Titi

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Touristic Intelligence Tirol (TiTi)

Dieter Fensel, Andreas Lackner, Christian Maurer, and Bernhard Rieder

with the help of ...

1STI Innsbruck

With the help of …

Birgit JuenZaenal Akbar Dr. José María GarcíaDr. Anna Fensel

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Dr. Nelia Lasierra Ioannis Stavrakantonakis Serge TymaniukDr. Ioan Toma

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What is the talk about?

• The Challenge: Successful value generation through Tourisms in the 21st century

• An essential means: A shared IT infrastructure for effective and efficient marketing and sales.

• Follow-Up opportunities

• Summary

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y

The Challenge

Successful value generation through Tourisms in the 21st century

4STI Innsbruck

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The Challenge

The Hotelier of today has to deal with many different communication channels:

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HOTEL RECEPTION

The Challenge

- walk-in customerThe Hotelier of today has to deal with many different communication channels:

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HOTEL RECEPTION

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- walk-in customer- phone


The Challenge

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HOTEL RECEPTION

The Challenge

- walk-in customer- phone-email


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HOTEL RECEPTION

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The Challenge

- walk-in customer- phone- email- fax


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HOTEL RECEPTION

The Challenge

- walk-in customer- phone- email- fax- hotel website


hotel website

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HOTEL RECEPTION

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The Challenge



- review sites

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HOTEL RECEPTION

The Challenge



- review sites- booking sites

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HOTEL RECEPTION

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The Challenge



hotel website- review sites- booking sites- social network sites

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HOTEL RECEPTION

The Challenge

The Hotelier of today has to deal with many different communication channels: - walk-in customer- phone- email- fax- hotel websitehotel website- review sites- booking sites- social network sites- blogs

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HOTEL RECEPTION

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The Challenge

The Hotelier of today has to deal with many different communication channels: - walk-in customer- phone- email- fax- hotel websitehotel website- review sites- booking sites- social network sites- blogs- fora & destination sites

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HOTEL RECEPTION

The Challenge

The Hotelier of today has to deal with many different communication channels: - walk-in customer- phone- email- fax- hotel websitehotel website- review sites- booking sites- social network sites- blogs- fora & destination sites- chat

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HOTEL RECEPTION

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The Challenge

The Hotelier of today has to deal with many different communication channels: - walk-in customer- phone- email- fax- hotel websitehotel website- review sites- booking sites- social network sites- blogs- fora & destination sites- chat- video & photo sharin

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HOTEL RECEPTION

The Challenge

The Hotelier doesn’t only have to deal with an overwhelming number of communication channels but also haschannels, but also has to pay up to 15% sales commissions to the booking sites!-> 100 million € sales

commission

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HOTEL RECEPTION

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The Challenge

-> 80 million overnight stays-> 4 billion € transaction

volume

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HOTEL RECEPTION

The Challenge

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source: http://infographicsmania.com/online-travel-statistics-2012/

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The Challenge

• More than 55% of all tourists in Central Europe inform themselves on-line about a certain destination before booking, and more than 27% of

fall tourists in this area use internet-based booking channels for reserving their tourism plans. And this number is constantly growing!

• In 2008, 1 in 3 trips was booked through travel agencies whereas in 2012 it was only 1 in 5!

• Furthermore, 70% of all online bookings are influenced by social media!

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The Challenge

• Influence of Social Media to travel planning:

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http://eprints.bournemouth.ac.uk/19262/1/Fotis_et_al_2012_-_Social_media_use_and_impact_during_the_holiday_travel_planning_process.pdf

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The Challenge

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The Challenge

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The challenge

Key challenge are:

• Professional on-line marketing for attracting potential customers requires:

– Content of high quality and originality

– Visible presented at multiple places in various formats and adaptations

• Professional on-line sales for gaining customers requires:– On-line bookability

– Tight alignment of content and bookings opportunities (i.e., content and booking data)

– Multiple booking opportunities (fluid booking)

– Multi channel yield management and revenue optimization (swarm intelligence and big

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data)

• Obviously even more is needed to cover to full-fledged customer journey

The solution

A shared IT infrastructure for effective and efficient marketing and sales

26STI Innsbruck

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The kernel

Where we go …

Semantic Alignment

Semantic Annotations

Repository

Touristic Ontology TISs

CMSs

TSPs TAs Tirol Werbung

External Data (LOD)and Content

Semantic Search

g

Web pages

Social MediaChannels

Mobile Channels

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The kernel

Semantic Alignment


Repository

Touristic Ontology TISs

CMSs



Semantic Search

g

Web pages


Mobile Channels

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Repository

Touristic OntologyTISs

CMSs

.. and how we start:

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The kernel

Repository


CMSs

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The kernel - Repository

• “A content repository is a store of digital content with an associated set of datamanagement, search and access methods allowing application-independent accessto the content ” (Wikipedia 2013)to the content… (Wikipedia, 2013).

• In terms of CMS a repository acts as a ground layer for long-term storage, structureddata management and digital preservation.

