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International Workshop on Mining Ubiquitous and Social Environments

International Workshop on Modeling Social Media

MUSE 2013, MSM 2013: Mining, Modeling, and Recommending 'Things' in Social Media pp 116–130Cite as

Open Smartphone Data for Structured Mobility and Utilization Analysis in Ubiquitous Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8940))

Abstract

The development and evaluation of new data mining methods for ubiquitous environments and systems requires real data that were collected from real users. In this work, we present an open smartphone utilization and mobility data set that was generated with several devices and participants during a 4-month study. A particularity of this data set is the inclusion of low-level operating system data. Additionally to the description of the data, we also describe the process of collection and the privacy measures we applied. To demonstrate the utility of the data, we evaluate the quality of generative spatio-temporal models for “apps” and network cells, since these are required as a building block in general predictions of the resource consumption of ubiquitous systems.

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Notes

  1. 1.

    Device Analyzer website: http://deviceanalyzer.cl.cam.ac.uk/.

  2. 2.

    SL4A can be found at: http://code.google.com/p/android-scripting.

  3. 3.

    The stream container and processors that have been written to preprocess the data for both tasks are available online at: http://sfb876.tu-dortmund.de/mobidata.

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Acknowledgments

This work has been supported by Deutsche Forschungsgemeinschaft (DFG) within the Collaborative Research Center SFB 876 “Providing Information by Resource-Constrained Data Analysis”, project A1. We would also like to thank our collaboration partners from the EcoSense project at Aarhus University for providing technical support. Last but not least, we would like to thank all our participants for contributing to the data set.

Author information

Authors and Affiliations

  1. Department of Computer Science, LS8, TU Dortmund University, 44227, Dortmund, Germany

    Nico Piatkowski & Katharina Morik

  2. Department of Computer Science, LS12, TU Dortmund University, 44227, Dortmund, Germany

    Jochen Streicher & Olaf Spinczyk

Authors
  1. Nico Piatkowski
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  2. Jochen Streicher
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  3. Olaf Spinczyk
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  4. Katharina Morik
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Corresponding author

Correspondence to Nico Piatkowski .

Editor information

Editors and Affiliations

  1. University of Kassel, Kassel, Germany

    Martin Atzmueller

  2. Microsoft, Beijing, China

    Alvin Chin

  3. University of Kassel, Kassel, Germany

    Christoph Scholz

  4. Norwegian University of Science and Technology, Trondheim, Norway

    Christoph Trattner

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Piatkowski, N., Streicher, J., Spinczyk, O., Morik, K. (2015). Open Smartphone Data for Structured Mobility and Utilization Analysis in Ubiquitous Systems. In: Atzmueller, M., Chin, A., Scholz, C., Trattner, C. (eds) Mining, Modeling, and Recommending 'Things' in Social Media. MUSE MSM 2013 2013. Lecture Notes in Computer Science(), vol 8940. Springer, Cham. https://doi.org/10.1007/978-3-319-14723-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-14723-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14722-2

  • Online ISBN: 978-3-319-14723-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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