Linking Open, Big Data Using Semantic Web Technologies - An Introduction

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The Physics Department of the University of Cagliari and the Linkalab Group invited me to talk about the Semantic Web and Linked Data - this is simply an introduction to the technologies involved.

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  • Linking Open, Big Data Using Semantic Web Technologies - An Introduction

    1. 1. LINKING OPEN, BIG DATA USINGSEMANTIC WEB TECHNOLOGIES AN INTRODUCTION Dr. Ronald Ashri - Istos srl http://www.istos.it
    2. 2. THE GOAL
    3. 3. connect and explore data to discover hidden patterns and create new informationnew information enables us to formulate better solutionsand identify new oportunities
    4. 4. the billiondollar-o-gram
    5. 5. TOOLSstatistical analysisnetwork analysissimulation(evolutionary,biologically inspiredsystems)symbolic manipulation
    6. 6. THE SEMANTIC WAYBuild ModelsCalculate with knowledgeExchange InformationVisualize - Analyze
    7. 7. BUILDING MODELSAND CALCULATING
    8. 8. BUILDING MODELSwhat things can be said to existwhat is reality?bring structure into modeling
    9. 9. ontology is a description of knowledge about a domain of interest ὸντος = that is how it is
    10. 10. arbor porhyriana Substance immaterial material Body Spirit animate inanimate Living Mineral sensitive insensitive Animal Plant rational irrational Human Beast 234AD, Tyre (Lebanon)
    11. 11. knowledge on the web is modeled using RDF, RDFsand/or the Web Ontology Language - OWL
    12. 12. RDFResource Description Framework directed labelled graph capitalOf Cagliari Sardegna subject predicate object
    13. 13. URIUniform Resource Identifiers a compact sequence of characters to identify an abstract or physical resource scheme:[//authority]path[?query][#fragment] e.g. http://www.regione.sardegna.it/uri
    14. 14. RDF + URI http://example.org/capitalOf Cagliari Sardegnahttp://www.comune.cagliari.it/uri http://www.regione.sardegna.it/uri
    15. 15. RDF + URI eg:livesIn Ronald Sicilyhttp://www.istos.it/ronald#me http://dbpedia/resource/Sicily eg:worksFor Ronald Istoshttp://www.istos.it/ronald#me http://www.istos.it/uri foaf:based_near Istos Ispica http://www.istos.it/uri http://dbpedia/resource/Ispica
    16. 16. RDF SCHEMARDF is a general way to describe structuredinformationRDF Schema extends RDF to express generalinformation about a data set Resources, Classes, Literals, Datatypes, Properties range, domain, subClassOf, subPropertyOf
    17. 17. RDFS SERIALIZATIONSN3, N-Triples, Turtle Human readable, limited software supportRDF XML takes advantage of tools to parse XMLRDFa - enables RDF to be embedded in HTML
    18. 18. OWLOffers more expresivity Classes (e.g. City, Region, Country) Roles (e.g. containedWithin) Individuals (e.g. Cagliari, Sardegna)
    19. 19. CALCULATINGCagliari is a City deduction => Cagliari isCagliari is containedWithin ItalycontainedWithinSardegnaSardegna is a RegionSardegna iscontainedWithin Italy
    20. 20. Class(a:giraffe partial a:animal restriction(a:eats allValuesFrom (a:leaf)))Class(a:leaf partial restriction(a:part_of someValuesFrom (a:tree)))Class(a:tree partial a:plant)DisjointClasses(unionOf(restriction(a:part_of someValuesFrom (a:animal)) a:animal) unionOf(a:plant restriction(a:part_of someValuesFrom (a:plant))))Class(a:vegetarian complete intersectionOf( restriction(a:eats allValuesFrom (complementOf(restriction(a:part_ofsomeValuesFrom (a:animal))))) restriction(a:eats allValuesFrom (complementOf(a:animal))) a:animal)) • Giraffes only eat leaves • Leaves are parts of trees, which are plants • Plants and parts of plants are disjoint from animals and parts of animals • Vegetarians only eat things which are not animals or parts of animals
    21. 21. Figure 2: Agent-Based Market Model
    22. 22. (a) Dependency: α sells (b) Comp-Sell: α and β (c) Comp-Buy: The goal (d) Coll: α sells to β goods to B are competing in α’s RoI of α is the same that the and β sells to α goal of β Figure 3: Key Relationship Patternson the buyer. We specify a dependency relationships in terms of y ygoals in the following way: Dep(q(gα ), a(gβ ))RoIβ ⊆V Eα , wherey is the product β is selling to α (i.e. α wants to achieve the goalof having y), and β’s region of influence is withing α’s viewableenvironment as for trade relationships.4.3 Competition
    23. 23. OWL - XML-based syntax suitable for machines and use in web documentsOWL - abstract syntax easier to read and write closer to description logics
    24. 24. balance between expressivity and efficient reasoningcomplex language constructs for respresentingimplicit knowledge yield high computationalcomplexities or even undecidability
    25. 25. OWL Lite decidable less expressive ExpTime
    26. 26. OWL DL contains OWL Lite decidable supported by software tools NExpTime
    27. 27. OWL Full very expressive undecidable
    28. 28. THE PROCESSBuild an ontology orvocabularyState facts aboutdomainReason aboutontologies and facts
    29. 29. EXCHANGINGINFORMATION
    30. 30. WWW 0.1the original web was thought of with ontological information at its heart http://www.w3.org/History/1989/proposal.html
    31. 31. ?? ??
    32. 32. THE PROBLEMhttp://www.w3.org/Talks/WWW94Tim/
    33. 33. THE SEMANTIC WEB
    34. 34. SPARQLProtocol and RDF Query LanguageGraph pattern matching Uses RDF triples but they may be variablesThe reply is the RDF graph equivalent to thesubgraph described
    35. 35. PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name ?emailWHERE { ?person a foaf:Person. ?person foaf:name ?name. ?person foaf:mbox ?email.}endpoint: world-wide webnames and e-mails of every person in the world!
    36. 36. EXCHANGE MORE INFORMATIONTHE LINKED DATA EFFORT
    37. 37. the semantic web provided tools butnot enough method - the linked data effort tries to rectify this
    38. 38. 1. Use URIs as names for things2. Use HTTP URIs so that people can look things up3. Provide useful info using standards (Sparql)4. Include links to other URIs
    39. 39. USE URISBasic - if you are not using URIs it is not SemanticWeb
    40. 40. USE HTTP URISstop inventing your own schemasHTTP works - browsers know it - let us takeadvantage of it
    41. 41. HELP OTHERSwhen people look up HTTP URIs make the dataavailable and/or provide Sparql support
    42. 42. Available on the web (whatever format), but with an openlicence Available as machine-readable structured data (e.g. excelinstead of image scan of a table) as (2) plus non-proprietary format (e.g. CSV instead ofexcel) All the above plus, Use open standards from W3C (RDFand SPARQL) to identify things, so that people can point at yourstuff All the above, plus: Link your data to other people’sdata to provide context
    43. 43. datasets
    44. 44. UMBEL - Reference concept ontology28000 scaffold concepts
    45. 45. services
    46. 46. REASON, VISUALIZE
    47. 47. the fear index
    48. 48. LOOKING AHEADTechnology and toolsare getting thereData needs to remainopenSpread the word -Annotate!
    49. 49. QUESTIONSronald@istos.it@ronald_istos

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