This is the presentation material for the EU-Japan Workshop on Big Data for Sustainability and Tourism at Hamburg University in 8th March 2017.

1. Kyoto University
How to Design Smart Tourism
Destination:
From Viewpoint of Data
Hidekazu Kasahara,
Masaaki Iiyama, Michihiko Minoh
Kyoto University
1
EU-Japan Workshop on Big
Data for Sustainability and
Tourism

2. Kyoto University
Contents
Background and Research Objectives
Regional Data
Tourism Service Portfolio
Regional Data Platform
Conclusions and Future Works
EU-Japan Workshop on Big
Data for Sustainability and
Tourism 2

3. Kyoto Univ.
Background
Tokyo Olympic in 2020
Governmental Policy (MIC/ METI/ JTA)
To promote tourism services using
IoT/ Big data/ Artificial intelligence technology.
This can be called “smart tourism services.”
However, no standard concept for developing smart
tourism services in the destination.
What’s smart tourism services.
How and who provides.
What kind of data are required.
Enter2017 3

4. Research Objectives
Design new standard concept for developing
smart tourism services in the destination from
the viewpoint of informatics.
What’s smart tourism
What’s the most important problem
How to solve the problem
Enter2017

5. Kyoto University
Shift of Tourism Services
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Data for Sustainability and
Tourism 5
Traditional Tourism
Mainframe Flight Booking
e Tourism
Internet
Web-based
technology
Room Reservation
Web Guide and Map
Smart Tourism
Machine Learning
Mobile & Sensor
Internet of Things
Big Data
Real-time Recommendation
Evacuation Support
Traffic Congestion Avoidance
Resource Optimization
50-60s
90-00s
00-10s
Personal
Real time

6. Kyoto University
Difficulty of Data Collection
Intelligent information processing requires vast amount of data.
Various data holders collect data independently in destinations.
Service providers and data holders are not always the same.
It is difficult for ventures to develop smart services.
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Data for Sustainability and
Tourism 6
Dat
a
Tech
nology
Servic
e
How to collect data?
Which data to be collected?
Technical and social
issues.

7. Kyoto University
What kind of data is necessary?
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Data for Sustainability and
Tourism 7
Regional Data (RD)
with Global Attribute
Dynamic Data
Static Data
Statistical
Data
Statistically
Integrated
Available in shot time
ex. GPS tracks
Smart Service Requires Dynamic Data.
Available in long time
ex. Map, Time table

8. Kyoto University
Collecting Regional Data is Difficult
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Data for Sustainability and
Tourism 8
Recently
Publicized
as Open Data
Traditionally
Publicized as
Open Data
Type Data Global Attribute
Dynamic
Data
● Tourist location
● Sales transaction
● Surveillance camera
● Transportation status
● SNS post
● Climate
● Transportation (Taxi, Bus, Train, etc)
● Disaster alert
● No
● No
● No
● No
● No
● No
● No
● No
S t a t i c
Data
● Event
● Public facility (Toilet, AED, Police,
etc)
● Tourist spot data
● Time schedule
● Road network
● Geographical map
● No
● No
● No / Yes
● No / Yes
● Yes
● Yes
Statistic
al Data
● Tourist statistics
● Population statistics
● Weather statistics
● Sales statistics
● Yes
● Yes
● Yes
● Yes
Difficult to
collect

9. Kyoto University
Issues of Regional Data (RD)
Ownership
RD has collected by various owners.
RD owner has motivation to keep the RD inside.
Probe car data ➔ Car navigation, auto maker
Location data ➔ mobile carrier
Surveillance camera ➔ Retail, rail
Data Giant （Google, Apple, Facebook , Amazon)
They collect dynamic data via services.
They play leading role in developing smart services.
New smart service providers try collecting RD independently, but can
collect too small number of RD to machine learning.
Easy access to RD promotes smart services.
9
EU-Japan Workshop on Big
Data for Sustainability and
Tourism

10. Kyoto University 10
Public Private Data Collaboration
Open Access RDClosed Access RD
Private Entities Public Entities
Provided
via API
Dynamic Data Static/Statistic Data
Usage is Not Limited
GPS Traj. SNS
Post
Transaction
Biological
Video
Weather
Population
Road Map
Disaster
Regional Data Owners
How to collect dynamic data
owned by private sector?
Usage is Limited
EU-Japan Workshop on Big
Data for Sustainability and
Tourism

11. Kyoto University 11
Public Private Data Collaboration
Open Access RDClosed Access RD
Private Entities Public Entities
Provided
via API
Dynamic Data Static/Statistic Data
Usage is Limited to Members in
Closed Market
Usage is Not Limited
GPS Traj. SNS
Post
Transaction
Biological
Video
Weather
Population
Road Map
Disaster
Regional Data Owners
Tourist Service Portfolio (TSP)
TSP Priorities DataTSP Priorities
Data
EU-Japan Workshop on Big
Data for Sustainability and
Tourism

