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Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34

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Author: search.filters.author.García-Holgado, A.Subject: search.filters.subject.SPL

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    Fostering Decision-Making Processes in Health Ecosystems Through Visual Analytics and Machine Learning
    (Springer, 2022-06-26) García-Peñalvo, F. J.; Vázquez-Ingelmo, A.; García-Holgado, A.
    Data-intensive contexts, such as health, use information systems to merge, synthesize, represent, and visualize data by using interfaces to ease decision-making processes. All data management processes play an essential role in exploiting data’s strategic value from acquisition to visualization. Technologi-cal ecosystems allow the deployment of highly complex services while supporting their evolutionary nature. However, there is a challenge regarding the design of high-level interfaces that adapt to the evolving nature of data. The AVisSA project is focused on tackling the development of an automatic dashboard generation system (meta-dashboard) using Domain Engineering and Artificial Intelligence techniques. This approach makes it possible to obtain dashboards from data flows in technological ecosystems adapted to specific domains. The implementation of the meta-dashboard will make intensive use of user experience testing throughout its development, which will allow the involvement of other actors in the ecosystem as stakeholders (public administration, health managers, etc.). These actors will be able to use the data for decision-making and design improvements in health provision.
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    Specifying information dashboards’ interactive features through meta-model instantiation
    (CEUR-WS.org, 2020-09-19) Vázquez-Ingelmo, A.; García-Peñalvo, F. J.; Therón, R.; García-Holgado, A.
    Information dashboards1 can be leveraged to make informed decisions with the goal of improving policies, processes, and results in different contexts. However, the design process of these tools can be convoluted, given the variety of profiles that can be involved in decision-making processes. The educative context is one of the contexts that can benefit from the use of information dashboards, but given the diversity of actors within this area (teachers, managers, students, researchers, etc.), it is necessary to take into account different factors to deliver useful and effective tools. This work describes an approach to generate information dashboards with interactivity capabilities in different contexts through meta-modeling. Having the possibility of specifying interaction patterns within the generative workflow makes the personalization process more fine-grained, allowing to match very specific requirements from the user. An example of application within the context of Learning Analytics is presented to demonstrate the viability of this approach.