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.

1. #openbelgium15 #opentourism
A community supporting Digital Creativity in Tourism

2. Cause and context
Raf Buyle - Open Knowledge
@rafke #opentourism

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. WHAT
Information often can't be reused without analizing
the data or building expensive custom connectors

5. WHAT
COULD
BE?
Linked Open Data aims to connect these solitary pieces
of information to other data sources on the web.

6. WHAT
SHOULD
WE DO?
we need more Open Data and a common
language for machine readable touristic
information.

7. Joined forces with ‘sustainable mobile tourism
guides’, Thomas More - iMinds

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. 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. priorities both as data
producer and as data
consumer

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. 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. Open Tourism hackathon
🗸 DATA
🗸 TOOLS
🗸 APP’S
🗸 FEEDBACK
http://www.mobielegidsen.be/hackathon/

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. Release Open Tourism Communty Site
● Mailing list
● Tools and resources
● The Open Standard for Tourism Ecosystems Data
Specification
● News on the upcoming events

16. Join our community! tourism.openknowledge.be

17. Join our community! tourism.openknowledge.be

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. 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. Getting started with
the Open Tourism Specification
Bruno Koninckx
THOMAS MORE
@brunokon #opentourism

21. Which domains are covered (for now)?
➔ Offering
What? By whom?
➔ Availability
Where? When?
➔ Experience
How?
➔ Demand

22. Offering
Availability
Experience
Demand

23. Availability Demand
Offering

24. Experience Offering

25. Demand
Offering

26. Specifications
http://w3id.org/ost/spec
Questions, remarks, issues on the domain model and
specifications via:
https://github.com/openknowledgebe/tourism/issues

27. Publising and Consuming
Linked Tourism Data
Anastasia Dimou - iMinds - Data Science Lab
@natadimou #opentourism

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. What is the Semantic Web?

30. The Semantic Web
is the extension of the World Wide Web

31. Are you the owner of your data?
OR
is the application that hosts your data?

32. The Semantic Web
is the extension of the World Wide Web
enables sharing content beyond
the boundaries of applications & websites

33. the Web for humans, thanks to HTML,
is understandable & constant
BUT
is the Web for machines too?

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. Semantic Web enabled applications
rely on data represented as Linked Data

36. What is Linked (Open) Data?

37. Linked (Open) Data
a standardized way of
expressing the relationships between data

38. Linked (Open) Data
a standardized way of
expressing the relationships between data
semantically annotated the data
with different vocabularies or ontologies

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. Where does Linked Data come from?

41. Linked (Open) Data
is often derived from originally
heterogeneous (semi-)structured data

42. Linked Open Data
from Not Open Data

43. Linked Open Data
from Not Open Data
from Open Data

44. Linked Open Data
from Not Open Data
from Open Data
from their combination

45. How is Open Data published?

46. The DataTank
open source RESTful data management system

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. The DataTank
supported data formats
CSV and XLS
XML
JSON(-LD)
SHP
RDF
MySQL
SPARQL

49. How is Linked (Open) Data published?

50. Linked (Open) Data
published in the form of RDF datasets

51. Resource Description Framework (RDF)
is the prevalent data model
for describing Linked (Open) Data

52. Resource Description Framework (RDF)
is the prevalent data model
for describing Linked (Open) Data
predicate
subject object

53. Resource Description Framework (RDF)
is the prevalent data model
for describing Linked (Open) Data
driven by unique identifiers (URIs)
predicate
subject object

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. How is Linked Data derived
from (semi-)structured data?

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. Person 1 Data Science Labworks
“Anastasia Dimou”
locatedDataScience Lab Ghent
Person 2 Data Science Labworks
“Ruben Verborgh”
Person 3 DataScience Labworks
“Erik Mannens”

58. Person {id}
{lab}
Assign unique identifiers (URIs)
“{firstname}
{surname}”

59. Person {id}
{lab}
Assign unique identifiers (URIs)
“{firstname}
{surname}”
http:://ex.com
{id}
http://ex.com{lab}
“{firstname}
{surname}”

60. Annotate data relationships with ontologies
http:://ex.com
{id}
http://ex.com{lab}
“{firstname}
{surname}”

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. 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. ex:{id}
ex:{lab}
ex:located
ex:{lab} ex:{city}
sets of triples of a dataset have repetitive patterns
“{firstname}
{surname}”

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. What are the different
Linked Data Generation approaches?

66. Linked Data generation approaches
case-specific solutions

67. Linked Data generation approaches
case-specific solutions
OR
format and source specific

68. Data OWNER / PUBLISHER
CSV JSONXML
RDF RDF RDF

69. R2RML mappings R2RML processor
Data OWNER / PUBLISHER
defines
RDF
DB CSV JSONXML
RDF RDF RDF

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. Why not a uniform approach?

72. Uniform and declarative RDF generation
from heterogeneous data sources
mappings processor
Data OWNER / PUBLISHER
defines
RDF
DB CSV JSONXML RDF

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. Uniform and declarative RDF generation
from heterogeneous data sources
RML mappings processor
Data OWNER / PUBLISHER
defines
RDF
DB CSV JSONXML RDF

75. Defining Mappings to generate Linked Data
Retrieving Input Data
Editing Mappings

76. Defining Mappings to generate Linked Data
Retrieving Input Data
Editing Mappings

77. RML describes
how to generated RDF
from structured data
predicate
subject object

78. RML describes
how to generated RDF
from structured data
predicate
subject object
Predicate Map
Subject Map Object Map

79. RML describes
how to generated RDF
from structured data
predicate
subject object
Predicate Map
Subject Map Object Map
<#TriplesMap>

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. 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. Extraction Module Mapping Module
RML Processor

83. Defining Mappings to generate Linked Data
Editing Mappings
Retrieving Input Data

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. Specifying data
which data form a data input
how to reference data input extracts
Accessing & Retrieving data
data input from original source(s)

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. Support data in Heterogeneous Structures
tabular-structured
hierarchical-structured
(semi-)structured
… … …

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. 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. 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. Specifying data
which data form a data input
how to reference data input extracts
Accessing & Retrieving data
data input from original source(s)

92. Input
data
Input
data
Input
data
Output
RDF
Mapping
module
RML
Processor
Map doc

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. Support different Locations and Access Interfaces
Local File(s)
Database connectivity
Web source(s)
RDF source(s)

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. 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. Defining Mappings to generate Linked Data
Retrieving Input Data
Editing Mappings

98. Semantic Web experts Vs. Data specialists

99. Semantic Web experts Vs. Data specialists
Modeling Domain Knowledge
as Linked (Open) Data
is not straightforward for
Data Specialists

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. Semantic Web experts Vs. Data specialists
Data Specialists
should be able to specify the mappings,
modify and extend them at any time

105. Defining Mappings to generate Linked Data
Editing Mappings
Retrieving Input Data

106. The five stars of the Linked Open Data scheme
should not be approached as a set of
consecutive steps

107. Well-considered policy regarding
mapping and interlinking of data
in the context of a certain
knowledge domain

108. GEO > OPEN
Geraldine Nolf
Flemish Information Agency
@natadimou #opentourism

109. > 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

110. > 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

111. > 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

112. 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

113. Geo > Open 113

114. Open Discussion
Bruno Koninckx
THOMAS MORE
@brunokon #opentourism

115. Open Discussion

116. Anastasia
@natadimou
Raf
@rafke
Bruno
@BrunoKon

117. Join our community!
http://tourism.openknowledge.be
#opentourism |raf{dot}buyle{at}okfn{dot}be

118. 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