On the Ontological Quality and Logical Quality of Conceptual-Modeling Grammars: The Need for a Dual Perspective

A core activity in information systems development involves building a conceptual model of the domain that an information system is intended to support. Such models are created using a conceptual-modeling (CM) grammar. Just as high-quality conceptual models facilitate high-quality systems development, high-quality CM grammars facilitate high-quality conceptual modeling. This paper provides a new perspective on ways to improve the quality of the semantics of CM grammars. For many years, the leading approach to this topic has relied on ontological theory. We show, however, that the ontological approach captures only half the story. It needs to be coupled with a logical approach. We explain how the ontological quality and logical quality of CM grammars interrelate. Furthermore, we outline three contributions that a logical approach can make to evaluating the quality of CM grammars: a means of seeing some familiar conceptual-modeling problems in simpler ways; the illumination of new problems; and the ability to prove the benefit of modifying existing CM grammars in particular ways. We demonstrate these benefits in the context of the Entity-Relationship grammar. More generally, our paper opens up a new area of research with many opportunities for future research and practice.

Case study investigation of indoor air quality in mechanically ventilated and naturally ventilated UK social housing

There is a significant lack of indoor air quality research in low energy homes. This study compared the indoor air quality of eight
newly built case study homes constructed to similar levels of air-tightness and insulation; with two different ventilation strategies (four homes with Mechanical Ventilation with Heat Recovery (MVHR) systems/Code level 4 and four homes naturally ventilated/Code level 3). Indoor air quality measurements were conducted over a 24 h period in the living room and main bedroom of each home during the summer and winter seasons. Simultaneous outside measurements and an occupant diary were also employed during the measurement period. Occupant interviews were conducted to gain information on perceived indoor air quality, occupant behaviour and building related illnesses. Knowledge of the MVHR system including ventilation related behaviour was also studied. Results suggest indoor air quality problems in both the mechanically ventilated and naturally ventilated homes, with significant issues identified regarding occupant use in the social homes

Mismatches and matches in address information from the Census and the BSO: A longitudinal perspective 2001-2011

Accurate address information from health service providers is fundamental for the effective delivery of health care and population monitoring and screening. While it is currently used in the production of key statistics such as internal migration estimates, it will become even more important over time with the 2021 Census of UK constituent countries integrating administrative data to enhance the quality of statistical outputs. Therefore, it is beneficial to improve understanding of the accuracy of address information held by health service providers and factors that influence this. This paper builds upon previous research on the social geography of address mismatch between census and health service records in Northern Ireland. It is based on the Northern Ireland Longitudinal Study; this is a large data linkage study including about 28 per cent of the Northern Ireland population, which is matched between the census (2001, 2011) and Health Card Registration System maintained by the Health and Social Care Business Service Organisation (BSO). This research compares address information from the Spring 2011 BSO download (Unique Property Reference Number, Super Output Area) with comparable geographic information from the 2011 Census. Multivariate and multilevel analyses are used to assess the individual and ecological determinants of match/mismatch between geographical information in both data sources to determine if the characteristics of the associated people and places are the same as the position observed in 2001. It is important to understand if the same people are being inaccurately geographically referenced in both Census years or if the situation is more variable.