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.
Device Analyzer website: http://deviceanalyzer.cl.cam.ac.uk/.
- 2.
SL4A can be found at: http://code.google.com/p/android-scripting.
- 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.
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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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