Collection of real-life stories on occupant-building interaction

This dataset was collected as part of an industrial PhD project between Saint-Gobain Nordic A/S and the Technical University of Denmark conducted by Lucile Sarran, under the supervision of Carsten Rode, Christian Hviid, Jakub Kolarik and Elisabeth Wærsted.<br>This work was carried out in the context of the International Energy Agency's EBC Annex 79: Occupant-Centric Building Design and Operation: https://annex79.iea-ebc.org/. It is the result of the cross-subtask activity C.7 co-led by Lucile Sarran (DTU, [e-mail]) and Connor Brackley (Concordia University, [e-mail]). Please contact Connor Brackley for more information or improvement suggestions.<br>Please cite as: Sarran, Lucile; Brackley, Connor (2021): Collection of real-life stories on occupant-building interaction. Dataset. https://doi.org/10.11583/DTU.14706066. This work is licensed under CC-BY version 4.0.<br>This activity focused on identifying human-related drivers of occupant dissatisfaction in buildings, by asking researchers around the world to describe unexpected occupant behaviors observed in their research projects. Therefore a series of prompts was developed with the aim to stimulate storytelling among researchers. A board containing these prompts was created on Miro, an online platform based on sticky notes. In a first phase, the link to the board was distributed to Annex 79 participants:18 stories were collected and included in a pilot study.<br>The prompts were:· “My story takes place in...”: building-related information (type, number of buildings, location) · “The technology or building system...”: e.g., ventilation, smart thermostats, new controls · “Was this an existing system or did you implement it?” · “The goal with the technology/building system was to...” original aim of the technology · “In real conditions, what happened was...”- the unexpected human-building interaction · “Because...” – researcher’s interpretation of the events · “What is this interpretation based on?...” - e.g. sensor data, observations, personal experience · “What we can learn from this story, and what should be done...” - lessons learned and best practice suggestions.<br>Two documents have been uploaded: (1) a high-resolution picture (in PDF format) of the data collection tool, together with the 18 research stories included in the pilot study; (2) a CSV file containing the data from the 18 stories.<br><br>An article presenting the methodology and the results of this story collection was submitted to the IAQ 2020 conference, postponed to 2022.<br>