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How to design smart tourism destination: From viewpoint of data

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

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How to design smart tourism destination: From viewpoint of data

  1. 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. 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. 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. 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. 5. Kyoto University Shift of Tourism Services EU-Japan Workshop on Big 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. 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. EU-Japan Workshop on Big 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. 7. Kyoto University What kind of data is necessary? EU-Japan Workshop on Big 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. 8. Kyoto University Collecting Regional Data is Difficult EU-Japan Workshop on Big 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. 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. 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. 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. 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. 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. 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. EU-Japan Workshop on Big Data for Sustainability and Tourism 14
  15. 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. 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. 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. EU-Japan Workshop on Big Data for Sustainability and Tourism 17
  18. 18. Kyoto University EU-Japan Workshop on Big Data for Sustainability and Tourism 18
  19. 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. EU-Japan Workshop on Big Data for Sustainability and Tourism 19
  20. 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) EU-Japan Workshop on Big Data for Sustainability and Tourism 20 Data Technology Service Coexistence of Tourists and Inhabitants From the viewpoint of informatics ….

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