• Common features:

– Data storage

– Data querying

– Data managementRepository

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– Data management

• Semantic repository is a store of structured data allowing– to store, query and manage the data,

– and automatically reason about the data by using ontologies as semantic schemata.

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• Efficient data access and collaborative data management allowing working with the same content consistently.

• Greater focus on digital preservation by better support of archiving, versioning, etc.

• Abstraction layer support for employing complex functionality in a uniform way.

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• Reasoning capabilities by implementing inference layers.

• Synchronization on the repository level.


• Native: Persistent storage systems with their own implementation ofRDF databases. Provide support for transactions, own query compilerand generally their own procedure language

– E.g., SwiftOWLIM, BigOWLIM , Sesame Native, AllegroGraph.

• Non-Native: Persistent storage systems set-up to run on third partyDBs.

– E.g. Jena SDB.

• In-Memory: RDF Graph is stored as triples in main memory

E S iftOWLIM All G h S N ti

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– E.g. SwiftOWLIM, AllegroGraph, Sesame Native.

• Non-in-Memory: RDF Graph is stored not in main memory

– E.g. BigOWLIM, AllegroGraph.

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• AllegroGraph is a native RDF graph database:– Scaling to billions of triples

– Support of RDF/XML, N3, N-Triples serialization formatsSupport of RDF/XML, N3, N Triples serialization formats

– SPARQL, PROLOG queries

– Built-in reasoners (Jena, Sesame, Racerpro)

– Free and Commercial versions.

• Virtuoso is a native, RDBMS-based semantic repository:– Scaling to billions of triples

– Support of RDF/XML, N3 serialization formats

– SPARQL/SPASQL queries

– Built-in reasoners (Jena, Sesame, Redland)

Free and Commercial versions

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– Free and Commercial versions.

• Oracle11g:– Scaling to millions of triples

– Support of RDF/XML, N-triples serialization formats

– SQL and SPARQL queries

– Native inferencing and 3rd party reasoned support (Jena)

– Commercial version.


• OWLIM is a scalable semantic repository which allows:

– Management, integration, and analysis of heterogeneous data

– Combined with light-weight reasoning capabilities

– Available as a Storage and Inference Layer (SAIL) for Sesame Open RDF

• Sesame’s infrastructure

• Support for multiple query language (RQL, RDQL, SeRQL)

• Support for import and export formats (RDF/XML, N-Triples, N3).

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• SwiftOWLIM: in-memory reasoning and query evaluation, fast retrieval, query evaluation, scales to ~100M statements.

• BigOWLIM: more scalable not-in-memory enterprise class repository.

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The kernel - Ontology

• Define a domain-specific data model in the repository.

• This touristic Ontology can be used to mediate between different data models reducing the mapping problem from n! to n .

Repository

Touristic Ontology

mapping problem from n! to n .

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The Problem Multiple & heterogeneous sources of information


- Different formats & structures- Common usage purpose

- Touristic Information Systems- Content Management Systems- Web pages- Social Media Channels

Mobile Channels

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- Mobile Channels- External Data (LOD) and Content- Hotel on-line content and data- Content and data of the various touristic associations- Content and data of the Tirol Werbung

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The Solution Touristic Ontology

Integration Layer to provide a common and clear understanding to:

Touristic Ontology

- Unify data & management

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Repository

First … what is an ontology?

“An ontology is a formal explicit specification of a shared conceptualization”


An ontology is a formal, explicit specification of a shared conceptualization Studer, Benjamin, Fensel. Knowledge Engineering: Principle and Methods. Data and knowledge engineering, 25 (1998) 161-197

In simple words….

• Ontologies represent concepts and basic relations for the purpose ofcomprehension of a knowledge domain area. To develop an ontologymeans to formalize a common view of a certain area.

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• Ontologies model knowledge about a specific domain.

• They provide a common vocabulary, the meaning of the terms and also therelation among the terms in order to provide a common and sharedunderstanding for the comprehension of a domain.

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Specifically, in the Tourism domain…Vocabulary and relations for describing hotel elements and characteristics.


• Example of a Tourism ontology: Accommodation Ontology Metadata[University of Innsbruck, Martin Hepp]

– This Accommodation Ontology is an extension of GoodRelations.

– Provides the additional vocabulary elements for describing hotel rooms, hotels, camping sites, and other formsof accommodations, their features, and modeling compound prices as frequently found in the tourism sector,e.g. weekly cleaning fees or extra charges for electricity in vacation homes based on metered usages.

– http://ontologies.sti-innsbruck.at/acco/ns.html

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• Schema.org vocabularies- Schema.org provides a collection of shared vocabularies webmasters can use to mark up their pages in ways that

can be understood by the major search engines.

– LodgingBusiness > Hotel , Bed &Breakfast, Hostel, Motel

– Also vocabularies for describing events, restaurants & touristic attractions


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Repository

Touristic Ontology

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Schema.org vocabularies (Example: http://schema.org/Hotel)

Property ExpectedType Description

description Text A short description of the item.

image URL URL of an image of the item.

name Text The name of the item.

review Review A review of the item.

telephone Text The telephone number

location Place or PostalAddress The location of the event, organization or action.

i H D ti Th i h f b i

Thing

Place

Organization

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openingHours Duration The opening hours for a business.

priceRange Text The price range of the business, for example $$$.

paymentAccepted Text Cash, credit card, etc.

