Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/1626536.1626539acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
research-article

Building real-world trajectory warehouses

Published: 13 June 2008 Publication History

Abstract

The flow of data generated from low-cost modern sensing technologies and wireless telecommunication devices enables novel research fields related to the management of this new kind of data and the implementation of appropriate analytics for knowledge extraction. In this work, we investigate how the traditional data cube model is adapted to trajectory warehouses in order to transform raw location data into valuable information. In particular, we focus our research on three issues that are critical to trajectory data warehousing: (a) the trajectory reconstruction procedure that takes place when loading a moving object database with sampled location data originated e.g. from GPS recordings, (b) the ETL procedure that feeds a trajectory data warehouse, and (c) the aggregation of cube measures for OLAP purposes. We provide design solutions for all these issues and we test their applicability and efficiency in real world settings.

References

[1]
Agarwal, S., Agrawal, R., Deshpande, P., Gupta, A., Naughton, J., Ramakrishnan, R., and Sarawagi. S. On the computation of multidimensional aggregates. Proc. VLDB, 1996.
[2]
Choi, W., Kwon, D., and Lee, S. Spatio-temporal data warehouses using an adaptive cell-based approach. DKE, 59(1):189--207, 2006.
[3]
eCourier.co.uk dataset, http://api.ecourier.co.uk/. (URL valid on May 14, 2008).
[4]
Giannotti, F., Nanni, M., Pinelli, F., and Pedreschi, D. Trajectory pattern mining. Proc. KDD, 2007.
[5]
Gray, J., Chaudhuri, S., Bosworth, A., Layman, A., Reichart, D., Venkatrao, M., Pellow, F., and Pirahesh, H. Data cube: A relational aggregation operator generalizing groub-by, crosstab and sub-totals. DMKD, 1(1):29--54, 1997.
[6]
Güting, R. H., and Schneider, M. Moving Object Databases, Morgan Kaufman Publishers. 2005.
[7]
Han, J., Stefanovic, N., and Koperski, K. Selective Materialization: An Efficient Method for Spatial Data Cube Construction. Proc. PAKDD, 1998.
[8]
Jensen, C. S., Kligys, A., Pedersen, T. B., Dyreson, C. E., and Timko, I. Multidimensional data modeling for location-based services, The VLDB Journal, 13:1--21, 2004.
[9]
Lee, J., Han, J., and Whang, K. Trajectory Clustering: A Partition-and-Group Framework. Proc. SIGMOD, 2007.
[10]
Orlando, S., Orsini, R., Raffaetà, A., Roncato, A., and Silvestri, C. Spatio-Temporal Aggregations in Trajectory Data Warehouses. Proc. DaWaK, 2007.
[11]
Orlando, S., Orsini, R., Raffaetà, A., Roncato, A., and Silvestri, C. Trajectory Data Warehouses: Design and Implementation Issues. JCSE, 1(2):240--261, 2007.
[12]
Papadias, D., Kalnis, P., Zhang, J., and Tao, Y. Efficient OLAP Operations in Spatial Data Warehouses. Proc. SSTD, 2001.
[13]
Pelekis, N., Raffaetà, A., Damiani, M.-L., Vangenot, C., Marketos, G., Frentzos, E., Ntoutsi, I., and Theodoridis, Y. Towards Trajectory Data Warehouses. Chapter in Mobility, Data Mining and Privacy: Geographic Knowledge Discovery. Springer-Verlag. 2008.
[14]
Pelekis, N., Theodoridis, Y., Vosinakis, S. and Panayiotopoulos, T. Hermes - A Framework for Location-Based Data Management. Proc. EDBT, 2006.
[15]
Pfoser, D., Jensen, C. S., and Theodoridis, Y. Novel Approaches to the Indexing of Moving Object Trajectories, Proc. VLDB, 2000.
[16]
Tao, T., and Papadias, D. Historical Spatio-Temporal Aggregation. ACM TODS, 23(1):61--102, 2005.
[17]
Tao, Y., Kollios, G., Considine, J., Li, F., and Papadias, D. Spatio-Temporal Aggregation Using Sketches. Proc. ICDE, 2004.
[18]
Vitter, J. S., Wang, M., and Iyer, B. Data Cube Approximation and Histograms via Wavelets. Proc. CIKM, 1998.

Cited By

View all
  • (2022)Addressing robust travel mode identification with individual trip‐chain trajectory noise reductionIET Intelligent Transport Systems10.1049/itr2.1224317:1(129-143)Online publication date: 24-Jul-2022
  • (2021)Moving Beyond Traditional Decision Support SystemsResearch Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering10.4018/978-1-7998-9023-2.ch068(1431-1445)Online publication date: 2021
  • (2021)Field-road trajectory segmentation for agricultural machinery based on direction distributionComputers and Electronics in Agriculture10.1016/j.compag.2021.106180186(106180)Online publication date: Jul-2021
  • Show More Cited By

Index Terms

  1. Building real-world trajectory warehouses

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    MobiDE '08: Proceedings of the Seventh ACM International Workshop on Data Engineering for Wireless and Mobile Access
    June 2008
    77 pages
    ISBN:9781605582214
    DOI:10.1145/1626536
    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]

    Sponsors

    In-Cooperation

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 13 June 2008

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. distinct count problem
    2. moving object databases
    3. trajectory data warehouses
    4. trajectory reconstruction

    Qualifiers

    • Research-article

    Funding Sources

    Conference

    MobiDE '08
    Sponsor:

    Acceptance Rates

    Overall Acceptance Rate 23 of 59 submissions, 39%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)12
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 17 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2022)Addressing robust travel mode identification with individual trip‐chain trajectory noise reductionIET Intelligent Transport Systems10.1049/itr2.1224317:1(129-143)Online publication date: 24-Jul-2022
    • (2021)Moving Beyond Traditional Decision Support SystemsResearch Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering10.4018/978-1-7998-9023-2.ch068(1431-1445)Online publication date: 2021
    • (2021)Field-road trajectory segmentation for agricultural machinery based on direction distributionComputers and Electronics in Agriculture10.1016/j.compag.2021.106180186(106180)Online publication date: Jul-2021
    • (2021)A Data Warehouse of Wi-Fi Sessions for Contact Tracing and Outbreak InvestigationTransactions on Large-Scale Data- and Knowledge-Centered Systems XLVIII10.1007/978-3-662-63519-3_4(85-104)Online publication date: 18-May-2021
    • (2020)A Survey on Big Data for Trajectory AnalyticsISPRS International Journal of Geo-Information10.3390/ijgi90200889:2(88)Online publication date: 1-Feb-2020
    • (2019)Mobility Data WarehousesISPRS International Journal of Geo-Information10.3390/ijgi80401708:4(170)Online publication date: 2-Apr-2019
    • (2018)TRIPSProceedings of the VLDB Endowment10.14778/3229863.323622411:12(1918-1921)Online publication date: 1-Aug-2018
    • (2018)Spatio-temporal analysis of trajectories for safer construction sitesSmart and Sustainable Built Environment10.1108/SASBE-10-2017-00477:1(80-100)Online publication date: 3-Apr-2018
    • (2018)Differentially private counting of users' spatial regionsKnowledge and Information Systems10.1007/s10115-017-1113-654:1(5-32)Online publication date: 1-Jan-2018
    • (2017)Moving Beyond Traditional Decision Support SystemsInternational Journal of Information Systems and Social Change10.4018/IJISSC.20170401048:2(74-87)Online publication date: 1-Apr-2017
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media