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#opentourism - Linked Open Data Publishing and Discovery Workshop

This session will bring a solution to one of the main issues in the field of application development for the tourism and leisure sector. A lot of projects fail because the underlying systems and databases are too difficult to connect or because it is too costly to do. We will share and discuss the ‘Open Standard for Tourism Ecosystems Data’, developed by touristic actors in Flanders and a tool for aggregating existing data and mapping it to the tourism vocabulary, which has been tested with local data in the region of West-Flanders.

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#opentourism - Linked Open Data Publishing and Discovery Workshop

  1. 1. #openbelgium15 #opentourism A community supporting Digital Creativity in Tourism
  2. 2. Cause and context Raf Buyle - Open Knowledge @rafke #opentourism
  3. 3. WHAT … Imagine we could use the same services in different places around the world without the need for searching new service providers or new apps...
  4. 4. WHAT Information often can't be reused without analizing the data or building expensive custom connectors
  5. 5. WHAT COULD BE? Linked Open Data aims to connect these solitary pieces of information to other data sources on the web.
  6. 6. WHAT SHOULD WE DO? we need more Open Data and a common language for machine readable touristic information.
  7. 7. Joined forces with ‘sustainable mobile tourism guides’, Thomas More - iMinds
  8. 8. shared vision: “Open Standard for Tourism” Vocabulary Ontologies are expected to enable computers to process information “much more effectively in ways that are useful and meaningful to the human user” (Berners-Lee, Hendler, and Lassila 2001).
  9. 9. User Group 40+ actors: SME’s, NPO’s involved in culture and tourism activities, representatives from the provinces and of the major cities in Flanders
  10. 10. priorities both as data producer and as data consumer
  11. 11. “After defining the scope of each sub- domain we organized working groups. Each group was responsible to work out their sub- domain in detail in terms of domain modeling”
  12. 12. Data in line with the Open Tourism specifiction The West Flanders tourism organization was the first to bring their data inline with the specification
  13. 13. Open Tourism hackathon 🗸 DATA 🗸 TOOLS 🗸 APP’S 🗸 FEEDBACK http://www.mobielegidsen.be/hackathon/
  14. 14. From ad-hoc activity to a solid community Our mission is to “support digital creativity concerning tourism" and to host the “Open Standard for Tourism” Vocabulary, which is a reusable Ontology for describing tourism data. Join the Community Meeting, March 5, 2016 Mechelen
  15. 15. Release Open Tourism Communty Site ● Mailing list ● Tools and resources ● The Open Standard for Tourism Ecosystems Data Specification ● News on the upcoming events
  16. 16. Join our community! tourism.openknowledge.be
  17. 17. Join our community! tourism.openknowledge.be
  18. 18. Vision and strategy… ● Bring The Open Tourism vocabulary at an international level ● Build a bridge to interoperability programme of the Flemish Government, “Open Standards for Linked Governments”. ● First step - March 3 our work and vision will be presented at the International e- Gov Conference in Montevideo.
  19. 19. What you really should remember from this talk: ● Semantic collaboration is going to be a cornerstone of the next generation tourism applications ● semantic standards are a katalysator for better services and Open Data. ● The Open Tourism vocabulary exist http://w3id.org/ost/spec ● You’re welcome to join our community! http://tourism.openknowledge.be
  20. 20. Getting started with the Open Tourism Specification Bruno Koninckx THOMAS MORE @brunokon #opentourism
  21. 21. Which domains are covered (for now)? ➔ Offering What? By whom? ➔ Availability Where? When? ➔ Experience How? ➔ Demand
  22. 22. Offering Availability Experience Demand
  23. 23. Availability Demand Offering
  24. 24. Experience Offering
  25. 25. Demand Offering
  26. 26. Specifications http://w3id.org/ost/spec Questions, remarks, issues on the domain model and specifications via: https://github.com/openknowledgebe/tourism/issues
  27. 27. Publising and Consuming Linked Tourism Data Anastasia Dimou - iMinds - Data Science Lab @natadimou #opentourism
  28. 28. RML.io Generating High Quality Linked Open Data from Open or Not Data Anastasia Dimou Data Science Lab, Ghent University - iMinds anastasia.dimou@ugent.be @natadimou
  29. 29. What is the Semantic Web?
