Practical semantics - An introduction

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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.

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  • 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

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  • 1. Practical Semantics What can Semantics do for me today?Ben GardnerCollaboration & Information ArchitectBen at differentiatedthinking.comhttp://www.linkedin.com/in/bengardner135
  • 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 Webhttp://www.informationarchitects.jp/en/wp-content/uploads/slash/iA_WebTrends_2007_2_1600x1024.gif 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 Datahttp://richard.cyganiak.de/2007/10/lod/
  • 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 Nodehttp://richard.cyganiak.de/2007/10/lod/
  • 23. Ben Gardner
  • 24. Ben Gardner
  • 25. Ben Gardner
  • 26. Making Connections Matter with Jessicahttp://www.slideshare.net/bengardner135/meet-jessica-making-connections-matter 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: http://www.linkedin.com/in/bengardner135 Blog http://dif-fer-en-ti-ate.blogspot.com/ http://www.slideshare.net/bengardner135 email Ben at differentiatedthinking.com