Interdisciplinary approach to defining outdoor places of knowledge work: quantified photo analysis

Working outdoors is an emerging, sparsely studied phenomenon in knowledge work. Office tasks have traditionally been considered to belong to indoor environments. The worldwide pandemic of COVID-19 has increased and changed attitudes toward multilocational working. The aim of this method study is 2-fold: first to define for interdisciplinary context outdoor environments when they are used as places of outdoor knowledge work and second to quantify the thematic photo analysis to support interdisciplinary understanding of the places of outdoor knowledge work.

The review of literature has been one of the methods to support the interdisciplinary approach of this article. The photographs of outdoor knowledge workplaces and views from the workstations are studied through photo analysis customized from the existing press photograph analysis.

First, we defined outdoor environments when used as places of outdoor knowledge work, as unconditioned outdoor or semi-outdoor places (opposite to closed indoor spaces with stable, conditioned indoor climate) providing favorable action possibilities as sources of comfort and mitigating unfavorable conditions, for example, by microclimatic solutions. Instead of defining all spaces as outdoor environments not fulfilling a stable indoor climate (conditioned) definition, adaptation to thermal and physical environments also brought semi-outdoor space into the definition. In this context, favorable latent action possibilities (affordance) in the built environment are often related to microclimate as a source of comfort. Second, we focussed on photo analysis. The proposed model is based on journalistic photo analysis PPSA and the pOKW model, which have been further developed in this study to pOKW2 model for analyzing mobile-based collected self-reported photographs by the occupants. In this pOKW2 model, the photographs would have time-location information enabling the combining of data from other datasets and thereby reducing the number of characteristics to be analyzed from the photograph. We proposed rating (in numeric form) to detect the favorable and unfavorable characteristics in the photographs most likely supporting or hindering conditions of outdoor knowledge work. This quantification would enable the use of machine vision analysis and would support handling large quantities of photographs and their combination with other datasets in interdisciplinary research.

The quantification of the photo analysis (pOKW2) includes the readiness to combine the analysis results with other time-location-specific datasets in an interdisciplinary research collaboration to advance our understanding of latent action possibilities for outdoor knowledge work.