  30. 30. The Semantic Web is the extension of the World Wide Web
  31. 31. Are you the owner of your data? OR is the application that hosts your data?
  32. 32. The Semantic Web is the extension of the World Wide Web enables sharing content beyond the boundaries of applications & websites
  33. 33. the Web for humans, thanks to HTML, is understandable & constant BUT is the Web for machines too?
  34. 34. The Semantic Web is the extension of the World Wide Web enables sharing content beyond the boundaries of applications & websites allows machines to understand the meaning of hyperlinked information
  35. 35. Semantic Web enabled applications rely on data represented as Linked Data
  36. 36. What is Linked (Open) Data?
  37. 37. Linked (Open) Data a standardized way of expressing the relationships between data
  38. 38. Linked (Open) Data a standardized way of expressing the relationships between data semantically annotated the data with different vocabularies or ontologies
  39. 39. Linked (Open) Data a standardized way of expressing the relationships between data semantically annotated the data with different vocabularies or ontologies describe domain-level knowledge understandable by humans & machines
  40. 40. Where does Linked Data come from?
  41. 41. Linked (Open) Data is often derived from originally heterogeneous (semi-)structured data
  42. 42. Linked Open Data from Not Open Data
  43. 43. Linked Open Data from Not Open Data from Open Data
  44. 44. Linked Open Data from Not Open Data from Open Data from their combination
  45. 45. How is Open Data published?
  46. 46. The DataTank open source RESTful data management system
  47. 47. The DataTank open source RESTful data management system enables publishing data into web readable formats read the data and publish them on the web using a URI as an identifier.
  48. 48. The DataTank supported data formats CSV and XLS XML JSON(-LD) SHP RDF MySQL SPARQL
  49. 49. How is Linked (Open) Data published?
  50. 50. Linked (Open) Data published in the form of RDF datasets
  51. 51. Resource Description Framework (RDF) is the prevalent data model for describing Linked (Open) Data
  52. 52. Resource Description Framework (RDF) is the prevalent data model for describing Linked (Open) Data predicate subject object
  53. 53. Resource Description Framework (RDF) is the prevalent data model for describing Linked (Open) Data driven by unique identifiers (URIs) predicate subject object
  54. 54. Resource Description Framework (RDF) is the prevalent data model for describing Linked (Open) Data driven by unique identifiers (URIs) allows establishing a shared meaning predicate subject object
  55. 55. How is Linked Data derived from (semi-)structured data?
  56. 56. How is Linked Data derived from (semi-)structured data? id firstname lastname lab city 1 Anastasia Dimou DSLab Ghent 2 Ruben Verborgh DSLab Ghent 3 Erik Mannens DSLab Ghent
  57. 57. Person 1 Data Science Labworks “Anastasia Dimou” locatedDataScience Lab Ghent Person 2 Data Science Labworks “Ruben Verborgh” Person 3 DataScience Labworks “Erik Mannens”
  58. 58. Person {id} {lab} Assign unique identifiers (URIs) “{firstname} {surname}”
  59. 59. Person {id} {lab} Assign unique identifiers (URIs) “{firstname} {surname}” http:://ex.com {id} http://ex.com{lab} “{firstname} {surname}”
  60. 60. Annotate data relationships with ontologies http:://ex.com {id} http://ex.com{lab} “{firstname} {surname}”
  61. 61. Annotate data relationships with ontologies http:://ex.com {id} http://ex.com{lab} “{firstname} {surname}” http:://ex.com {id} http://ex.com{lab} “{firstname} {surname}”
  62. 62. ex:1 ex:DSLabex:works “Anastasia Dimou” ex:locatedex:DSLab ex:Ghent ex:2 ex:DSLabex:works “Ruben Verborgh” ex:3 ex:DSLabex:works “Erik Mannens”
  63. 63. ex:{id} ex:{lab} ex:located ex:{lab} ex:{city} sets of triples of a dataset have repetitive patterns “{firstname} {surname}”
  64. 64. ex:{id} ex:{lab} sets of triples of a dataset have repetitive patterns “{firstname} {surname}” RDF dataset generation tools rely their implementation on repetitively applying those patterns to input data ex:located ex:{lab} ex:{city}
  65. 65. What are the different Linked Data Generation approaches?