LocalBusiness

Which is the added value of the ontology?

- Common knowledge model Clear understanding


- Common knowledge model Clear understanding

- Integration layer - Reduce the number of mappings between information sources (n:n n:1) from n! to n.

- Provide a background knowledge for systems to automatize certain tasks. Can be used to perform meaningful and inteligent queries Semantic Search

- Allows to exchange data and to interpret the information in the data that has been

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Allows to exchange data and to interpret the information in the data that has been exchanged in the right context Semantic Alignment

- Allow the creation of machine readable annotations Semantic Annotations

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Touristic Information Systems include:

• Property Management Systems,

H l I f i S

The kernel – Touristic Information Systems

• Hotel Information Systems,

• Points of Sales,

• Accounting and Payroll Systems,

• Inventory control Systems,

• Booking and B ki Ch l

Repository


CMSs

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Booking Channel Management Systems.


Information integration and use across these systems is not a trivial task, because:

foundations and concepts behind backend solutions for e Tourism• foundations and concepts behind backend solutions for e-Tourism (Touristic Information Systems) vary.

• knowledge on the backend solutions for e-Tourism and the functionalities they provide needs to be applied in a consistent manner.

• existing implementation of backend systems and their use in practice varies.

• being able to select, in the light of concepts, functionalities and existing solutions the appropriate backend system for a given tourism business

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solutions the appropriate backend system for a given tourism business setting and make that easily interoperable is essential.

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Import of data from Touristic Information Systems (TISs) will facilitate multi-platform touristic operation, such as:


• unifying principles and methods that enable bookings electronically;

• enabling advanced concepts on booking, direct and multi-channel booking;

• understanding, anticipation and influencing tourists behavior in order to maximize hotel yield or profits;

• facilitating getting a clear overview of the varieties in booking software

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solutions available on the market;

• making the appropriate solution choices and apply booking and yield management practically.


Addressing the needs of various stakeholders with the ontologized layer for integration of TISs data:

• Tourists, e.g.:– Effective integrated availability of offers availability data

– Possibility to more efficiently combine available offers

• Hotels and tourism service providers, e.g.:– Improved information and process management across heterogeneous TISs

– Receiving data across TISs to enrich their own data and content (e.g. linking to the events in the area which could draw tourists)

• Touristic associations, e.g.:

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, g– Enabled easier access to the data from hotels and other tourism service providers

– Possibility to easier combine and aggregate data, serve as a better intermediary

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The kernel – Content Management Systems

Import from and export to Content Management Systems (CMSs)

Repository


CMSs

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• 38,4% of the websites use Web Content Management Systems and the CMS market share is constantly increasing (W3Techs.com report, Nov. 2013)

• CMS is referred to “a computer program that allows publishing, editing and modifying content as well as maintenance from a central interface” (Wikipedia, 2013).

• Types:– Component Content Management System (CCMS)

• Methods and tools for managing and storing re-usable assets, concept items, topics within documents.

– Enterprise Content Management Systems (ECMS)

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Enterprise Content Management Systems (ECMS)

• Methods and tools for managing and storing enterprise’s content and documents related to organizational processes.

– Web Content Management System (WCMS, often referred as CMS)

• Methods and tools for online and/or offline managing and storing the website content.

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• Adding, editing, delivering, sharing, retrieving, analyzing, controllingand administering online content.

• Uses content repository or a database for data storage.

• Supplied as off-the-shelf or custom-developed tailored to specificneeds.

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• Based on content and design separation.

• Presentation layer consists of basic CMS templates, which act as a webpage blueprint.

• Dynamic page creation on demand through data extraction from database/content repository.

Customization is achieved by adding plug ins with custom features

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• Customization is achieved by adding plug-ins with custom features.

• Major technologies used: Java, PHP, Python, MySQL, Perl.

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44%Use a CMS

system

38%Use a CMS

system

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WCMS distribution of Austrian hotels

WCMS distribution world-wide

W3Techs.com, Nov.2013

Feature 1: Sharing of Content and Data

Solving the Data and Content Bottleneck: Content and Data sharing between different touristic agents

Repository


CMSs

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Feature 1: Sharing of Content and Data

Solving the Data and Content Bottleneck: Content and Data sharing between different touristic agents.

• Successful on-line marketing requires high and up-to-date quality on-line content.

• Successful on-line sales requires and up-to-date booking data describing available offers and their• Successful on-line sales requires and up-to-date booking data describing available offers and their prices.

• Providing these at the proper level of quantity, quality, and up-to-date is rather cost-intensive and therefore a major obstacle.

• This problem appears at the layer of the

• Touristic service provider

• Touristic association

• Tirol Werbung

• Large budgets are spent on this issue and many web presences miss a lot of potential due to the related costs.

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• Therefore, we propose an infrastructure that makes sharing of content and data easy and cheap.

• Based on injecting content and data in our kernel it can be easily exported towards the on-line presence of a certain agent as well as it can be shared with and reused by other touristic agents.

Feature 2: Enrichment

Solving the Data and Content Bottleneck: Enrich with external content and data

Repository


CMSs

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Web of Content

The Web is a web of content The Web is a web of content

Content is any textual, visual or aural information that could be found on the

websites.

For a specific entity, e.g. a hotel, we can find on the Web a lot of content

scattered across various websites.

Review sites

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Sharing sites

Wikis

etc.


• Web of Content

Web of content

VideosTextReviewSites

Wikipedia

VimeoYouTube etc.

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ImagesFlickr Picasa etc.

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― Content can be crawled or retrieved via APIs, like in Hotelnavigator and Trust You services

― Make it accessible through the kernel of the architecture

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• Web of Documents • Web of Data

Hyperlinks

Typed Links

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“Documents”“Things”

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• Characteristics:– Links between arbitrary things

• Web of Data

y g(e.g., persons, locations, events, buildings)

– Structure of data on Web pages is made explicit

– Things described on Web pages are named and get URIs

– Links between things are

Typed Links

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Links between things are made explicit and are typed

“Things”


• The Web of Data is envisioned as a global database

– consisting of objects and their descriptionsg j p

– objects are linked with each other

– with a high degree of object structure

– with explicit semantics for links and content

• Linked Data is about the use of Semantic Web technologies to publish structured data on the Web and set links between data sources.

6060 Figure from C. Bizer

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Facts:• 295 data sets• Over 31 billion triples• Over 504 billion RDF links between data sources

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Figure from http://www4.wiwiss.fu-berlin.de/lodcloud/state/, September 2011


• Linked Open Data can be seen as a global data integration platform– Heterogeneous data items from different data sets are linked to each other following the

Linked Data principlesLinked Data principles

– Widely deployed vocabularies (e.g. FOAF) provide the predicates to specify links between data items

• Data integration with LOD requires:1. Access to Linked Data

• HTTP, SPARQL endpoints, RDF dumps

• Crawling and caching

2. Normalize vocabularies – data sets that overlap in content use different vocabularies• Use schema mapping techniques based on rules (e.g. RIF, SWRL) or query languages (e.g. SPARQL

Construct, etc.)

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3. Resolve identifies – data sets that overlap in content use different URIs for the same real world entities

• Use manual merging or approaches such as SILK (part of Linked Data Integration Framework) or LIMES

4. Filter data• Use SIVE ((part of Linked Data Integration Framework)

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See: http://www4.wiwiss.fu-berlin.de/bizer/ldif/

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• Use LOD to integrate and lookup data about

– places and routes

f– time-tables for public transport

– hiking trails

– ski slopes

– points-of-interest

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• Open Streetmap• Google Places • Databases of government

– TIRIS

– DVT

• Tourism & Ticketing association • IVB (busses and trams) • OEBB (trains) • Ärztekammer• Supermarket chains: listing of products • Hofer and similar: weekly offers • ASFINAG: Traffic/Congestion data • Herold (yellow pages)

• Innsbruck Airport (travel times, airline schedules)

• ZAMG (Weather)

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(y p g )• City archive • Museums/Zoo • News sources like TT (Tyrol's major daily

newspaper) • Statistik Austria

• University of Innsbruck (Curricula, student statistics, study possibilities)

• IKB (electricity, water consumption) • Entertainment facilities (Stadtcafe,

Cinema...) • Special offers (Groupon)

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• Lots of public data sources

– public transportation - Verkehrsverbund Tirol - Innsbrucker Verkehrsbetriebe (IVB)

– public safety - avalanche - Tyrolean Avalanche Warning Service - traffic - Tyrolean Regional Hazard Warning Centre - weather - Tyrolean Regional Hazard Warning Centre

– public health services - regional hospitals/clinics

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- UMIT - health and life science university

– culture - cultural events (Tourismusverband Innsbruck, etc.)

- http://www.tirol.gv.at/kunst-kultur/

– and many more …

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• External content from web site, audio streams, videos and mobile devices

• New touristic services can be provided based on content but requires first:

– Content annotation

– Linking to content

– Enhanced content consumption and delivery

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Feature 3: Semantic Search

Solving the Search Problem: Increase visibility of contents!

Repository


CMSs

Semantic Search

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Solving the Search Problem: Increase visibility of contents!

• Providing the contents to be searchable is only one step to increase their visibility

A h i d t id l f t t id th t l t d f l h• A search engines need to consider several factors to provide the most relevant and useful search queries, including:

• Intent of the search the results should not based on the specific words used in the query, but more on the intent of the search

• Variations of words should consider tenses, plural, singular, etc.

• Synonyms give same results on any synonyms of the word in query

• Generalized and specialized queries should be able to set relations between generalized and specialized queries

• Concept matching should understand the broad concept of the query

• Natural language queries should be able to process the natural language used by the

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g g q p g g yusers

• Location of search should be able to provide results based on the current location of the search

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• Semantic search is designed to improve the traditional web searching by improving the search accuracy though the “meaning” of the documents made available for search.

