Comparing Common Data Environment Platforms for Student Collaborative Working: A Case Study from Ulster University

PAS1192-2 (2013) outlines the “fundamental principles of Level 2 information modeling”, one of these principles is the use of what is commonly referred to as a Common Data Environment (CDE). A CDE could be described as an internet-enabled cloudhosting platform, accessible to all construction team members to access shared project information. For the construction sector to achieve increased productivity goals, the next generation of industry professionals will need to be educated in a way that provides them with an appreciation of Building Information Modelling (BIM) working methods, at all levels, including an understanding of how data in a CDE should be structured, managed, shared and published. This presents a challenge for educational institutions in terms of providing a CDE that addresses the requirements set out in PAS1192-2, and mirrors organisational and professional working practices without causing confusion due to over complexity. This paper presents the findings of a two-year study undertaken at Ulster University comparing the use of a leading industry CDE platform with one derived from the in-house Virtual Learning Environment (VLE), for the delivery of a student BIM project. The research methodology employed was a qualitative case study analysis, focusing on observations from the academics involved and feedback from students. The results of the study show advantages for both CDE platforms depending on the learning outcomes required.

Is it time for standards and a common data exchange format for digital image analysis?

Digital image analysis is at a crossroads. While the technology has made great strides over the past few decades, there is an urgent need for image analysis to inform the next wave of large scale tissue biomarker discovery studies in cancer. Drawing parallels from the growth of next generation sequencing, this presentation will consider the case for a common language or standard format for storing and communicating digital image analysis data. In this context, image analysis data comprises more than simply an image with markups and attached key-value pair metrics. The desire to objectively benchmark competing platforms or a push for data to be deposited to public repositories much like genomics data may drive the need for a standard that also encompasses granular, cell-by-cell data.

Immunocompetence of nestling great tits in relation to rearing environment and parentage

Theoretical models of host-parasite coevolution assume a partially genetic basis to the variability in susceptibility to parasites among hosts, for instance as a result of genetic variation in immune function. However, few empirical data exist for free-living vertebrate hosts to support this presumption. In a cross-fostering experiment with nestling great tits, by comparing nestlings of the same origin we investigated (i) the variance in host resistance against an ectoparasite due to a common genetic origin, (ii) the effect of ectoparasite infestation on cell-mediated immunity and (iii) the variance in cell-mediated immunity due to a common genetic origin. Ectoparasitic hen fleas can impair the growth of nestling great tits and nestling growth was therefore taken as a measure of host susceptibility. A common origin did not account for a significant part of the variation in host susceptibility to fleas. There was no significant overall effect of fleas on nestling growth or cell-mediated immunity, as assessed by a cutaneous hypersensitivity response. A common rearing environment explained a significant part of the variation in cell-mediated immunity among nestlings, mainly through its effect on nestling body mass. The variation in cell-mediated immunity was also related to a common origin. However, the origin-related variation in body mass did not account for the origin-related differences in cell-mediated immunity. The results of the present study thus suggest heritable variation in cell-mediated immunity among nestling great tits. [References: 49]

Open standards-based system integration for asset management decision support

Over the last decade, system integration has grown in popularity as it allows organisations to streamline business processes. Traditionally, system integration has been conducted through point-to-point solutions – as a new integration scenario requirement arises, a custom solution is built between the relevant systems. Bus-based solutions are now preferred, whereby all systems communicate via an intermediary system such as an enterprise service bus, using a common data exchange model. This research investigates the use of a common data exchange model based on open standards, specifically MIMOSA OSA-EAI, for asset management system integration. A case study is conducted that involves the integration of processes between a SCADA, maintenance decision support and work management system. A diverse number of software platforms are employed in developing the final solution, all tied together through MIMOSA OSA-EAI-based XML web services. The lessons learned from the exercise are presented throughout the paper.

Vulnerability of axially loaded columns subjected to transverse impact loads

Increased industrialisation has brought to the forefront the susceptibility of concrete columns in both buildings and bridges to vehicle impacts. Accurate vulnerability assessments are crucial in the design process due to possible catastrophic nature of the failures that can cause. This paper reports on research undertaken to investigate the impact capacity of the columns of low to medium raised building designed according to Australian Standards. Numerical simulation techniques were used in the process and validation was done by using experimental results published in the literature. The investigation thus far has confirmed that vulnerability of typical columns in five story buildings located in urban areas to medium velocity car impacts and hence these columns need to be re-designed (if possible) or retrofitted. In addition, accuracy of the simplified method presented in EN 1991 to quantify the impact damage was scrutinised. A simplified concept to assess the damage due to all collisions modes was introduced. The research information will be extended to generate a common data base to assess the vulnerability of columns in urban areas against new generation of vehicles.

Infrastructure sustainability : vulnerability of axially loaded columns subjected to transverse impact loads

Increased industrialisation has brought to the forefront the susceptibility of concrete columns in both buildings and bridges to vehicle impacts. Accurate vulnerability assessments are crucial in the design process due to possible catastrophic nature of the failures that can cause. This chapter reports on research undertaken to investigate the impact capacity of the columns of low to medium raised building designed according to the Australian standards. Numerical simulation techniques were used in the process and validation was done by using experimental results published in the literature. The investigation thus far has confirmed that vulnerability of typical columns in five story buildings located in urban areas to medium velocity car impacts and hence these columns need to be re-designed or retrofitted. In addition, accuracy of the simplified method presented in EN 1991-1-7 to quantify the impact damage was scrutinised. A simplified concept to assess the damage due to all collisions modes was introduced. The research information will be extended to generate a common data base to assess the vulnerability of columns in urban areas against new generation of vehicles.

Digit recognition using trispectral features

Features derived from the trispectra of DFT magnitude slices are used for multi-font digit recognition. These features are insensitive to translation, rotation, or scaling of the input. They are also robust to noise. Classification accuracy tests were conducted on a common data base of 256× 256 pixel bilevel images of digits in 9 fonts. Randomly rotated and translated noisy versions were used for training and testing. The results indicate that the trispectral features are better than moment invariants and affine moment invariants. They achieve a classification accuracy of 95% compared to about 81% for Hu's (1962) moment invariants and 39% for the Flusser and Suk (1994) affine moment invariants on the same data in the presence of 1% impulse noise using a 1-NN classifier. For comparison, a multilayer perceptron with no normalization for rotations and translations yields 34% accuracy on 16× 16 pixel low-pass filtered and decimated versions of the same data.

Identifying differences in safe roads and crash prone roads using clustering data mining

Road asset managers are overwhelmed with a high volume of raw data which they need to process and utilise in supporting their decision making. This paper presents a method that processes road-crash data of a whole road network and exposes hidden value inherent in the data by deploying the clustering data mining method. The goal of the method is to partition the road network into a set of groups (classes) based on common data and characterise the class crash types to produce a crash profiles for each cluster. By comparing similar road classes with differing crash types and rates, insight can be gained into these differences that are caused by the particular characteristics of their roads. These differences can be used as evidence in knowledge development and decision support.

Developing tools to support complex infrastructure decision-making

Purpose – The rapidly changing role of capital city airports has placed demands on surrounding infrastructure. The need for infrastructure management and coordination is increasing as airports and cities grow and share common infrastructure frameworks. The purpose of this paper is to document the changing context in Australia, where the privatisation of airports has stimulated considerable land development with resulting pressures on surrounding infrastructure provision. It aims to describe a tool that is being developed to support decision-making between various stakeholders in the airport region. The use of planning support systems improves both communication and data transfer between stakeholders and provides a foundation for complex decisions on infrastructure. Design/methodology/approach – The research uses a case study approach and focuses on Brisbane International Airport and Brisbane City Council. The research is primarily descriptive and provides an empirical assessment of the challenges of developing and implementing planning support systems as a tool for governance and decision-making. Findings – The research assesses the challenges in implementing a common data platform for stakeholders. Agency data platforms and models, traditional roles in infrastructure planning, and integrating similar data platforms all provide barriers to sharing a common language. The use of a decision support system has to be shared by all stakeholders with a common platform that can be versatile enough to support scenarios and changing conditions. The use of iPadss for scenario modelling provides stakeholders the opportunity to interact, compare scenarios and views, and react with the modellers to explore other options. Originality/value – The research confirms that planning support systems have to be accessible and interactive by their users. The Airport City concept is a new and evolving focus for airport development and will place continuing pressure on infrastructure servicing. A coordinated and efficient approach to infrastructure decision-making is critical, and an interactive planning support system that can model infrastructure scenarios provides a sound tool for governance.

