skip to main content
10.1145/2938503.2938550acmotherconferencesArticle/Chapter ViewAbstractPublication PagesideasConference Proceedingsconference-collections
research-article

Enriching Mobility Data with Linked Open Data

Authors Info & Claims
Published:11 July 2016Publication History

ABSTRACT

Recent research has pointed out the needs and advantages of the semantic enrichment of movement data, a process where trajectories are partitioned into homogeneous segments that are annotated with contextual information. However, the lack of a comprehensive and well-defined framework for the enrichment makes this process difficult and error-prone. In this paper, we therefore propose a conceptual framework for the semantic enrichment of movement data, which benefits from the emerging Web of Data (or Linked Open Data) both as a unifying formalism and as the source of contextual data, which can be greatly useful for trajectories enrichment. Moreover, the semantic structure of such sources makes it easier to share and process enriched trajectories. We illustrate the enrichment process by presenting a case study in the tourism domain.

References

  1. W3C OWL Working group, 2012. OWL 2 web ontology language. document overview (second edition). W3C recommendation 11 december 2012. available at https://www.w3.org/tr/owl2-overview/.Google ScholarGoogle Scholar
  2. Ana Alves, Bruno Antunes, Francisco C Pereira, and Carlos Bento. Semantic enrichment of places: Ontology learning from web. International Journal of Knowledge-based and Intelligent Engineering Systems, 13(1):19--30, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. Dbpedia: A nucleus for a web of open data. Springer, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  4. Clara Bacciu, Angelica Lo Duca, Andrea Marchetti, and Maurizio Tesconi. Accommodations in Tuscany as Linked Data. In LREC, pages 3542--3545, 2014.Google ScholarGoogle Scholar
  5. C. Bizer, T. Heath, and T. Berners-Lee. Linked data - the story so far. Int. J. Semantic Web Inf. Syst., 5(3):1--22, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  6. Vania Bogorny, Chiara Renso, Artur Ribeiro Aquino, Fernando Lucca Siqueira, and Luis Otavio Alvares. Constant--a conceptual data model for semantic trajectories of moving objects. Transactions in GIS, 18(1):66--88, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  7. Marco A Casanova, Vânia MP Vidal, Giseli Rabello Lopes, Luiz André P Paes Leme, and Livia Ruback. On materialized sameas linksets. In Database and Expert Systems Applications, pages 377--384. Springer, 2014.Google ScholarGoogle Scholar
  8. Marcirio Silveira Chaves, Larissa A. Freitas, and Renata Vieira. Hontology: a multilingual ontology for the accommodation sector in the tourism industry. In Proceedings of the 4th International Conference on Knowledge Engineering and Ontology Development, 2012.Google ScholarGoogle Scholar
  9. Dejing Dou, Hao Wang, and Haishan Liu. Semantic data mining: A survey of ontology-based approaches. In Mohan S. Kankanhalli, Tao Li, and Wei Wang, editors, ICSC, pages 244--251. IEEE Computer Society, 2015.Google ScholarGoogle Scholar
  10. Brigitte Endres-Niggemeyer. Semantic Mashups: Intelligent Reuse of Web Resources. Springer Publishing Company, Incorporated, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Renato Fileto, Marcelo Krüger, Nikos Pelekis, Yannis Theodoridis, and Chiara Renso. Baquara: A holistic ontological framework for movement analysis using linked data. In Conceptual Modeling, pages 342--355. Springer, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Renato Fileto, Alessandra Raffaetà, Alessandro Roncato, Juarez AP Sacenti, Cleto May, and Douglas Klein. A semantic model for movement data warehouses. In Proceedings of the 17th International Workshop on Data Warehousing and OLAP, pages 47--56. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Tom Heath and Christian Bizer. Linked data: Evolving the web into a global data space. Synthesis lectures on the semantic web: theory and technology, 1(1):1--136, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Yingjie Hu, Krzysztof Janowicz, David Carral, Simon Scheider, Werner Kuhn, Gary Berg-Cross, Pascal Hitzler, Mike Dean, and Dave Kolas. Spatial Information Theory: 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings, chapter A Geo-ontology Design Pattern for Semantic Trajectories, pages 438--456. Springer International Publishing, Cham, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Axel-Cyrille Ngonga Ngomo and Sören Auer. LIMES - A Time-Efficient Approach for Large-Scale Link Discovery on the Web of Data. integration, 15:3, 2011.Google ScholarGoogle Scholar