• “Meaning” is established through a semantic model which essentially captures interrelationships• Meaning is established through a semantic model, which essentially captures interrelationships between syntactic elements and their interpretations.

• The semantic models allow for a more precise matching of queries against the documents.

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• Typically, semantic search engines rely on certain ontology structures which are built from concepts, properties, constraints and possibly axioms of the documents.

• Searching methodologies: RDF path traversal, keyword to concept mapping, graph patterns, logics.


Example: Increase the visibility of contents on Mobile Devices

• Typically, the documents are grouped into several main categories and sub-categories as shown at the picture.

• The sub-categories are dynamically shown according to the selection of their main category

• On desktop or personal computer, there is no problem to navigate to those sub-categories, ...

• but on the mobile devices (with limited resources), the sub-categories will be inaccessible decrease the visibility

Th f ti d l i i d t t

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• Therefore, a semantic model is required to represent those super and sub-categories relationships, such that performing a search to a main category will also include its sub-categories

• all documents will be visible to the search engine including on the mobile devices

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Feature 4: Semantic Alignment of Data and Content

Solving the Data and Content

Alignment Problem:

I th i t !Semantic Alignment

Increase the conversion rate!

Repository


CMSs

Semantic Search

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Solving the Data and Content Alignment Problem: Increase the conversion rate!

• Achieving visibility through high-quality content, proper dissemination, interaction and engagement with customers are essential corner stones in successful eTourismusengagement with customers are essential corner stones in successful eTourismus.

• However, what matters in the achieving booking volume in terms of numbers of bookings, achieved pricing, and required commission fees.

• Achieving a high conversation rate in relation to successful contents is what matters.

• In consequence, it is essential to align dissemination and communication of content with bookable touristic service offers, i.e., with data related to available booking offers.

• How can this be achieved in a scalable fashion with steadily changing content and context it is presented?

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• Semantic alignment is the automated process of determining correspondences between different data sources based on a semantic analysis of their relationships.

• A set of correspondences is also called an alignment• A set of correspondences is also called an alignment.

• Natural language analysis and matchmaking of semantic annotations can be used to dynamically establish such correspondences on the fly.

• Based on this different content and data sources of a related topic can be grouped and disseminated together automatically.

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Show together for: “I want to skii in Mayerhofen”

• Cool content with … booking data and service

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• Based on corresponding ontological characterization of both.

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Feature 5: Semantic Annotations

Provide SEO beyond

keywords and link farms:

S ti A t tiSemantic Alignment



Repository


CMSs

Semantic Search

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What are Semantic Annotations?


Innsbruck is the capital city of the federal state of Tyrol (Tirol),

located at 47°16′N 11°23′E.

The name of the Place It is contained in another Place -> Tyrol

In DeutschIn English

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Refers to Geo coordinates

Talks about a Place

In DeutschIn English

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Which is the added value of Semantic Annotations?


annotate

Search EnginesRead and index

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Which is the added value of Semantic Annotations?

d t dSearch engines understand the content of the pages.

Called “rich snippet” by Google

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“These rich snippets help users recognize when your site is relevant to their search, and may result in more clicks to your pages.” [4]

pp y g

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How do we create Semantic Annotations?

We need:We need:

• A technical way to add them

• A vocabulary with terms about the concept that we want to annotate

Vocabulary created byBing, Google, Yahoo!, Yandex

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to support the semantic annotationsand speak the same language with the

developers.


How could a hotel be semantically annotated?

Term Value

Name Grand Hotel Europa

Image http://www.innsbruck.info/[...]e.jpg

Logo http://www.innsbruck.info/[...]2.JPG

Address Südtiroler Platz 2, Innsbruck, 6020, AT

telephone +43 512 59 31

Fax number +43 512 58 78 00

Email info@grandhoteleuropa at

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Email [email protected]

URL http://www.grandhoteleuropa.at/

Description The Grand Hotel Europa combines two worlds[...]

Price range $$$

Payment accepted available credit cards, cash payment

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What categories of concepts do exist in schema.org?

For example:For example:

• …

• Event

• Organization, Hotel, Restaurant

• Offer

• Place

• Product

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• Review, Rating

• …


Summary

In TITi when we talk about Semantic Annotations we imply the usage of the• In TITi when we talk about Semantic Annotations we imply the usage of the schema.org vocabulary.

• The architecture could be extended to support more vocabularies (e.g. the Accommodation Ontology).

• The content is annotated automatically.

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Feature 6: Multi-channel Communication

Read and write in hundred

thousands of channels:

S l bl M lti h lSemantic Alignment


Scalable Multi-channel

communication

Repository


CMSs

Semantic SearchWeb pages


Mobile Ch l

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Channels


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Platform types

• Static Broadcasting• Static Broadcasting

• Dynamic Broadcasting

• Sharing

• Collaboration

• Group Communication

• Semantic-based Dissemination

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Static Broadcasting

Homepages / Static Websites

Homepage ExampleStatic Website Example

Entry in Wikipedia for Hotel Goldener Adler

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Although created through a collaborative process, Wiki websites can be considered static forms of online broadcasting as the information contained in them remains the same for long periods of time.

