Practical semantics - An introduction

Uploaded on

This is an intriduction to how Semantic/Linked Data technologies can help solve the challenges of information overload. This presentation is often given in co-junction with 'meet Jessica - Making …

This is an intriduction to how Semantic/Linked Data technologies can help solve the challenges of information overload. This presentation is often given in co-junction with 'meet Jessica - Making Connections Matter.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads


Total Views
On Slideshare
From Embeds
Number of Embeds



Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

    No notes for slide
  • It is estimated that 40 exabytes (4.0 x 10E19) of unique new information will be generated worldwide this yearThat is more than in the previous 5,000 yearsOne weeks worth of the New York times contains more information than a person was likely to come across in a lifetime in the 18th centuryItoday 31 billion google searches are performed per month, in 2006 this was just 2.7 billionThe amount of technical information is doubling every 2 years


  • 1. Practical Semantics What can Semantics do for me today?Ben GardnerCollaboration & Information ArchitectBen at differentiatedthinking.com
  • 2. Practical SemanticsAn introduction to SemanticsDelivering semantic solutions todaymeet Jessica – A vision of working in aSemantic enabled organisation Ben Gardner
  • 3. We live in exponential times Ben Gardner
  • 4. A list is good enough? Ben Gardner
  • 5. A list is not enough ReflectNetwork SemanticsAnalysis Utopia Carrot 2 Quosa Targetpedia Ben Gardner
  • 6. Many Places for Lots of Bits ? Targetpedia TOU Ben Gardner
  • 7. Integrating Relational Data is HardCost/Resource/Time Complexity Ben Gardner
  • 8. An Alternative ApproachExploratory/Investigative Best practiceEvolving ReproducibleDynamic Business Drivers StandardisedAgile ConsistentSemantics RelationalOpen RobustDiscoverable Technology Strengths PerformanceInteroperable Auditing Ben Gardner
  • 9. HTML Links Pages Ben Gardner
  • 10. World Wide Web Ben Gardner
  • 11. Things have Properties JessicaExpertise Projects Targets LocationMolecular Pharmacology D3 Agonist for FSD 5HT1a&b SandwichMolecular Biology Nav1.7 for Pain G-ProteinsReceptor Theory CB2 for Obesity CB1&2G-Protein Coupled Receptors D2 for Schizophrenia P38Modelling Arrestin’sData VisualisationReceptor RegulationIn Vitro Assay Development Ben Gardner
  • 12. Resource Description Framework (RDF) Subject Predicate Object <Jessica> <hasExpertise> <CB2> RDF Triple Combining Triples creates a directed, labelled graph <Molecular Biology> hasSkill <Nav1.7 for hasWorkedOn Pain> <Jessica> hasLocation Graph <Sandwich> hasExpertise <CB2>Inspired by J Phil Brooks Ben Gardner
  • 13. Connections are common properties shared by ThingsJessica Cannabinoid Receptor 2 Migraine[+] Expertise [+] Structure [-] Targets[+] Projects [+] Isoforms CGRP[-] Targets [+] Pharmacological tools 5HT1D CBR2 [-] Implicated in CB2 5HT1A&C Migraine PDE3 G-Proteins Obesity Ras P38 Schizophrenia [+] Competitive Intelligence Arrestin’s ….. [+] Treatments[+] Location [+] …… Vocabularies Ben Gardner
  • 14. Resource Description Framework (RDF)Graphs can be joined together …… <Molecular Biology> hasSkill <Nav1.7 for hasWorkedOn Pain> <Jessica> hasLocation <Sandwich> hasExpertise <CB2> <CB2> Implicated_in <Migraine> subClassOf hasTool <PF-334,765> <GPCR>Inspired by J Phil Brooks Ben Gardner
  • 15. Resource Description Framework (RDF)…... to traverse the knowledge space <Molecular Biology> hasSkill <Nav1.7 for hasWorkedOn Pain> <Jessica> hasLocation <CGRP> <Sandwich> Associated target hasExpertise <CB2> Implicated_in Associated target <Migraine> <5HT1D> subClassOf hasTool hasTreatmentClass <PF-334,765> <GPCR> <Tryptan>Inspired by J Phil Brooks Ben Gardner
  • 16. Linked Open Data
  • 17. Ok so it is a bit more complicated Disambiguation Context Sildenafil Citrate Viagra Revatio Ben Gardner
  • 18. Building a linked data cloud 3 Applications Business Process / Workflow Automation PURL Rest Services (Abstraction layer) Increasing Ease of Development 2 Semantic Integration Framework Decreasing knowledge of Semantic technologies Knowledge Collation, Concept mapping, Distributed Query Result inference, Aggregation 1 RDF Sparql EndPoint Native Sparql EndPoint RDBMS RDF Triple MS Excel Oracle,Postgres Store TXT SQL, mySql Doc Data SourcesPhil Ashworth UCB – SemTech 2011 Ben Gardner
  • 19. But this is all theoretical right? Ben Gardner
  • 20. Patents have Properties Ben Gardner
  • 21. Patents can be aggregated by Properties Ben Gardner
  • 22. Pfizerpedia Patents is a Node
  • 23. Ben Gardner
  • 24. Ben Gardner
  • 25. Ben Gardner
  • 26. Making Connections Matter with Jessica Ben Gardner
  • 27. 18 months ago Jessica’s did not know what shewas missing She needed to know where information was before she could use it Ben Gardner
  • 28. Today because of Semantics….. …… information finds Jessica’s Ben Gardner
  • 29. Ask Jessica what semantics means to herit’s most definitely about Making Connections Matter Ben Gardner
  • 30. “It’s all about connections”People 2 People Data 2 Data People 2 Data Ben Gardner
  • 31. Semantics on the Gartner Hype Cycle visibility Linked Data Peak of Technology Inflated Trough of Plateau of Trigger Expectations Disillusionment Slope of Enlightenment Productivity time Ben Gardner
  • 32. ProfileBen GardnerCollaboration and Information Architect Contact via: Blog email Ben at