Designing and personalising systems for specific user groups encompasses a lot of effort with respect to analysing and understanding user behaviour. The goal of our paper is to provide a new methodology for determining navigational patterns of behaviour of specific user groups. We consider agricultural users as a specific user group, during the usage of a decision support system supporting cultivar selection - OPTIRas(TM). Combining process mining techniques with insights from decision making theories, we provide a method of analysing logs resulted from usage of decision support systems. For instance, farmers show difficulties in fulfilling the goal of OPTIRas, while other agricultural users seems to manage better. The results of our analysis can be used to support the redesign and personalization of decision support systems.
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Designing and personalising systems for specific user groups encompasses a lot of effort with respect to analysing and understanding user behaviour. The goal of our paper is to provide a new methodology for determining navigational patterns of behaviour of specific user groups. We consider agricultural users as a specific user group, during the usage of a decision support system supporting cultivar selection - OPTIRas(TM). Combining process mining techniques with insights from decision making theories, we provide a method of analysing logs resulted from usage of decision support systems. For instance, farmers show difficulties in fulfilling the goal of OPTIRas, while other agricultural users seems to manage better. The results of our analysis can be used to support the redesign and personalization of decision support systems.
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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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The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
Uitkomsten van besluitvorming bij overheidsinstanties kunnen gemakkelijk de publieke waarde vergroten of schenden. In dit onderzoek wordt een nieuwe, aan besluitvormingsondersteuning gerelateerde methode ontwikkeld om een positieve bijdrage aan de publieke waarde te leveren.Doel Hoewel de besluitvorming deels wordt beveiligd door op regels gebaseerde procedures die deze professionals moeten volgen, en deels door informatiesystemen, is decision mining een nieuwe techniek die, eenmaal correct toegepast, de kwaliteit van de besluitvorming voor publieke waarde zou kunnen verbeteren. Aanpak Door samen te werken met een reeks overheidsinstanties (Belastingdienst, UWV, IND, DUO, SVB, NVWA en Rijkswaterstaat) kunnen technologieën worden ontwikkeld voor het kunnen toepassen van decision mining. Dit ook met als doel uiteindelijk inzetbaar te kunnen zijn bij deze instanties. Resultaten Het ontdekken van uitdagingen van decision mining bij overheidsinstanties Het ontwikkelen van technieken voor: Het ontdekken van beslissingen uit data door middel van decision mining Beslissingen op conformiteit controleren door middel van decision mining Beslissingen verbeteren door middel van decision mining, vanuit een perspectief van publieke waarde Develop a method for using decision mining. Looptijd 20 november 2020 - 20 november 2025 Cofinanciering Dit onderzoek wordt gefinancierd door de Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Uitkomsten van besluitvorming bij overheidsinstanties kunnen gemakkelijk de publieke waarde vergroten of schenden. In dit onderzoek wordt een nieuwe, aan besluitvormingsondersteuning gerelateerde methode ontwikkeld om een positieve bijdrage aan de publieke waarde te leveren.
