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

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.

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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