QS Mapper: A Transparent Data Aggregator for the Quantified Self - Freedom from Particularity Using Two-way Mappings

Rasmus Rosenqvist Petersen, Adriana Lukas, Uffe Kock Wiil

2015

Abstract

Quantified Self is a growing community of individuals seeking self-improvement through self-measurement. Initially, personal variables such as diet, exercise, sleep, and productivity are tracked. This data is then explored for correlations, to ultimately either change negative or confirm positive behavioural patterns. Tools and applications that can handle these tasks exist, but they mostly focus on specific domains such as diet and exercise. These targeted tools implement a black box approach to data ingestion and computational analysis, thereby reducing the level of trust in the information reported. We present QS Mapper, a novel tool, that allows users to create two-way mappings between their tracked data and the data model. It is demonstrated how drag and drop data ingestion, interactive explorative analysis, and customisation of computational analysis procures more individual insights when testing Quantified Self hypotheses.

References

  1. Augemberg, K. (2012). Building that perfect quantified self app: Notes to developers, part 1. http://measuredme.com/2012/10/building-thatperfect-quantified-self-app. [Online; accessed March 27 2015].
  2. Choe, E. K., Lee, N. B., Lee, B., Pratt, W., and Kientz, J. A. (2014). Understanding quantified-selfers' practices in collecting and exploring personal data. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 7814, pages 1143-1152, New York, NY, USA. ACM.
  3. E. K. Choe, N. B. Lee, B. L. W. P. and Kientz, J. A. (2014). Understanding quantified-selfers' practices in collecting and exploring personal data. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1141-1152.
  4. Fluxtream (2015). Fluxtream web application. [last visited March 5th 2015].
  5. Google (2015). Getting started with google bigquery.
  6. Kleine, D. (2011). The capability approach and the 'medium of choice': steps towards conceptualising information and communication technologies for development. Ethics and Inf. Technol., 13(2):119-130.
  7. Krug, S. (2005). Don't Make Me Think: A Common Sense Approach to Web Usability, 2nd Edition. New Riders, Pearson Education.
  8. Labs, I. (2015). Data sense. last visited March 5th 2015.
  9. Lanier, J. (2014). Who owns the future? Penguin.
  10. Licklider, J. C. R. (1960). Man-computer symbiosis. IRE transactions on human factors in electronics, pages 4-11.
  11. Lukas, A. and midata et al. (2015). Proposal for selfhacking vm project to increase analytical capabilities for individual users. unpublished.
  12. Marshall, C. C. and Shipman, III, F. M. (1995). Spatial hypertext: Designing for change. Commun. ACM, 38(8):88-97.
  13. McGuffin, M. J. (2012). Simple algorithms for network visualization: A tutorial. TSINGHUA SCIENCE AND TECHNOLOGY, 17(4):1-16.
  14. Melnik, S., Gubarev, A., Long, J. J., Romer, G., Shivakumar, S., Tolton, M., and Vassilakis, T. (2010). Dremel: Interactive analysis of web-scale datasets. Proceedings of the VLDB Endowment, 3(1).
  15. Petersen, R. R. (2012). Criminal Network Investigation: Processes, Tools, and Techniques. University of Southern Denmark, Odense, Denmark.
  16. Petersen, R. R. and Wiil, U. K. (2009). Asap: A lightweight tool for agile planning. In Proceedings of the 4th International Conference on Software and Data Technologies (ICSOFT), pages 265-272.
  17. QS (2014). Quantified self europe. http://quantifiedself.com/conference/Amsterdam2014/. [Online; accessed 26-May-2014].
  18. Realidata (2015). rtracker. [Online; accessed March 27 2015].
  19. Sierra, K. (2015). Badass: Making Users Awesome. O'Reilly.
  20. Swan, M. (2013). The quantified self: fundamental disruption in big data science and biological discovery. Big Data, 1(2):85-99.
  21. Track and Apps, S. (2015). Tracknshare. http://www.trackandshareapps.com/. [Online; accessed March 27 2015].
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Paper Citation


in Harvard Style

Petersen R., Lukas A. and Wiil U. (2015). QS Mapper: A Transparent Data Aggregator for the Quantified Self - Freedom from Particularity Using Two-way Mappings . In Proceedings of the 10th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2015) ISBN 978-989-758-114-4, pages 65-72. DOI: 10.5220/0005553800650072


in Bibtex Style

@conference{icsoft-ea15,
author={Rasmus Rosenqvist Petersen and Adriana Lukas and Uffe Kock Wiil},
title={QS Mapper: A Transparent Data Aggregator for the Quantified Self - Freedom from Particularity Using Two-way Mappings},
booktitle={Proceedings of the 10th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2015)},
year={2015},
pages={65-72},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005553800650072},
isbn={978-989-758-114-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Software Engineering and Applications - Volume 1: ICSOFT-EA, (ICSOFT 2015)
TI - QS Mapper: A Transparent Data Aggregator for the Quantified Self - Freedom from Particularity Using Two-way Mappings
SN - 978-989-758-114-4
AU - Petersen R.
AU - Lukas A.
AU - Wiil U.
PY - 2015
SP - 65
EP - 72
DO - 10.5220/0005553800650072