12. Kyoto University 12
Service User
Tech
nology
Static Data Dynamic Data
Current
Service
Priorit
y
Offline Map Tourist
Map
(Toilet, Police box, ATM, Cycle,
Parking, Tourist Spot, AED)
Event Only Private A
Transfer Guide Tourist Time table, Map Yes -
SNS post Analysis DMO
Statistical
Analysis
SNS post No A
Travel Guide Tourist
Tourist Spot Data,
Tourist Spot, Tourist Route
Yes A
Disaster Alert
Tourist/
Inhabitant
Disaster Data Yes A
Route
Recommendation
Tourist Recommen
dation
Tourist Spot, Tourist Route
Tourist Trajectory,
Climate Data
No B
Spot
Recommendation
Tourist Recommen
dation
Tourist Spot, Tourist Route
SNS post, Tourist Trajectory,
Climate Data
No B
Congestion Forecast
Tourist/
Inhabitant/
DMO
Positon
Data
Analysis
Tourist Trajectory,
Transportation Trajectory
No C
Bus Arrival Forecast
Tourist/
Inhabitant
Positon
Data
Analysis
Map
Tourist Trajectory,
Bus Trajectory
No C
Tourism Service Portfolio (TSP)
EU-Japan Workshop on Big
Data for Sustainability and
Tourism

13. Kyoto University
Regional Data Platform (RDP)
13
Private Sector
Data Public Sector Data
Data Processing for Services
Preprocessing (Incl. Privacy)
Regional Data Platform
(RDP)
Smart Service
Portfolio (STP)
Making STP
Data Collecting
based on STP
Smart Service
Provider
Private Data
Holder
Public Data Holder
RDP collects RD from various data owners, and transforms the collected RD, to the symbol data
by using intelligent information processing, distributes the symbol data.
Data Data
Data
(ex. Mobile Carrier, Rail, Retail) (ex. Government)
University
Government
Incubation
Support
EU-Japan Workshop on Big
Data for Sustainability and
Tourism
Regional Round Table for Making TSP

14. Kyoto University
Activities in Kyoto
Collaboration with Kyoto university, Kyoto city
and Kyoto prefecture.
We will start a workgroup for implementing
sample case.
Ventures/ Local governments/ University
Symposium for publication.
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Data for Sustainability and
Tourism 14

15. Conclusions
For developing smart services for tourism destination, how to
collect the data is key. (Characteristics of AI)
Smart service providers and data owners are not always
the same. (Exceptions are data giants like GOOGLE)
The situation prevents sustainable service development in
destinations.
Data are owned by data owners in destinations.
The data owners do not know the need for their data.
So, by listing required data, we can facilitate data exchange
among data owners and service providers.
The list is called as “Tourism Service Portfolio (TSP).”

16. Conclusions
Usage is Limited to Members
in Closed Market
Usage is Not Limited
Tourist Service Portfolio (TSP) TSP Priorities DataTSP Priorities
Data
Open Access RDClosed Access RD
Private Sector Public Sector
Provided
via API
Dynamic Data Static/Statistic Data
GPS Traj. SNS
Post
Transaction
Biological
camera
Weather
Population
Road Map
Disaster
Regional Data Owners
Service Providers

17. Kyoto University
Conclusions and Future Works
TSP and RDP based on new data exchange
framework named “private public data
collaboration” for realizing smart destinations.
In future,
International comparison of existing services.
Standard TSP should be studied under
consideration of the current service status and
technical advances.
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Data for Sustainability and
Tourism 17

18. Kyoto University
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Data for Sustainability and
Tourism 18

19. Kyoto University
Smart Tourism Definition
Tourism supported by real-time and personalized tourism
services based on a list of required services
in a destination with use of intelligent information
processing, and regional data (RD) collected
in the destination for promoting on-site experiences of
tourists and coexistence with inhabitants and tourists.
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Data for Sustainability and
Tourism 19

20. Kyoto University
Previous Research
“Tourism supported by integrated efforts at a destination to collect and
aggregate/harness data derived from physical infrastructure, social
connections, government/organizational sources and human bodies/
minds in combination with the use of advanced technologies to
transform that data into on-site experiences and business value-
propositions with a clear focus on efficiency, sustainability and
experience enrichment.“ (Gretzel et al. 2015)
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Data for Sustainability and
Tourism 20
Data
Technology
Service
Coexistence of
Tourists and
Inhabitants
From the viewpoint of informatics ….