Correlating indoor and outdoor temperature and humidity in a sample of buildings in tropical climates

The incidence of several respiratory viral infections has been shown to be related to climate. Because humans spend most of their time indoors, measures of indoor climate, rather than outdoor climate, may be better predictors of disease incidence and transmission. Therefore, understanding the relationship between indoor and outdoor climate will help illuminate their influence on the seasonality of diseases caused by respiratory viruses. Indoor-outdoor relationships between temperature and humidity have been documented in temperate regions, but little information is available for tropical regions, where seasonal patterns of respiratory viral diseases differ. We have examined indoor-outdoor correlations of temperature, relative humidity (RH), and absolute humidity (AH) over a 1-year period in each of seven tropical cities. Across all cities, the average monthly indoor temperature was 25 ± 3°C (mean ± standard deviation) with a range of 20–30°C. The average monthly indoor RH was 66 ± 9% with a range of 50–78%, and the average monthly indoor AH was 15 ± 3 g/m³ with a range of 10–23 g/m³. Indoor AH and RH were linearly correlated with outdoor AH when the air conditioning (AC) was off, suggesting that outdoor AH may be a good proxy of indoor humidity in the absence of AC. All indoor measurements were more strongly correlated with outdoor measurements as distance from the equator increased. Such correlations were weaker during the wet season, especially when AC was in operation. These correlations will provide insight for assessing the seasonality of respiratory viral infections using outdoor climate data, which is more widely available than indoor data, even though transmission of these diseases mainly occurs indoors.     

Evaluation of the OQuaRE framework for ontology quality

The increasing importance of ontologies has resulted in the development of a large number of ontologies in both coordinated and non-coordinated efforts. The number and complexity of such ontologies make hard to ontology and tool developers to select which ontologies to use and reuse. So far, there are no mechanism for making such decisions in an informed manner. Consequently, methods for evaluating ontology quality are required. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies. OQuaRE has been applied to identify the strengths and weaknesses of different ontologies but, so far, this framework has not been evaluated itself. Therefore, in this paper we present the evaluation of OQuaRE, performed by an international panel of experts in ontology engineering. The results include the positive and negative aspects of the current version of OQuaRE, the completeness and utility of the quality metrics included in OQuaRE and the comparison between the results of the manual evaluations done by the experts and the ones obtained by a software implementation of OQuaRE.