The planning and design of an inland container terminal is a complex task due to many interrelated design parameters and interdependent stakeholders. Design tools may support the optimization of technical, economic and logistical values, but this optimization is strongly inhibited by conflicting interests, political and environmental boundaries and strategic stakeholder behavior. The main research question in this contribution is: how can visualization-simulation tools be used in an early stage of complex inter-organizational decision-making on infrastructures in such a way that it enhances the quality and progress of this decision-making? A collaborative design environment was developed for the early phase of inter-organizational decision-making. In the gaming-simulation 'containers a drift', a number of public and private stakeholders try to reach initial agreement on an inland container terminal. A team of process-managers facilitate a collaborative design process and set up a number of ground rules for negotiation. A visualization-simulation tool is used to explore the various technical, economic, political and spatial issues. While negotiating on issues such as location and size of the terminal, small groups of stakeholders interactively draw several terminal layouts. Logistical and economic data, e.g., on ships, containers and costs are entered in a database. The terminal's performance and its dynamic behavior is simulated and assessed. The game was played in three sessions with a total number of 77 students. The evaluation results indicate that the various tools are easy to work with, greatly contribute to the quality and process of negotiation and generate mutual understanding.
Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area. Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared and combined MRO data, flight data and external data, and used statistical and machine learning methods to visualize, analyse and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time and useful life of parts. Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data-sources and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining – and ways to overcome the related challenges – in MRO. Overall, the research project has delivered promising proofs of concept and pilot implementations
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Visualizing news is increasingly considered an apt way for dealing with two challenges of modern journalism: disclosing big data and presenting complex information in a way that is easy to comprehend. Newsrooms are trying their hand at it, and finding ways to organize the production of information visualizations effectively. This study delves into reported challenges for the production of news visualizations and suggests, in line with findings from the research case studies, that the introduction of information visualization in the media requires a convergence of journalistic and visual thinking skills, a more iterative news production process and a revised view of the function of news per se.
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