  66. 66. Linked Data generation approaches case-specific solutions
  67. 67. Linked Data generation approaches case-specific solutions OR format and source specific
  68. 68. Data OWNER / PUBLISHER CSV JSONXML RDF RDF RDF
  69. 69. R2RML mappings R2RML processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF RDF RDF
  70. 70. RDF Terms (focusing on IRIs) are… generated independently disregarding their possible prior definitions manually replicated by reconstructing the same URIs (if possible) manually aligned afterwards links with other datasets are defined after the RDF terms are published
  71. 71. Why not a uniform approach?
  72. 72. Uniform and declarative RDF generation from heterogeneous data sources mappings processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF
  73. 73. RDF Mapping Language (RML) generic scalable mapping language for generating and interlinking RDF data from heterogeneous resources in an integrable and interoperable fashion superset of the W3C standardized R2RML mapping language http://rml.io
  74. 74. Uniform and declarative RDF generation from heterogeneous data sources RML mappings processor Data OWNER / PUBLISHER defines RDF DB CSV JSONXML RDF
  75. 75. Defining Mappings to generate Linked Data Retrieving Input Data Editing Mappings
  76. 76. Defining Mappings to generate Linked Data Retrieving Input Data Editing Mappings
  77. 77. RML describes how to generated RDF from structured data predicate subject object
  78. 78. RML describes how to generated RDF from structured data predicate subject object Predicate Map Subject Map Object Map
  79. 79. RML describes how to generated RDF from structured data predicate subject object Predicate Map Subject Map Object Map <#TriplesMap>
  80. 80. rr:constant ex:located rr:template “http://ex.com/{lab}” rr:template “http://ex.com/{city}” rr:template “http://ex.com/{id}” rr:template “http://ex.com/{lab}” rr:template “{firstname} {surname}” rr:termType rr:Literal RDF Mapping Language (RML) @prefix rr: <http://www.w3.org/ns/r2rml#>
  81. 81. rr:constant ex:locatedrr:template “http://ex.com/{lab}” rr:template “http://ex.com/{city}” rr:template “http://ex.com/{id}” rr:template “http://ex.com/{lab}” <#ResearcherMap> <#LabMap> rr:template “{firstname} {surname}” rr:termType rr:Literal RDF Mapping Language (RML)
  82. 82. Extraction Module Mapping Module RML Processor
  83. 83. Defining Mappings to generate Linked Data Editing Mappings Retrieving Input Data
  84. 84. RML describes rules to map any structured data to RDF RML supports any data independently of which structure and format they have where they originally reside how they are accessed & retrieved
  85. 85. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
  86. 86. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
  87. 87. Support data in Heterogeneous Structures tabular-structured hierarchical-structured (semi-)structured … … …
  88. 88. Support data in Heterogeneous Structures and Formats tabular-structured tables in DBs or CSV files … hierarchical-structured JSON or XML … (semi-)structured HTML … … … …
  89. 89. rr:template “http://ex.com/{id}” rr:template “http://ex.com/{lab}” <#ResearcherMap> rr:template “{firstname} {surname}” rr:termType rr:Literal id firstname surname lab 1 Anastasia Dimou DSLab 2 Ruben Verborgh DSLab 3 Erik Mannens DSLab tabular-structured data
  90. 90. rr:constant ex:located rr:template “http://ex.com/ {/labs/lab/short}” rr:template “http://ex.com/ {/labs/lab/location/city}” <#LabMap> <labs> <lab> <short>MMLab</short> <title>Multimedia Lab</title> <location> <city>Ghent</city> </location> </lab> <lab> …. </lab> … </labs> hierarchical-structured data
  91. 91. Specifying data which data form a data input how to reference data input extracts Accessing & Retrieving data data input from original source(s)
  92. 92. Input data Input data Input data Output RDF Mapping module RML Processor Map doc
