Information Technology & Tourism

, Volume 21, Issue 4, pp 577–593 | Cite as

Open Tourist Information System: a platform for touristic information management and outreach

  • Pedro Lopes
  • Luís Almeida
  • João Pinto
  • Justino de Jesus
  • Didiana Fernandes
  • Isabel Vieira
  • Ricardo GamaEmail author
Case Study


In this paper, we present a generic, open source, touristic information system. The main objective of this platform is to promote the development of third-party applications based on a previously structured data and validated centralized common source of open information. The proposed system comprises an information management module and an extended set of web services enabling efficient information management as well as its use by third-parties such as web and mobile applications. It was designed with a modular functional architecture with the aim of being easy to implement and adapt in practical environments, as well as being user-friendly and having capability to grow. The entire system structure is discussed in detail. We test the use of the information system in a practical scenario, implementing it for the Douro World Heritage Region, Portugal. The web services developed are profiled in this real word setting through a wide set of performance tests. The results show that the end-to-end execution times of the web services functions make them suitable for standard tourism applications. These results establish concrete performance benchmarks for future applications.


Information system Information outreach Tourism Route planner 



The authors are deeply thankful to Nuno André and the anonymous reviewers for their helpful and constructive comments. This work was financed by the Instituto Politécnico de Viseu and Caixa Geral de Depósitos under the PROJCI&DETSCGD0017 project. Furthermore, we would like to thank the CI&DETS for their support.


