939 resultados para Digital Projects Workshop


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In the last fifteen years digital storytelling has come to stand for considerably more than a specific form of collaborative media production. It is also an international network of new media artists, creative practitioners, curators, scholars, and facilitating community media organisations. In May this year the movement will converge on Ankara, Turkey for its Fifth International Conference and Exhibition. The event will draw together key adopters, adapters and innovators in community-based methods of collaborative media production from around the world. Researchers from the Queensland University of Technology will lead a delegation that will include key players in the Australian digital storytelling movement.

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Collaborative infrastructure projects use hybrid formal and informal governance structures to manage transactions. Based on previous desk-top research, the authors identified the key mechanisms underlying project governance, and posited the performance implications of the governance (Chen et al. 2012). The current paper extends that qualitative research by testing the veracity of those findings using data from 320 Australian construction organisations. The results provide, for the first time, reliable and valid scales to measure governance and performance of collaborative projects, and the relationship between them. The results confirm seven of seven hypothesised governance mechanisms; 30 of 43 hypothesised underlying actions; eight of eight hypothesised key performance indicators; and the dual importance of formal and informal governance. A startling finding of the study was that the implementation intensity of informal mechanisms (non-contractual conditions) is a greater predictor of project performance variance than that of formal mechanisms (contractual conditions). Further, contractual conditions do not directly impact project performance; instead their impact is mediated by the non-contractual features of a project. Obligations established under the contract are not sufficient to optimise project performance.

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Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

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A recent success story of the Australian videogames industry is Brisbane based Halfbrick Studios, developer of the hit game for mobile devices, Fruit Ninja. Halfbrick not only survived the global financial crisis and an associated downturn in the Australian industry, but grew strongly, moving rapidly from developing licensed properties for platforms such as Game Boy Advance, Nintendo DS, and Playstation Portable (PSP) to becoming an independent developer and publisher of in-house titles, generating revenue both through App downloads and merchandise sales. Amongst the reasons for Halfbrick’s success is their ability to adaptively transform by addressing different technical platforms, user dynamics, business models and market conditions. Our ongoing case-study research from 2010 into Halfbrick’s innovation processes, culminating with some 10 semi-structured interviews with senior managers and developers, has identified a strong focus on workplace organisational culture, with staff reflecting that the company is a flat, team-based organisation devolving as much control as possible to the development teams directly, and encouraging a work-life balance in which creativity can thrive. The success of this strategy is evidenced through Halfbrick’s low staff turnover; amongst our interviewees most of the developers had been with the company for a number of years, with all speaking positively of the workplace culture and sense of creative autonomy they enjoyed. Interviews with the CEO, Shainiel Deo, and team leaders highlighted the autonomy afforded to each team and the organisation and management of the projects on which they work. Deo and team leaders emphasised the collaboration and communication skills they require in the developers that they employ, and that these characteristics were considered just as significant in hiring decisions as technical skills. Halfbrick’s developers celebrate their workplace culture and insist it has contributed to their capacity for innovation and to their commercial success with titles such as Fruit Ninja. This model of organisational management is reflected in both Stark’s (2009) idea of heterarchy, and Neff’s (2012) concept of venture labour, and provides a different perspective on the industry than the traditional political economy critique of precarious labour exploited by gaming conglomerates. Nevertheless, throughout many of the interviews and in our informal discussions with Halfbrick developers there is also a sense that this rewarding culture is quite tenuous and precarious in the context of a rapidly changing and uncertain global videogames industry. Whether such a workplace culture represents the future of the games industry, or is merely a ‘Prague Spring’ before companies such as Halfbrick are swallowed by traditional players’ remains to be seen. However, as the process of rapid and uncertain transformation plays out across the videogames industry, it is important to pay attention to emerging modes of organisation and workplace culture, even whilst they remain at the margins of the industry. In this paper we investigate Halfbrick’s workplace culture and ask how sustainable is this kind of rewarding and creative workplace?

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Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.

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BACKGROUND Research on engineering design is a core area of concern within engineering education and a fundamental understanding of how engineering students approach and undertake design is necessary in order to develop effective design models and pedagogies. Understanding the factors related to design experiences in education and how they affect student practice can help educators as well as designers to leverage these factors as part of the design process. PURPOSE This study investigated the design practices of first-year engineering students’ and their experiences with a first-year engineering course design project. The research questions that guided the investigation were: 1. From a student perspective, what design parameters or criteria are most important? 2. How does this perspective impact subsequent student design practice throughout the design process? DESIGN/METHOD The authors employed qualitative multi-case study methods (Miles & Huberman, 1994) in order to the answer the research questions. Participant teams were observed and video recorded during team design meetings in which they researched the background for the design problem, brainstormed and sketched possible solutions, as well as built prototypes and final models of their design solutions as part of a course design project. Analysis focused on explanation building (Yin, 2009) and utilized within-case and cross-case analysis (Miles & Huberman, 1994). RESULTS We found that students focused disproportionally on the functional parameter, i.e. the physical implementation of their solution, and the possible/applicable parameter, i.e. a possible and applicable solution that benefited the user, in comparison to other given parameters such as safety and innovativeness. In addition, we found that individual teams focused on the functional and possible/ applicable parameters in early design phases such as brainstorming/ ideation and sketching. When prompted to discuss these non-salient parameters (from the student perspective) in the final design report, student design teams often used a post-hoc justification to support how the final designs fit the parameters that they did not initially consider. CONCLUSIONS This study suggests is that student design teams become fixated on (and consequently prioritize) certain parameters they interpret as important because they feel these parameters were described more explicitly in terms how they were met and assessed. Students fail to consider other parameters, perceived to be less directly assessable, unless prompted to do so. Failure to consider other parameters in the early design phases subsequently affects their approach in design phases as well. Case studies examining students’ study strategies within three Australian Universities illustrate similarities with some student approaches to design.

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The report of this subcommittee concerns the impact of contact lenses (CLs) on the ocular surface, with a particular emphasis on CL discomfort (CLD). We define the ocular surface, its regional anatomy, and the physiological responses of each region to CL wear.