  93. 93. Data source Access interface Input data Input data Input data Output RDF Mapping module RML Processor Map doc Data source Access interface Data source Access interface Retrieval module Source description
  94. 94. Support different Locations and Access Interfaces Local File(s) Database connectivity Web source(s) RDF source(s)
  95. 95. Support different Locations and Access Interfaces Local File(s) Database connectivity D2RQ Web source(s) (Web API/service) DCAT, CSVW, Hydra, VOiD (Dataset) RDF source(s) VOiD (Endpoint), SPARQL-SD
  96. 96. file.xml WEBAPI DCAT XML data JSON data tabular data Output RDF Mapping module RML Processor Map doc Data repo WEBAPI Hydra Data base JDBC D2RQ Retrieval module Source description Triple store SPARQL
  97. 97. Defining Mappings to generate Linked Data Retrieving Input Data Editing Mappings
  98. 98. Semantic Web experts Vs. Data specialists
  99. 99. Semantic Web experts Vs. Data specialists Modeling Domain Knowledge as Linked (Open) Data is not straightforward for Data Specialists
  100. 100. Semantic Web experts Vs. Data specialists Modeling Domain Knowledge as Linked (Open) Data is not straightforward for Data Specialists Data context is not straightforward for Semantic Web experts
  101. 101. Semantic Web experts Vs. Data specialists Data Specialists should be able to specify the mappings, modify and extend them at any time
  102. 102. Defining Mappings to generate Linked Data Editing Mappings Retrieving Input Data
  103. 103. The five stars of the Linked Open Data scheme should not be approached as a set of consecutive steps
  104. 104. Well-considered policy regarding mapping and interlinking of data in the context of a certain knowledge domain
  105. 105. GEO > OPEN Geraldine Nolf Flemish Information Agency @natadimou #opentourism
  106. 106. > Geographical data in Flanders ▪ Must follow its obligations, regulations, standards, … > F.e. SDI-Flanders partnership (decree, implementing decree, commandments, …) > MUST’s for describing metadata: ▪ ISO > 19115 (datasets/series), 19119 (services), 19139 (implementation), 19110 (feature catalogue) ▪ INSPIRE > Directive: Implementing Rules on Metadata + Technical Guidelines on Metadata ▪ SDI-Flanders > Best Practices on Metadata v1.0 (metadata for datasets, dataset series, services, feature catalogues) ▪ OGC / INSPIRE > Catalogue Service for the Web (OGC Catalogue Services Specification 2.0.2) = Discovery Service (INSPIRE) = Zoekdienst (SDI-Flanders) > Geoportal: http://www.geopunt.be The way to open geographical data in Flanders? Geo > Open 109
  107. 107. > Open data Portal in Flanders: ▪ SHOULD follow its manual > SHOULD HAVE’s for describing metadata: ▪ DCAT-AP > Portal: http://opendata.vlaanderen.be/ ▪ CKAN The way to open geographical data in Flanders? Geo > Open 110
  108. 108. > So, do I have to describe my data on both portals? > The power of metadata: ▪ Describe it only once, ▪ Create multiple use The way to open geographical data in Flanders? Geo > Open 111 1
  109. 109. The way to open geographical data in Flanders? Geo > Open 112 > Follow the SDI-track to describe metadata (MUST) ▪ Appear on http://www.geopunt.be ▪ AND appear on http://opendata.vlaanderen.be/ > Because of: ▪ Set keyword “Open data in Flanders” in the metadata record ▪ Via CSW harvest of Geopunt metadata ▪ With filter on keyword “Open data in Flanders” ▪ Mapping to DCAT (XSLT: ISO 19139 to DCAT) ▪ Mapping to CKAN
  110. 110. Geo > Open 113
  111. 111. Open Discussion Bruno Koninckx THOMAS MORE @brunokon #opentourism
  112. 112. Open Discussion
  113. 113. Anastasia @natadimou Raf @rafke Bruno @BrunoKon
  114. 114. Join our community! http://tourism.openknowledge.be #opentourism |raf{dot}buyle{at}okfn{dot}be
  115. 115. A world where knowledge creates power for the many, not the few. A world where data frees us — to make informed choices about how we live, what we buy and who gets our vote. A world where information and insights are accessible — and apparent — to everyone. This is the world we choose #openbelgium16 #opentourism

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