantic Software • Welcome and Introduction to IoT and Big Data • Introduction to Semantic Computing concepts • Benefits of Semantic Computing to Government • Q&A • Close
  • 3. Who is Semantic Software • An Australian Company with HQ in North Sydney • Owned by over one hundred and thirty private investors • Developed a Semantic Interoperability Platform • Created a strong and strategic patent portfolio that has patents & patent applications in Australia and the United States • Implemented a training division called Semantic Academy for the delivery of technical workshops, executive presentations and training modules for Tertiary Institutions
  • 4. Evolution of the World Wide Web Semantic Software 4
  • 5. Current Data Issues • CURRENT DATA ISSUES • Rigid Data Structures • Distributed Data Sources • Unstructured Data • Limited Context , Meaning, Sources • Growth of Social Collaboration • Resource Requirements to Manage
  • 6. How many devices record information?
  • 7. How much Information does the bank use to manage clients needs?
  • 8. How Integrated is Data in Government ?
  • 9. Internet of Things (IoT) • The IoT is a giant network of connected “things” (which also includes people). • The relationship will be between people- people, people-things, and things-things. • ISSUES • Security • Technology & Interoperability • Privacy, IP and Data Sharing • “Data lake” Storage Requirements • Unstructured data • Data interoperability • Meaningful Analysis of Data
  • 11. Internet of Things & Cognitive Computing • IoT is already overwhelming data analytics • Driving the need for cognitive computing • Cognitive computing requires • A semantic knowledge base for meaning • Natural Language Processing to ingest unstructured data • Algorithmic methods to make propositions • Machine Learning to improve propositions Semantic Software 11
  • 12. Agenda • General Introduction of Semantic Software • Welcome and Introduction to IoT and Big Data • Introduction to Semantic Computing concepts • Benefits of Semantic Computing to Government • Q&A • Close
  • 13. Evolution of Data Mining Technologies
  • 14. What is Semantic Computing • Semantic Computing is at the core of Cognitive Computing processes, and is enhanced by other Artificial Intelligence techniques such as Natural Language Processing and Machine Learning • Semantic Computing is the facilitator of key IT Tools of the future providing INTEROPERABILITY and CONTEXT • The Key elements that engage with Semantic Computing include: • Internet of Things (IoT) • Big Data & Analytics • Cloud Computing • Collaborative /Social Media
  • 15. Concepts in Semantic Computing “I got a great shot of an elephant at a zoo.” Semantic Software 16
  • 16. Concepts in Semantic Computing – RDF Resources • Data is transformed into granular facts describing “Resourses” • These facts are expressed in Subject–Predicate–Object form, called Triples • Subjects and Objects are Resources • The Resource Description Framework (RDF) defines the above • Example: • “I got a great shot of an elephant at a zoo.” • Nouns = I, shot, elephant, zoo • Verbs = got, shot • Preposition = of, at, are • RDF Triples generated: • I got a shot • I shot an elephant • I was at the zoo • An elephant was at the zoo • The shot occurred at the zoo Semantic Software 17
  • 17. Concepts in Semantic Computing - Ontologies • An Ontology is a dataset of “rules” that describe a domain of knowledge • They use RDF formats Semantic Software 18 Zoo Ontology FOAF Ontology Photography Ontology A zoo houses animals I means a person Cameras make photos Elephants are animals People is the plural of person A shot is a photo People take photos
  • 18.
  • 19. Semantic Web Stack • "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation." -- Tim Berners-Lee
  • 20. The “Intelligent” Web Semantic Software 21 Professor Sir Tim Berners-Lee (inventor of WWW and Semantic Web)” • 1999 “we don’t know how to do trust, security and proof • In 2006, TBL and colleagues: "This simple idea...remains largely unrealized". • Rust, security and proof recently reaffirmed as “unrealized technologies”
  • 21. Agenda • General Introduction of Semantic Software • Welcome and Introduction to IoT and Big Data • Introduction to Semantic Computing concepts • Benefits of Semantic Computing to Government • Q&A • Close
  • 22. Example of Relationship Finder Query
  • 23. . 25 • Monetary: profit / loss, assets / liabilities, equity • Law and Jurisdiction • Government, regulatory environment • Contracts, agreements, commitments • Products and Services • Other e.g. geopolitical, logistics Key areas for decision making that Semantic Computing supports
  • 24. Semantic Computing in Finance • customer-focus • risk management • increase flexibility • combining disparate sources • regulatory reporting • insider trading controls • data governance • accessing information quickly
  • 25. Benefits of Semantic Computing to Government • Comprehensive Interaction with the Public • Supports Policy Development • Supports Integrated National Security • Manages Risk, Governance and Compliance
  • 26. Semantic Computing in Government Treatment Plan/Workflo w Options Drugs/ Gene Interactions Wearable Diagnostic Support Reduce Excessive Payouts Membershi p Engagemen t Reduce Claim Fraud Correlate Diverse Data Sources Exploit Specialist Ontologies Expanded Govt Access and Sharing Tailor Holistic Treatment Providers Payers Research Expanded Analytic Tasks Personal Patient Files Consumers
  • 27. Semantic Computing in Healthcare • forecast patient behaviour • provide preventive care • impact of infections on patients • identify high volume service users • determine the probability of readmission • improve response rates • identify cardiac failure risk
  • 28. Semantic Computing in Healthcare Treatment Plan/Workflo w Options Drugs/ Gene Interactions Wearable Diagnostic Support Reduce Excessive Payouts Membershi p Engagemen t Reduce Claim Fraud Correlate Diverse Data Sources Exploit Specialist Ontologies Expanded Govt Access and Sharing Tailor Holistic Treatment Providers Payers Research Expanded Analytic Tasks Personal Patient Files Consumers