ToC. n Introduction. n Linked Data. n Iterative and Incremental Linked Data Life cycle. n Q&A. Copyright 2017 FUJITSU LIMITED

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1 ToC n Introduction n Linked Data n Iterative and Incremental Linked Data Life cycle n Q&A 1

2 Personal Introduction n Undergraduate University: Universidad Católica Boliviana n Postgraduate University: Universidad Politécnica de Madrid n Research stays: National Research Council, Rome, Italy Digital Enterprise Research Institute, NUI, Galway, Ireland The University of Aberdeen, Scotland, UK n Ontology Engineering Group n isoco, Intelligent Software Components n Expert System n Fujitsu Laboratories of Europe n Tetuan Valley Startup School 2

3 Main references Pan, Jeff et al. (Ed) Exploiting Linked Data and Knowledge Graphs in Large Organisations - Knowledge Graph Foundations Boris Villazón Terrazas, Nuria García-Santa, Yuan Ren - Construction of Enterprise Knowledge Graphs Boris Villazón Terrazas, Nuria García-Santa, Yuan Ren Best Practices for Publishing Linked Data W3C Working Group Note Bernadette Hyland, Ghislain Atemezing, Boris Villazón Terrazas Wood, David (Ed) Linking Government Data Methodological Guidelines for Publishing Government Linked Data Boris Villazón Terrazas, Luis M. Vilches, Oscar Corcho, Asunción Gómez-Pérez 3

4 Introduction 4

5 Knowledge Graphs n Knowledge in a graph form n Captures entities, attributes, and relationships n Nodes are entities n Nodes are labeled with attributes n Typed edges between two nodes represent a relationship between entities Edmundo Paz-Soldán bornin Iris Cochabamba 5

6 Google n The Knowledge Graph is a knowledge base to enhance its search engine's search results with semantic-search information gathered from a wide variety of sources. 6

7 Microsoft Concept Graph n What we need in order to act like a human is nothing more than knowledge about concepts (e.g., persons and animals) and the ability to conceptualize (e.g., cats are animals). Concepts are the glue that holds our mental world together 7

8 IBM Watson n Watson is a question answering computer system capable of answering questions posed in natural language. There is a knowledge graph under the hood. 8

9 and more n Amazon Product Graph n Facebook Graph API n LinkedIn Knowledge Graph n 9

10 Linked Data 10

11 Knowledge Representation n Decades of research into knowledge representation n Some knowledge graph implementations use RDF Triples, the foundations of Linked Data. n Linked Data is one of the core concepts and pillars of the Semantic Web. The Semantic Web is all about making links between datasets understandable not only to humans but also to machines. n Standards for defining and exchanging Knowledge RDF, RDFa, JSON-LD, schema.org RDFS, OWL, SKOS, FOAF 11

12 Linked Data enables a Web of Data Global Identifier: URI (Uniform Resource Identifier), which is a string of characters used to identify a name or a resource on the Internet. Data Model: RDF (Resource Description Framework), which is a standard model for data interchange on the Web. Access Mechanism: HTTP Connection: Typed Links Even the Rain CIA World FactBook MovieDB Slide adapted from 5 min Introduction to Linked Data - Olaf Hartig 12

13 LOD Cloud "Linking Open Data cloud diagram 2017, by Andrejs Abele, John P. McCrae, Paul Buitelaar, Anja Jentzsch and Richard Cyganiak 13

14 Resource Description Framework n RDF is a basic Knowledge Representation language based on semantic networks. Useful to represent metadata and describe any type of information in a machine-accesible way (aka data model) Resources are described in terms of properties and property values using RDF statement Statements are represented as triples, consisting of a subject, predicate, and object [S,P,O] Subject property Object Statement 14

15 SPARQL n Language developed to allow accessing datasets expressed in RDF. Application Application SQL queries SPARQL queries Relational DB RDF 15

16 RDF Example Esteban García hasname hascolleague hascolleague hassex Male 16

17 RDF Example n For practical purposes, specially if handwritten, URIs are shortened using XML namespaces n xmlns:ue= n ue:esteban is equivalent to n RDF serializations: XML, N3, N-Triple, JSON-LD Esteban García person:hasname ue:esteban person:hascolleague person:hascolleague ue:enrique ue:diego person:hassex Male 17

18 RDF - SPARQL Esteban García person:hasname ue:esteban person:hascolleague person:hascolleague ue:enrique ue:diego person:hassex Male Query: Tell me who are the people who have Enrique as colleague? person:hascolleague ue:enrique Result: ue:esteban and ue:diego SPARQL query language for RDF. W3C recommendation SELECT?s WHERE {?s person:hascolleague ue:enrique.} 18

