Automatic generation of software interfaces for supporting decision-making processes. An application of domain engineering and machine learning
Information dashboards are sophisticated tools. Although they enable users to reach useful insights and support their decisionmaking challenges, a good design process is essential to obtain powerful tools. Users need to be part of these design processes, as they will be the consumers of the informat...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/140557 |
| Acceso en línea: | http://hdl.handle.net/10366/140557 |
| Access Level: | acceso abierto |
| Palabra clave: | Automatic generation Domain engineering Meta-modeling Information Dashboards High-level requirements 1203.17 Informática |
| Sumario: | Information dashboards are sophisticated tools. Although they enable users to reach useful insights and support their decisionmaking challenges, a good design process is essential to obtain powerful tools. Users need to be part of these design processes, as they will be the consumers of the information displayed. But users are very diverse and can have different goals, beliefs, preferences, etc., and creating a new dashboard for each potential user is not viable. There exist several tools that allow users to configure their displays without requiring programming skills. However, users might not exactly know what they want to visualize or explore, also becoming the configuration process a tedious task. This research project aims to explore the automatic generation of user interfaces for supporting these decisionmaking processes. To tackle these challenges, a domain engineering, and machine learning approach is taken. The main goal is to automatize the design process of dashboards by learning from the context, including the end-users and the target data to be displayed. |
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