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Dynamic Broadcasting

• Small piece of content that is dependent upon constraints such as time and p p plocation.

• With Web 2.0 technologies have created dedicated means for publishing streams and interacting with content generated by users.

• Examples of platforms types (organized considering first the length of message and second – the level of interactivity):

N F d RSS

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• News Feeds: e.g. RSS

• Newsletters

• Email / Email lists

• Microblogs: e.g. Twitter, Tumblr

• Blogs: e.g. Blogger, BuzzFeed

• Social networks: e.g. Facebook, Google+, LinkedIn, Xing

• Chat and instant messaging applications: e.g. Skype, Talk, Meebo.


Sharing

• There are a large number of Web 2.0 websites that support the sharing of g pp ginformation items such as: bookmarks, images, slides, and videos, etc.

• Provided by hosting services (images, videos, slides are stored on a server).

• Can use specialized applications (see below) of features of other platforms and services (e.g. share photos through Facebook).

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• Examples: • Picture sharing: e.g. Flickr, Instagram, Picasa, Pinterest

• Slide sharing: e.g. Slideshare, MyPlick, Slideboom, Prezi

• Video sharing: e.g. YouTube, Vimeo, Videolectures

• Social Bookmark sites: e.g. Delicious, Digg, StumbleUpon

• Social News websites: e.g. Reddit.

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Collaboration

• Collaborative software helps to facilitate action-oriented teams working together p g gover geographic distances, and by providing tools that aid communication, collaboration and the process of problem solving.

• Examples: • Wikis: e.g. Wikipedia.

• Collaborative tagging: adding metadata to shared content, e.g. Delicious.

• Document & Application collaboration:

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e.g. Google Docs, EtherPad.


Group Communication

• Platforms for sharing and exchanging information but also to collecting feedback g g g gor discussing certain issues.

• Examples: • Social networks: e.g. Facebook, Google+, My Space, Xing, LinkedIn.

• Internet forums: e.g. Quora, Ask.com.

• Online discussion groups: e.g. Google Groups, Facebook Groups, Yahoo! Groups, Meetup, GroupSpaces, Windows Live Groups.

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Semantic-based Dissemination• Scope: add machine-processable semantics to the information

Search and aggregation engines can provide much better service in finding and gg g g p gretrieving information.

• Search Engine Optimization• Are potential customers finding your web site?

• Is it possible that potential customers might not be aware that your site exists?

• Do your targeted search terms have high search engine rankings?

• Does your website attract a large number of daily visitors?

Semantic Search:

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• Semantic Search:• Semantic search tries to understand the searcher’s intent and meaning of the query instead of

parsing the keywords like a dictionary.


Semantic-based Dissemination

• A (Semantic Web) vocabulary can be considered as a special form of (usually light-weight) t l ti l l ll ti f URI ith ( ll i f ll ) d ib dontology, or sometimes also merely as a collection of URIs with an (usually informally) described

meaning*.

• URI = uniform resource identifier

• Semantic vocabularies include: Schema.org, FOAF, Good Relations, Dublin Core.

• Format is an explicit set of requirements to be satisfied by a material, product, or service.

• The most known examples are RDF and OWL.

• Implementation realization of an application, plan, idea, model,

Format e.g. RDFa

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p pp , p , , ,

or design

• Semantic repositories.Implementation e.g. OWLIM

Vocabulary e.g. foaf

* http://semanticweb.org/wiki/Ontology

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Semantic-based Dissemination: Formats

<div xmlns:dc=http://purl.org/dc/elements/1.1/about="http://www example com/books/globaltourism">

• HTML Meta Elementsabout= http://www.example.com/books/globaltourism > <span property="dc:title">Global Tourism</span> <span property="dc:creator">William Theonbald</span><span property="dc:date">2004‐10‐01</span>

</div>

• RDFa

• OWL (OWL-Lite, OWL-DL,

OWL-Full, OWL2)

• RIF

• Microformats<ul class="vcard">

li l "f " J D /li

RDFa usage example

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• Microformats

• Microdata

• RDF

• SPARQL

<li class="fn">Joe Doe</li> <li class="org">The Example Company</li> <li class="tel">604‐555‐1234</li><li><a class="url“

href="http://example.com/">http://example.com/</a></li> </ul>

Microformats usage example


Semantic-based Dissemination: Vocabularies

• Schema.org

• Schemas for a large number of concepts and domains, such as creative works (e.g. movies, music, TV, shows), places, products, organizations, lodging businesses, etc.

• FOAF

• Uses RDF to describe the relationship people have to other “things” around them.

• FOAF permits intelligent agents to make sense of the thousands of connections people have with each other, their jobs and the items important to their lives.

• Good Relations

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• A lightweight ontology for annotating offerings and other aspects of e-commerce on the Web.

• The only OWL DL ontology officially supported by both Google and Yahoo.

• Dublin Core

• A set of vocabulary terms used to describe a full range of web resources: video, images, web pages etc. and physical resources such as books and objects like artworks.

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Channels:

• A channel is part of a platform specified by the type of information item it can handle.