  16. Christine Parent, Stefano Spaccapietra, Chiara Renso, Gennady Andrienko, Natalia Andrienko, Vania Bogorny, Maria Luisa Damiani, Aris Gkoulalas-Divanis, Jose Antonio de Macedo, Nikos Pelekis, et al. Semantic trajectories modeling and analysis. ACM Computing Surveys (CSUR), 45(4):42, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Nikos Pelekis and Yannis Theodoridis. Semantic aspects on mobility data. In Mobility Data Management and Exploration, pages 189--209. Springer, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  18. Chiara Renso, Miriam Baglioni, Jose Antonio de Macedo, Roberto Trasarti, and Monica Wachowicz. How you move reveals who you are: understanding human behavior by analyzing trajectory data. Knowledge and information systems, 37(2):331--362, 2013.Google ScholarGoogle Scholar
  19. Jose Antonio M. R. Rocha, Valéria Cesário Times, Gabriel Oliveira, Luis Otávio Alvares, and Vania Bogorny. Db-smot: A direction-based spatio-temporal clustering method. In IEEE Conf. of Intelligent Systems, pages 114--119. IEEE, 2010.Google ScholarGoogle ScholarCross RefCross Ref
  20. Stefano Spaccapietra, Christine Parent, Maria Luisa Damiani, Jose Antonio de Macedo, Fabio Porto, and Christelle Vangenot. A conceptual view on trajectories. Data & knowledge engineering, 65(1):126--146, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Vânia MP Vidal, Marco A Casanova, Narciso Arruda, Mariano Roberval, Luiz Paes Leme, Giseli Rabello Lopes, and Chiara Renso. Specification and incremental maintenance of linked data mashup views. In Advanced Information Systems Engineering, pages 214--229. Springer, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  22. Julius Volz, Christian Bizer, Martin Gaedke, and Georgi Kobilarov. Silk-a link discovery framework for the web of data. LDOW, 538, 2009.Google ScholarGoogle Scholar
  23. Wei Wang, Guosun Zeng, and Daizhong Tang. Bayesian intelligent semantic mashup for tourism. Concurrency and Computation: Practice and Experience, 23(8):850--862, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Zhixian Yan, Jose Antonio de Macedo, Christine Parent, and Stefano Spaccapietra. Trajectory ontologies and queries. Transactions in GIS, 12(s1):75--91, 2008.Google ScholarGoogle Scholar
  25. Ji Yuan, Xudong Liu, Richong Zhang, Hailong Sun, Xiaohui Guo, and Yanghao Wang. Discovering semantic mobility pattern from check-in data. In Web Information Systems Engineering--WISE 2014, pages 464--479. Springer, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  26. Vincent W. Zheng, Yu Zheng, Xing Xie, and Qiang Yang. Collaborative location and activity recommendations with gps history data. In Proceedings of the 19th International Conference on World Wide Web, WWW '10, pages 1029--1038, New York, NY, USA, 2010. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Yu Zheng, Yukun Chen, Quannan Li, Xing Xie, and Wei-Ying Ma. Understanding transportation modes based on gps data for web applications. ACM Trans. Web, 4(1):1:1--1:36, January 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Enriching Mobility Data with Linked Open Data

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          IDEAS '16: Proceedings of the 20th International Database Engineering & Applications Symposium
          July 2016
          420 pages
          ISBN:9781450341189
          DOI:10.1145/2938503

          Copyright © 2016 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 11 July 2016

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

          Acceptance Rates

          Overall Acceptance Rate74of210submissions,35%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader