Making visible the coding process : Using qualitative data software in a post-structural study

Qualitative research methods require transparency to ensure the ‘trustworthiness’ of the data analysis. The intricate processes of organizing, coding and analyzing the data are often rendered invisible in the presentation of the research findings, which requires a ‘leap of faith’ for the reader. Computer assisted data analysis software can be used to make the research process more transparent, without sacrificing rich, interpretive analysis by the researcher. This article describes in detail how one software package was used in a poststructural study to link and code multiple forms of data to four research questions for fine-grained analysis. This description will be useful for researchers seeking to use qualitative data analysis software as an analytic tool.

Building Information Modelling for FM at Sydney Opera House

“SOH see significant benefit in digitising its drawings and operation and maintenance manuals. Since SOH do not currently have digital models of the Opera House structure or other components, there is an opportunity for this national case study to promote the application of Digital Facility Modelling using standardized Building Information Models (BIM)”. The digital modelling element of this project examined the potential of building information models for Facility Management focusing on the following areas: • The re-usability of building information for FM purposes • BIM as an Integrated information model for facility management • Extendibility of the BIM to cope with business specific requirements • Commercial facility management software using standardised building information models • The ability to add (organisation specific) intelligence to the model • A roadmap for SOH to adopt BIM for FM The project has established that BIM – building information modelling - is an appropriate and potentially beneficial technology for the storage of integrated building, maintenance and management data for SOH. Based on the attributes of a BIM, several advantages can be envisioned: consistency in the data, intelligence in the model, multiple representations, source of information for intelligent programs and intelligent queries. The IFC – open building exchange standard – specification provides comprehensive support for asset and facility management functions, and offers new management, collaboration and procurement relationships based on sharing of intelligent building data. The major advantages of using an open standard are: information can be read and manipulated by any compliant software, reduced user “lock in” to proprietary solutions, third party software can be the “best of breed” to suit the process and scope at hand, standardised BIM solutions consider the wider implications of information exchange outside the scope of any particular vendor, information can be archived as ASCII files for archival purposes, and data quality can be enhanced as the now single source of users’ information has improved accuracy, correctness, currency, completeness and relevance. SOH current building standards have been successfully drafted for a BIM environment and are confidently expected to be fully developed when BIM is adopted operationally by SOH. There have been remarkably few technical difficulties in converting the House’s existing conventions and standards to the new model based environment. This demonstrates that the IFC model represents world practice for building data representation and management (see Sydney Opera House – FM Exemplar Project Report Number 2005-001-C-3, Open Specification for BIM: Sydney Opera House Case Study). Availability of FM applications based on BIM is in its infancy but focussed systems are already in operation internationally and show excellent prospects for implementation systems at SOH. In addition to the generic benefits of standardised BIM described above, the following FM specific advantages can be expected from this new integrated facilities management environment: faster and more effective processes, controlled whole life costs and environmental data, better customer service, common operational picture for current and strategic planning, visual decision-making and a total ownership cost model. Tests with partial BIM data – provided by several of SOH’s current consultants – show that the creation of a SOH complete model is realistic, but subject to resolution of compliance and detailed functional support by participating software applications. The showcase has demonstrated successfully that IFC based exchange is possible with several common BIM based applications through the creation of a new partial model of the building. Data exchanged has been geometrically accurate (the SOH building structure represents some of the most complex building elements) and supports rich information describing the types of objects, with their properties and relationships.

Public acceptance of carbon dioxide capture and storage in a proposed demonstration area

With the rising levels of CO2 in the atmosphere, low-emission technologies with carbon dioxide capture and storage (CCS) provide one option for transforming the global energy infrastructure into a more environmentally, climate sustainable system. However, like many technology innovations, there is a social risk to the acceptance of CCS. This article presents the findings of an engagement process using facilitated workshops conducted in two communities in rural Queensland, Australia, where a demonstration project for IGCC with CCS has been announced. The findings demonstrate that workshop participants were concerned about climate change and wanted leadership from government and industry to address the issue. After the workshops, participants reported increased knowledge and more positive attitudes towards CCS, expressing support for the demonstration project to continue in their local area. The process developed is one that could be utilized around the world to successfully engage communities on the low carbon emission technology options.