  1. Ali A, Sirilertworakul N, Zipf A, Mobasheri A (2016) Guided classification system for conceptual overlapping classes in OpenStreetMap. ISPRS Int J Geo-Inf 5(6):87CrossRefGoogle Scholar
  2. APACHE (n.d.) Retrieved 14 March 2019
  3. Arenas AE, Goh JM, Urueña A (2019) How does IT affect design centricity approaches: evidence from Spain’s smart tourism ecosystem. Int J Inf Manag 45:149–162CrossRefGoogle Scholar
  4. AWS (n.d.) Retrieved 14 March 2019
  5. Bermbach D, Wittern E (2016) Benchmarking web API quality. Int Conf Web Eng 2722:277–284Google Scholar
  6. Borràs J, Moreno A, Valls A (2014) Intelligent tourism recommender systems: a survey. Expert Syst Appl 41(16):7370–7389CrossRefGoogle Scholar
  7. Chen TH, Shang W, Jiang ZM, Hassan AE, Nasser M, Flora P (2016) Finding and evaluating the performance impact of redundant data access for applications that are developed using object-relational mapping frameworks. IEEE Trans Softw Eng 42(12):1148–1161CrossRefGoogle Scholar
  8. Cipeluch B, Jacob R, Winstanley A, Mooney P, Ciepluch B, Jacob R, Mooney P (2010) Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps. In: Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciencesGoogle Scholar
  9. Douro Alliance (n.d.) Retrieved 14 March 2019
  10. Douro Valley (n.d.) Retrieved 14 March 2019
  11. Flask (n.d.) Retrieved 14 March 2019
  12. Fogli A, Sansonetti G (2019) Exploiting semantics for context-aware itinerary recommendation. Pers Ubiquit Comput. CrossRefGoogle Scholar
  13. Gavalas D, Konstantopoulos C, Mastakas K, Pantziou G (2014) A survey on algorithmic approaches for solving tourist trip design problems. J Heuristics 20(3):291–328CrossRefGoogle Scholar
  14. Gavalas D, Kasapakis V, Konstantopoulos C, Pantziou G, Vathis N, Zaroliagis C (2015) The eCOMPASS multimodal tourist tour planner. Expert Syst Appl 42(21):7303–7316CrossRefGoogle Scholar
  15. Gavalas D, Kasapakis V, Konstantopoulos C, Pantziou G, Vathis N (2017) Scenic route planning for tourists. Pers Ubiquit Comput 21(1):137–155CrossRefGoogle Scholar
  16. Girres JF, Touya G (2010) Quality assessment of the French OpenStreetMap dataset. Trans GIS 14(4):435–459CrossRefGoogle Scholar
  17. Goodchild M (2009) NeoGeography and the nature of geographic expertise. J Locat Based Serv 3(2):82–96CrossRefGoogle Scholar
  18. Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environ Plan B Plan Design 37(4):682–703CrossRefGoogle Scholar
  19. Jovicic DZ (2017) Current issues in tourism from the traditional understanding of tourism destination to the smart tourism destination, 3500CrossRefGoogle Scholar
  20. Karnwal T, Sivakumar T, Aghila G (2012) A comber approach to protect cloud computing against XML DDoS and HTTP DDoS attack. In: 2012 IEEE students’ conference on electrical, electronics and computer science, pp 1–5Google Scholar
  21. Li Y, Hu C, Huang C, Duan L (2017) The concept of smart tourism in the context of tourism information services. Tour Manag 58:293–300CrossRefGoogle Scholar
  22. Lim KH, Chan J, Leckie C, Karunasekera S (2018) Personalized trip recommendation for tourists based on user interests, points of interest visit durations and visit recency. Knowl Inf Syst 54(2):375–406CrossRefGoogle Scholar
  23. Longhi C, Titz J-B, Viallis L (2014) Open data: challenges and opportunities for the tourism industry. In: Tourism management, marketing, and development. Palgrave Macmillan, New York, pp 57–76Google Scholar
  24. Lopes P, Pereira F (2017) Proposal for a federation of hybrid clouds infrastructure in higher education institutions. In: Rocha Á, Correia AM, Adeli H, Reis LP, Costanzo S (eds) Advances in intelligent systems and computing, vol 570. Springer International Publishing, Cham, pp 197–206Google Scholar
  25. Luxen D, Vetter C (2011) Real-time routing with OpenStreetMap data. In: Proceedings of the 19th ACM SIGSPATIAL international conference on advances in geographic information systems. ACM, New York, pp 513–516Google Scholar
  26. Mooney P, Corcoran P (2014) Analysis of interaction and co-editing patterns amongst OpenStreetMap contributors. Trans GIS 18(5):633–659CrossRefGoogle Scholar
  27. Open Source Routing Machine (n.d.) Retrieved 14 March 2019
  28. Pereira RL, Sousa PC, Barata R, Oliveira A, Monsieur G (2015) CitySDK Tourism API—building value around open data. J Internet Serv Appl 6(1):1–13CrossRefGoogle Scholar
  29. Rajapaksha P, Farahbakhsh R, Nathanail E, Crespi N (2017) iTrip, a framework to enhance urban mobility by leveraging various data sources. Transp Res Procedia 24:113–122CrossRefGoogle Scholar
  30. Rebelo J, Caldas J, Guedes A (2015) The Douro Region: wine and Tourism. Almatourism J Tour Cult Territ Dev 6(11):75–90Google Scholar
  31. Ribeiro FR, Silva A, Barbosa F, Silva AP, Metrôlho JC (2018) Mobile applications for accessible tourism: overview, challenges and a proposed platform. Inf Technol Tour 19(1–4):29–59CrossRefGoogle Scholar
  32. Richards R (2006) Representational state transfer (REST). In: Pro PHP XML and web services, pp 633–672CrossRefGoogle Scholar
  33. Silva CA, Toasa R, Guevara J, Martinez HD, Vargas J (2018) Mobile application to encourage local tourism with context-aware computing. Springer, Cham, pp 796–803Google Scholar
  34. SQLAlchemy (n.d.) Retrieved 14 March 2019
  35. Thiengburanathum P, Cang S, Yu H (2016) Overview of personalized travel recommendation systems. In: 2016 22nd International conference on automation and computing, ICAC 2016: tackling the new challenges in automation and computing, pp 415–422Google Scholar
  36. Vansteenwegen P, Souffriau W, Vanden Berghe G, Van Oudheusden D (2009) Iterated local search for the team orienteering problem with time windows. Comput Oper Res 36(12):3281–3290CrossRefGoogle Scholar
  37. Vansteenwegen P, Souffriau W, Van den Berghe G, Van Oudheusden D (2011) The city trip planner: an expert system for tourists. Expert Syst Appl 38(6):6540–6546CrossRefGoogle Scholar
  38. Wang HD, Li L (2010) Research of process concealment based on technology of intercepting API calls. In: 2010 3rd International conference on computer science and information technology, vol 7, pp 412–414Google Scholar
  39. Wang M, Li Q, Hu Q, Zhou M (2013) Quality analysis of open street map data. In: 8th International symposium on spatial data quality, vol 40, pp 155–158CrossRefGoogle Scholar
  40. Yan C, Cheung A, Yang J, Lu S (2017) Understanding database performance inefficiencies in real-world web applications. In: Proceedings of the 2017 ACM on conference on information and knowledge management-CIKM’17, pp 1299–1308Google Scholar
  41. Yang J, Subramaniam P, Lu S, Yan C, Cheung A (2018) How not to structure your database-backed web applications: a study of performance bugs in the wild. In: ICSE, pp 1–11Google Scholar
  42. Zielstra D, Zipf A (2010) Quantitative studies on the data quality of OpenStreetMap in Germany. In: Proceedings of GIScienceGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Technology and Management of LamegoPolytechnic Institute of ViseuLamegoPortugal

Personalised recommendations