Data transformations in custom digital workflows : property graphs as a data model for user-defined mappings

This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

Population variation in biomonitoring data for persistent organic pollutants (POPs) : an examination of multiple population-based datasets for application to Australian pooled biomonitoring data

Background Australian national biomonitoring for persistent organic pollutants (POPs) relies upon age-specific pooled serum samples to characterize central tendencies of concentrations but does not provide estimates of upper bound concentrations. This analysis compares population variation from biomonitoring datasets from the US, Canada, Germany, Spain, and Belgium to identify and test patterns potentially useful for estimating population upper bound reference values for the Australian population. Methods Arithmetic means and the ratio of the 95th percentile to the arithmetic mean (P95:mean) were assessed by survey for defined age subgroups for three polychlorinated biphenyls (PCBs 138, 153, and 180), hexachlorobenzene (HCB), p,p-dichlorodiphenyldichloroethylene (DDE), 2,2′,4,4′ tetrabrominated diphenylether (PBDE 47), perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS). Results Arithmetic mean concentrations of each analyte varied widely across surveys and age groups. However, P95:mean ratios differed to a limited extent, with no systematic variation across ages. The average P95:mean ratios were 2.2 for the three PCBs and HCB; 3.0 for DDE; 2.0 and 2.3 for PFOA and PFOS, respectively. The P95:mean ratio for PBDE 47 was more variable among age groups, ranging from 2.7 to 4.8. The average P95:mean ratios accurately estimated age group-specific P95s in the Flemish Environmental Health Survey II and were used to estimate the P95s for the Australian population by age group from the pooled biomonitoring data. Conclusions Similar population variation patterns for POPs were observed across multiple surveys, even when absolute concentrations differed widely. These patterns can be used to estimate population upper bounds when only pooled sampling data are available.

Historical intake and elimination of polychlorinated biphenyls and organochlorine pesticides by the Australian population reconstructed from biomonitoring data

Quantifying the competing rates of intake and elimination of persistent organic pollutants (POPs) in the human body is necessary to understand the levels and trends of POPs at a population level. In this paper we reconstruct the historical intake and elimination of ten polychlorinated biphenyls (PCBs) and five organochlorine pesticides (OCPs) from Australian biomonitoring data by fitting a population-level pharmacokinetic (PK) model. Our analysis exploits two sets of cross-sectional biomonitoring data for PCBs and OCPs in pooled blood serum samples from the Australian population that were collected in 2003 and 2009. The modeled adult reference intakes in 1975 for PCB congeners ranged from 0.89 to 24.5 ng/kg bw/day, lower than the daily intakes of OCPs ranging from 73 to 970 ng/kg bw/day. Modeled intake rates are declining with half-times from 1.1 to 1.3 years for PCB congeners and 0.83 to 0.97 years for OCPs. The shortest modeled intrinsic human elimination half-life among the compounds studied here is 6.4 years for hexachlorobenzene, and the longest is 30 years for PCB-74. Our results indicate that it is feasible to reconstruct intakes and to estimate intrinsic human elimination half-lives using the population-level PK model and biomonitoring data only. Our modeled intrinsic human elimination half-lives are in good agreement with values from a similar study carried out for the population of the United Kingdom, and are generally longer than reported values from other industrialized countries in the Northern Hemisphere.

An architecture for trustworthy open data services

This paper addresses the development of trust in the use of Open Data through incorporation of appropriate authentication and integrity parameters for use by end user Open Data application developers in an architecture for trustworthy Open Data Services. The advantages of this architecture scheme is that it is far more scalable, not another certificate-based hierarchy that has problems with certificate revocation management. With the use of a Public File, if the key is compromised: it is a simple matter of the single responsible entity replacing the key pair with a new one and re-performing the data file signing process. Under this proposed architecture, the the Open Data environment does not interfere with the internal security schemes that might be employed by the entity. However, this architecture incorporates, when needed, parameters from the entity, e.g. person who authorized publishing as Open Data, at the time that datasets are created/added.