A semantic framework for persistence of moisture-related experimental data

A semantic framework for persistence of moisture-related experimental data

Both within UCL IEDE and the wider research community there is an increasing appreciation that controlling and understanding the impact of moisture on Indoor Environmental Quality and Health and establishing rigorous links between contributing factors is challenging but also profoundly important both from a scientific as well as a societal impact perspective.

To bridge knowledge gaps, many ongoing studies rely on data collection from building sites (e.g. by installation of temperature and humidity sensors or connection to already existing Building Management Systems), use of thermal imaging or surface measurement techniques (e.g. for mould), and contextual data that include building geometry, construction characteristics and prevailing external conditions. Some of the latter information might be available from external (web-)services. No clear measurement protocol exists, and for each study, depending upon its specific aims, data are collected in ad hoc formats; often, important contextual data are not captured undermining the value and re-usability of data sets.

The aim of the work is the development of a persistence and data integration framework for storage of experimental data collected in the context of the UKCMB activities. The outputs of the project are expected to contribute to the development of an information repository for storage of data obtained from industry- and research activities of the UKCMB.


Abel Maciel
Bartlett School of Architecture

Dimitrios Rovas
UCL Institute for Env. Design & Engineering (IEDE)