Sustainable subdivisions – ventilation data analysis

This project, as part of a broader Sustainable Sub-divisions research agenda, addresses the role of natural ventilation in reducing the use of energy required to cool dwellings

Looking through the haze of discontent : smokers as a data source

In the case of industrial relations research, particularly that which sets out to examine practices within workplaces, the best way to study this real-life context is to work for the organisation. Studies conducted by researchers working within the organisation comprise some of the (broad) field’s classic research (cf. Roy, 1954; Burawoy, 1979). Participant and non-participant ethnographic research provides an opportunity to investigate workplace behaviour beyond the scope of questionnaires and interviews. However, we suggest that the data collected outside a workplace can be just as important as the data collected inside the organisation’s walls. In recent years the introduction of anti-smoking legislation in Australia has meant that people who smoke cigarettes are no longer allowed to do so inside buildings. Not only are smokers forced outside to engage in their habit, but they have to smoke prescribed distances from doorways, or in some workplaces outside the property line. This chapter considers the importance of cigarette-smoking employees in ethnographic research. Through data collected across three separate research projects, the chapter argues that smokers, as social outcasts in the workplace, can provide a wealth of important research data. We suggest that smokers also appear more likely to provide stories that contradict the ‘management’ or ‘organisational’ position. Thus, within the haze of smoke, researchers can uncover a level of discontent with the ‘corporate line’ presented inside the workplace. There are several aspects to the increased propensity of smokers to provide a contradictory or discontented story. It may be that the researcher is better able to establish a rapport with smokers, as there is a removal of the artificial wall a researcher presents as an outsider. It may also be that a research location physically outside the boundaries of the organisation provides workers with the freedom to express their discontent. The authors offer no definitive answers; rather, this chapter is intended to extend our knowledge of workplace research through highlighting the methodological value in using smokers as research subjects. We present the experience of three separate case studies where interactions with cigarette smokers have provided either important organisational data or alternatively a means of entering what Cunnison (1966) referred to as the ‘gossip circle’. The final section of the chapter draws on the evidence to demonstrate how the community of smokers, as social outcasts, are valuable in investigating workplace issues. For researchers and practitioners, these social outcasts may very well prove to be an important barometer of employee attitudes; attitudes that perhaps cannot be measured through traditional staff surveys.

Preliminary report on data mining techniques for life prediction

This project is an extension of a previous CRC project (220-059-B) which developed a program for life prediction of gutters in Queensland schools. A number of sources of information on service life of metallic building components were formed into databases linked to a Case-Based Reasoning Engine which extracted relevant cases from each source. In the initial software, no attempt was made to choose between the results offered or construct a case for retention in the casebase. In this phase of the project, alternative data mining techniques will be explored and evaluated. A process for selecting a unique service life prediction for each query will also be investigated. This report summarises the initial evaluation of several data mining techniques.

Report : school survey to collect data on material performance

A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.

Report : wireless data throughput testing on a mobile device using WiFi and GPRS

This project report presents the results of a study on wireless communication data transfer rates for a mobile device running a custombuilt construction defect reporting application. The study measured the time taken to transmit data about a construction defect, which included digital imagery and text, in order to assess the feasibility of transferring various types and sizes of data and the ICT-supported construction management applications that could be developed as a consequence. Data transfer rates over GPRS through the Telstra network and WiFi over a private network were compared. Based on the data size and data transfer time, the rate of transfer was calculated to determine the actual data transmission speeds at which the information was being sent using the wireless mobile communication protocols. The report finds that the transmission speeds vary considerably when using GPRS and can be significantly slower than what is advertised by mobile network providers. While WiFi is much faster than GPRS, the limited range of WiFi limits the protocol to residential-scale construction sites.