<Platform>::<InformationItemType>::<AccountUID>

– Facebook :: Event :: STI account

– Facebook :: Image :: STI account

– Facebook :: Link :: STI account

– Facebook :: Video :: STI account

– Google+ :: MicroBlogPost :: STI account

G l I STI t

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– Google+ :: Image :: STI account

– Twitter :: Link :: STI account

– YouTube :: Video :: STI account


Challenges:

• Scalability– The overwhelming amount of available communication channels cannot be easily

managed by content publishers

• Costs– Social Media experts needed to handle communication channels

– Not feasible for hoteliers

• Domain personalization

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– Adaptation, alignment and definition of the content for several channels

– Generic and automatic solutions can be personalized to any domain

• Bilateral communication– Feedback and engagement

– Reputation management

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Web/Blog Conte

Content Semantic Alignment

Semantic AnnotationsCollect feedback

statistics

Social Web

Weaver

ent Extractio

n an

d Public

t/Chan

nel m

apping &

ad

Repository

Touristic Ontology

Semantic Search

Semantic Alignment

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Web 3.0/Mobile/Other

cation Laye

r

aptatio

n laye

r

Distribute content


Dynamic rules:

• Content is mapped & adapted to specific channels using business rules, pp p p g ,defined by domain experts

• Domain ontologies applied to map concepts with channels in rules

• Publication can be scheduled

• Feedback is collected to improve the engagement and adapt dissemination rules

whenThere is a new Event ev

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There is a new Event evthen

Publish ev in Facebook channelPublish ev in Drupal/News channel

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Feedback of Dissemination

Feedback collection:

Refers to the response of an a dience to a message or acti it• Refers to the response of an audience to a message or activity.

• Giving the audience a chance to provide feedback is crucial for maintaining an opencommunication climate.

• Views and clicks

• Unary feedback

• Binary feedback

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• Binary feedback

• Ratings

• Re-publication

• Comments:


Engagement process =

Infinite loop between the listening and responding steps, interweaving publishing and listeningpublishing and listening

Listen Analyze Understand Respond

In order to retrieve the desired information, several API calls have to be performed at the dissemination channels:• Fetching the amount of comments of a post

• Fetching all comment of a post

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g p

• Publish a comment to a post

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Outlook

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Feature 7: Additional Services

Additional services can be provided:

• Data analytics and swarm-based yield management

D i k i• Dynamic packaging

• Data Value chain

• Governmental reporting and governance

Semantic Alignment


Service Layer

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Repository


CMSs



Semantic Search

g

Web pages


Mobile Channels

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Data analytics and swarm-based yield management

• “is the discovery and communication of meaningful patterns in data. Itrelies on the simultaneous application of statistics, computer

f fprogramming and operations research to quantify performance.Analytics often favors data visualization to communicate insight.”

http://en.wikipedia.org/wiki/Analytics

•Large amount of data are usually process in order to uncover hidden patterns, unknown correlations or other useful information

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•That information can provide:– Advantage over competitors

– Business benefits

– Effective marketing and increased revenue


• Typical problems data analytics is used to:– Make predictionsp

– Understand systems

– Optimize functions

• Typical techniques used to implement

data analytics include:– Classification

– Regression

– Clustering

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Clustering

– Reinforcement learning

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From data to knowledge:

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http://www.slideshare.net/renuccif/data-analytics-session-1-2013-27929321?from_search=1

Data analytics and swarm-based yield management in Tourism

• Used for revenue management, capacity and network planning, inventory management, dynamic pricing, last-minute reservations

• Enables better understanding of tourists’ needs and preferences, which can be latter used to design a highly-customized sales and service process to meet those needs

• Helps revealing and analyzing causal relationships that explain the attractiveness of hotels or destinations and preference patterns of

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attractiveness of hotels or destinations and preference patterns of tourists

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• Hotels are confronted with a multitude of online booking channels.

• Hotels should provide their available rooms and their rates to most if not all of the channels to prevent not meeting their potential customers.

• In many channels, visibility is achieved through low prices.– However, often channels also require constraints on the price offers in other channels.

• Some channels generate costs without guaranteeing actual income.

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• A multi-directional multi-channel approach also must rely on Swarm intelligence.

• Observing in real time the reaction of customers and competitors is the key to achieving on-line marketing.

• Adopting your offer and your price dynamically in response to the behavior of your (on-line visible) environment becomes a key for economic success http://en.wikipedia.org/wiki/Swarm_intelligence

• Many solutions to yield management are based on complex statistical methods and complex domain assumptions on how variation of the price can influence the amount of bookings of a service

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price can influence the amount of bookings of a service.

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• Swarm intelligence support is an essential feature of the yield management.

• Yield management could be realized utilizing reputation and usage values collected from

– different channels, as well as

– tourism information systems.

• Key is the data and content available in Titi!

