Improving Trustworthiness of Human Sensing Data via Open Data
Mikkel Baun Kjærgaard, Fisayo Caleb Sangogboye, Anooshmita Das, Jens Hjort Schwee · 2018
A key piece of information when maintaining and developing the built environment is quantified information about human behavior to understand usage. The digitalisation of our society including mobile, wearable and Internet of Things devices and the availability of low-cost sensors opens up new possibilities for mapping human behavior and its context via objective sensor data. However, to gain the full potential of using resources on mapping human behavior requires that data is not collected for single usage. The open data paradigm prescribes a method for going beyond one-time data collection. In this vision abstract, we argue that the open data paradigm also supports increasing the trustworthiness of sensing data about human behavior by providing multiple and multi-modal sources of data that complements each other. This is important to enable trustworthy data-driven decision making on data that is not artificially limited by sensing coverage and accuracy or tampered with. We argue that sharing open data can help avoid these issues by providing more data sources and thereby increase trustworthiness.