Report : stochastic analysis of road asset data for maintenance cost prediction

Reliable budget/cost estimates for road maintenance and rehabilitation are subjected to uncertainties and variability in road asset condition and characteristics of road users. The CRC CI research project 2003-029-C ‘Maintenance Cost Prediction for Road’ developed a method for assessing variation and reliability in budget/cost estimates for road maintenance and rehabilitation. The method is based on probability-based reliable theory and statistical method. The next stage of the current project is to apply the developed method to predict maintenance/rehabilitation budgets/costs of large networks for strategic investment. The first task is to assess the variability of road data. This report presents initial results of the analysis in assessing the variability of road data. A case study of the analysis for dry non reactive soil is presented to demonstrate the concept in analysing the variability of road data for large road networks. In assessing the variability of road data, large road networks were categorised into categories with common characteristics according to soil and climatic conditions, pavement conditions, pavement types, surface types and annual average daily traffic. The probability distributions, statistical means, and standard deviation values of asset conditions and annual average daily traffic for each type were quantified. The probability distributions and the statistical information obtained in this analysis will be used to asset the variation and reliability in budget/cost estimates in later stage. Generally, we usually used mean values of asset data of each category as input values for investment analysis. The variability of asset data in each category is not taken into account. This analysis method demonstrated that it can be used for practical application taking into account the variability of road data in analysing large road networks for maintenance/rehabilitation investment analysis.

Nonfatal heroin overdoses in Queensland, Australia : an analysis of ambulance data

In the past decade, the utilization of ambulance data to inform the prevalence of nonfatal heroin overdose has increased. These data can assist public health policymakers, law enforcement agencies, and health providers in planning and allocating resources. This study examined the 672 ambulance attendances at nonfatal heroin overdoses in Queensland, Australia, in 2000. Gender distribution showed a typical 70/30 male-to-female ratio. An equal number of persons with nonfatal heroin overdose were between 15 and 24 years of age and 25 and 34 years of age. Police were present in only 1 of 6 cases, and 28.1% of patients reported using drugs alone. Ambulance data are proving to be a valuable population-based resource for describing the incidence and characteristics of nonfatal heroin overdose episodes. Future studies could focus on the differences between nonfatal heroin overdose and fatal heroin overdose samples.

Benchmarks for recycling practices in commercial office building refurbishment : data collection challenges

In recent years considerable effort has gone into quantifying the reuse and recycling potential of waste generated by residential construction. Unfortunately less information is available for the commercial refurbishment sector. It is hypothesised that significant economic and environmental benefit can be derived from closer monitoring of the commercial construction waste stream. With the aim of assessing these benefits, the authors are involved in ongoing case studies to record both current standard practice and the most effective means of improving the eco-efficiency of materials use in office building refurbishments. This paper focuses on the issues involved in developing methods for obtaining the necessary information on better waste management practices and establishing benchmark indicators. The need to create databases to establish benchmarks of waste minimisation best practice in commercial construction is stressed. Further research will monitor the delivery of case study projects and the levels of reuse and recycling achieved in directly quantifiable ways

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

Estimating indoor air quality using integrated 3D CAD building models

The indoor air quality (IAQ) in buildings is currently assessed by measurement of pollutants during building operation for comparison with air quality standards. Current practice at the design stage tries to minimise potential indoor air quality impacts of new building materials and contents by selecting low-emission materials. However low-emission materials are not always available, and even when used the aggregated pollutant concentrations from such materials are generally overlooked. This paper presents an innovative tool for estimating indoor air pollutant concentrations at the design stage, based on emissions over time from large area building materials, furniture and office equipment. The estimator considers volatile organic compounds, formaldehyde and airborne particles from indoor materials and office equipment and the contribution of outdoor urban air pollutants affected by urban location and ventilation system filtration. The estimated pollutants are for a single, fully mixed and ventilated zone in an office building with acceptable levels derived from Australian and international health-based standards. The model acquires its dimensional data for the indoor spaces from a 3D CAD model via IFC files and the emission data from a building products/contents emissions database. This paper describes the underlying approach to estimating indoor air quality and discusses the benefits of such an approach for designers and the occupants of buildings.