Making it work: Identifying the challenges of collaborative international research

In this article, we explore the challenges - and benefits - of conducting collaborative research on an international scale. The authors - from Australia, Canada, and New Zealand - draw upon their experiences in designing and conducting a three-country study. The growing pressures on scholars to work in collaborative research teams are described, and key findings and reflections are presented. It is claimed that such work is a highly complex and demanding extension to the academic's role. The authors conclude that, despite the somewhat negative sense that this reflection may convey, the synergies gained and the valuable comparative learning that took place make overcoming these challenges a worthwhile process. The experiences as outlined in this paper suggest that developing understandings of the challenges inherent in undertaking international collaborative research might well be a required component of the professional development opportunities afforded to new scholars.

Public and private psychiatry: Can they work together and is it worth the effort?

Objective: Partnerships in mental health care, particularly between public and private psychiatric services, are being increasingly recognized as important for optimizing patient management and the efficient organization of services. However, public sector mental health services and private psychiatrists do not always work well together and there seem to be a number of barriers to effective collaboration. This study set out to investigate the extent of collaborative 'shared care' arrangements between a public mental health service and private psychiatrists practising nearby. It also examined possible barriers to collaboration and some possible solutions to the identified problems. Method: A questionnaire examining the above factors was sent to all public sector mental health clinicians and all private psychiatrists in the area. Results: One hundred and five of the 154 (68.2%) public sector clinicians and 103 of the 194 (53.1%) private psychiatrists returned surveys. The main barriers to successful collaboration identified by members of both sectors were: 'Difficulty communicating' endorsed by 71.4% of public clinicians and 72% of private psychiatrists, 'Confusion of roles and responsibilities' endorsed by 62.9% and 66%, respectively, and 'Different treatment approach' by 47.6% and 45.6%, respectively. Over 60% of private psychiatrists identified problems with access to the public system as a barrier to successful shared care arrangements. It also emerged, as hypothesized, that the public and private systems tend to manage different patient populations and that public clinicians in particular are not fully aware of the private psychiatrists' range of expertise. This would result in fewer referrals for shared care across the sectors. Conclusions: A number of barriers to public sector clinicians and private psychiatrists collaborating in shared care arrangements were identified. The two groups surveyed identified similar barriers. Some of these can potentially be addressed by changes to service systems. Others require cultural shifts in both sectors. Improved communications including more opportunities for formal and informal meetings between people working in the two sectors would be likely to improve the understanding of the complementary sector's perspective and practice. Further changes would be expected to require careful work between the sectors on training, employment and practice protocols and initiatives, to allow better use of the existing services and resources.

Collaborative decision-making processes for maintaining biodiversity: Two Australian case studies

There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

Emergent temporal behaviour and collaborative work

Although collaboration manifestly takes place in time, the role of time in shaping the behaviour of collaborations, and collaborative systems, is not well understood. Time is more than clock-time or the subjective experience of time; its effects on systems include differential rates of change of system elements, temporally non-linear behaviour and phenomena such as entrainment and synchronization. As a system driver, it generates emergent effects shaping systems and their behaviour. In the paper we present a systems view of time, and consider the implications of such a view through the case of collaborative development of a new university timetabling system. Teasing out the key temporal phenomena using the notion of temporal trajectories helps us understand the emergent temporal behaviour and suggests a means for improving outcomes.

Collaborative filtering on data streams

Collaborate Filtering is one of the most popular recommendation algorithms. Most Collaborative Filtering algorithms work with a static set of data. This paper introduces a novel approach to providing recommendations using Collaborative Filtering when user rating is received over an incoming data stream. In an incoming stream there are massive amounts of data arriving rapidly making it impossible to save all the records for later analysis. By dynamically building a decision tree for every item as data arrive, the incoming data stream is used effectively although an inevitable trade off between accuracy and amount of memory used is introduced. By adding a simple personalization step using a hierarchy of the items, it is possible to improve the predicted ratings made by each decision tree and generate recommendations in real-time. Empirical studies with the dynamically built decision trees show that the personalization step improves the overall predicted accuracy.