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Dynamic packaging

• Dynamic packages play a more and more important role in tourism

• Tourists want to buy not only single services but service packages

• Most touristic platforms offer the possibility to book a single service (e.g. hotel, flight, car, events) but few provide service packages

• Very often in order to build interesting packages, services offered

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y g p g ,by different online platform needs to be combined

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Dynamic packaging

• Data and services from from various providers can be integrated for booking g gpackages containing:

– Flight

– Hotels

– Restaurants

– Cultural and entertainment events

– Sightseeing

– Shops

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Dynamic packaging

• Service packaging involves:

– Understanding requirements and preferences

– Finding relevant services that can fulfill part of the overall request

– Composing relevant services from various sources in packages

– Having a single price for service packages

– Selecting and recommending the optimal

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Selecting and recommending the optimal service package

– Booking of the service package

– Realize player technology with our architecture

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Data Value Chain

“Your data is worth more if you give it away.”

Commission Vice President

Neelie Kroes

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Data Value chain

• A "DATA Value” based economy driven by the open data strategy

• It will enable and foster best possible social and commercial added value based on intelligent use, management and re-use of data sources in Europe.

• This will lead to– increased business intelligence and efficiency of private and public

sectors

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sectors

– world class applications

– new business opportunities involving SMEs - (open) data friendly policy and business environment

Based on Márta Nagy-Rothengass – Head of Unit, EC DG Information Society and Media keynote talk “Leveraging the data potential in Europe” at EDF2012

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Data Value chain

• Non tangible assets (i.e. data) play a significant role in creation of the economic value.

Data is nowadays more important than for example• Data is nowadays more important than for example search or advertisement.

• The value of the data, its potential to be used to create new products and services, is more important than the data itself.

• New businesses can be built on the back of this data.

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• Data is an essential raw material for a wide range of new information products and services.

• Facilitating re-use of this raw data will create jobs and thus stimulate growth.

Data Value chain

• Open Data can be integrated into new products and services

• A whole new industry implementing services on top of large data sets is emerging.

• So…Data Value Chain in the Tourism domain refers to…

Chain of activities performed to get profitable value of the Touristic data through different phases.

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Data Value Chain

To exploit data value chain, TiTi offers:

Service Layer• Integrated and uniform data layer

th t b d f diff t

• To export EDF (Einheitliches Daten Format), OTDS

Repository

Touristic Ontology

Semantic Search

Semantic Alignment


that can be used for different purposes in the tourism domain.

• Hub functionalities: allows to repeat through all its output channels an input data.

(Open Travel Data Standard).

• Semantic infrastructure to be used under a multi-purpose service layer for different touristic activities.

Which can be used…

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-To promote coordination between different players Coordination of services

E.g Travel agency + hotel+ Tour+ Bus services

Data Value Chain

Example in the Touristic area: Tourism Association

EDF

Resell and package touristic offers

Semantic Search

Semantic Alignment


Service Layer

EDFGlobal TypsODTS

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Repository

Touristic Ontology

Hotel

Rooms availability

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Governmental reporting and governance

• Governments need data from strategic sectors– To measure performance, analyze risks, foresee trends…

– To inform strategic decisions

– For policy making

• Opening up data will give allow businesses to– comply with regulations

– sell data-related services to government

– improve collaboration with local governments

– provide insight into investment and innovation

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– support public-private partnerships

• Example in the touristic sector – Data from bookings can be used to analyze tourism trends, make new policies, target

specific groups…Based on “Open Data: Driving growth, ingenuity and innovation”, Deloitte 2012. Available online at http://www.deloitte.com/assets/dcom-unitedkingdom/local%20assets/documents/market%20insights/deloitte%20analytics/uk-insights-deloitte-analytics-open-data-june-2012.pdf

Summary

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The Problem

• The number of people who plan and book their travel activities online is steadily growing.

• This confronts touristic service providers with many new challenges– To attract potential customers they have to be present in a multitude of channels

in various formats and adaptions.

– The content in the various channels should be of high quality and originality.

– There should be multiple online booking opportunities for their offers (fluid booking).

– Multi channel yield management and revenue optimization is necessary.

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HOTEL RECEPTION

The overall picture

Service Layer

Repository


CMSs

Semantic Search

Semantic Alignment


Web pages


Mobile Channels

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Key elements of our solution

The Kernel:

•A repository for structured data management and digital preservation.

•An Ontology to mediate between different data models•An Ontology to mediate between different data models.

•The import from Touristic Information Systems (TISs).

•The import and export from Content Management Systems (CMS).


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Repository

Touristic Ontology

CMSs

Key elements of our solution

The Features:1.The sharing of content and data between different touristic agents.

2 The enrichment with external content and data2.The enrichment with external content and data.

3.Increased visibility of content using Semantic Search.

4.Increased conversion rate using Semantic Alignment of Data and Content.

5.SEO beyond keywords and link farms using Semantic Annotations.

6.Scalable Multi-channels communication.

7.Additional Services:D t l ti d b d i ld t

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– Data analytics and swarm-based yield management

– Dynamic packaging

– Data Value chain

– Governmental reporting and governance

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Questions?

Questions??

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Titi

Presentations & Public Speaking

hotel reception

customer phone

email fax

customerthe hotelier

fora destination sites

sti innsbruck

anna fensel

andreas lackner