19 Hands on - n Information about People SELECT DISTINCT?person?p?o WHERE {?person a < ;?p?o } GROUP BY?person?p?o LIMIT 30 n Information about a particular person SELECT DISTINCT?person?p?o WHERE {?person a < ; foaf:firstname "Boris" ; foaf:lastname "Villazon-Terrazas" ;?p?o } GROUP BY?person?p?o n Infomation about people and companies SELECT DISTINCT?affiliation?member WHERE { < swrc:affiliation?affiliation.?affiliation foaf:member?member } 19

20 Hands on - n Whose birthday is today? SELECT?entityLabel (YEAR(?date) as?year) WHERE { BIND(MONTH(NOW()) AS?nowMonth) BIND(DAY(NOW()) AS?nowDay)?entity wdt:p569?date. FILTER (MONTH(?date) =?nowmonth && DAY(?date) =?nowday) SERVICE wikibase:label { bd:serviceparam wikibase:language "en". } } LIMIT 10 20

21 Hands on - n Soccer players from Cochabamba SELECT?label?goals WHERE {?player a < < < < rdfs:label?label } ORDER BY DESC(?goals) 21

22 Iterative and Incremental Linked Data Life cycle 22

23 Publishing Linked Data? Process that involves a high number of steps, design decisions and technologies. 23

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26 Specification n Identification and analysis of the data sources n URI design n Definition of the license 26

27 Identification and analysis of the data sources After we have identified and selected the data sources n Search and compile all the available data and documentation about those resources n Identify the schema of those resources including conceptual components and their relationships n Identify the items in the domain, i.e., things whose properties and relations are described in the data sources 27

28 URI Design n Use meaningful URIs, instead of opaque URIs, when possible n Separate TBox (ontology model) from ABox (instances) URIs n Base URI n TBox URIs property} n ABox URIs

29 Definition of the License n Data Licensing is not trivial n Requires technological knowledge n Depends on business strategy and models n Data is an intellectual asset and can be protected by intellectual property rights n Licenses create a secure business environment n Creative Commons, and Open Data Commons 29

30 Cáceres - Example Restaurants Hotels 30

31 Cáceres - Example n Base URI n TBox URIs property} n ABox URIs

32 Cáceres - Example Licencia para los conjuntos de datos Todos los conjuntos de datos que ofrece el Ayuntamiento de Cáceres, si no se indica lo contrario, se publican bajo los términos de la licencia Creative Commons-Reconocimiento (CC-by 3.0) 32

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34 Modelling Search for suitable vocabularies are there suitable vocabularies? Yes Build the vocabulary by reusing available vocabularies No 34

35 Modelling Highly reliable Web Sites Search for suitable non-ontological resources Domain-related sites Government Catalogs are there suitable resources? Yes Build the vocabulary by transforming available resources * No Build the vocabulary from scratch Boris Villazón-Terrazas, A Method for Reusing and Re-Engineering Non-Ontological Resources for Building Ontologies. IOS Press

36 Cáceres - Example 36

37 Cáceres - Example 37

38 Cáceres - Example n Protégé, free an open source ontology editor and framework for building intelligent systems 38

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40 Generation n Transformation n Data cleansing / curation n Linking 40

41 Transformation n Take the data sources selected in the specification activity and transform them to RDF according to the vocabulary created in the modelling activity n Some tools n CSV and spreadsheets Open Refine, XLWrap, RDF123 n RDB R2RML n XML GRDDL, ReDeFer n RML 41

42 Transformation RDB2RDF n A majority of dynamic Web content is backed by relational databases (RDB), and so are many enterprise systems. n W3C RDB2RDF Working Group R2RML: RDB to RDF Mapping Language - Direct Mapping - R2RML and Direct Mapping Test Cases - RDB2RDF Implementation Report

43 Transformation Geospatial to RDF n Tool for generating RDF from geospatial information n The geometry could be available in GML or WKT 43

44 Transformation MARC21 to RDF n A MARC Mappings and RDF generator 44

45 Linking Identify suitable data sets as linking targets Look for similar datasets in Discover relationships between data items LIMES Silk Framework Validate the relationships discovered 45

46 Cáceres - Example Restaurants 46

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48 Publication n Dataset publication n Metadata publication 48

49 Dataset publication n Tools for storing RDF/SPARQL endpoint/linked Data frontend n Virtuoso Universal Server, Jena Fuseki, Sesame, 4Store, YARS, Apache Marmotta, Pubby, Linked Data API, Linked Data Platform n Store the RDF data in different graphs n n n 49

50 Metadata publication n VoID allows to express metadata about RDF datasets n The PROV Ontology

51 Cáceres - Example

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53 Exploitation Data Analytics 53

54 Exploitation n Faceted browser interface. n Geospatial visualization using Google Maps and Open Street Maps. n Visualization of geometries (LineStrings, Polygons, etc) when using the GeoLinkedData data model. map4rdf SPARQL Triplestore 54

55 Cáceres - Example 55

56 Cáceres - Example 56

57 Use cases 57

58 Maintenance 58

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61 Questions 61

62 n n n n hl=en&user=n0nwnc0aaaaj&view_op=list_works&sortby=pu bdate 62

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