AI-Supported EUD for Data Visualization: An Exploratory Case Study

Data visualization is a key activity in data-driven decision making and is gaining momentum in many organizational contexts. However, the role and contribution of both end-user development (EUD) and artificial intelligence (AI) technologies for data visualization and analytics are still not clear or...

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Vydáno v:Future internet Ročník 17; číslo 8; s. 349
Hlavní autoři: Beschi, Sara, Fogli, Daniela, Gargioni, Luigi, Locoro, Angela
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.08.2025
Témata:
Artificial intelligence
Case studies
case study research
Customization
Data analysis
Data visualization
data visualization routines
Decision making
Design
Designers
end-user development
human–AI interaction
Hypotheses
Information literacy
Information management
Large language models
Optimization techniques
Query formulation
Scientific visualization
Skills
Usability
Visual tasks
Visualization
Visualization (Computers)
ISSN:1999-5903, 1999-5903
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Shrnutí:Data visualization is a key activity in data-driven decision making and is gaining momentum in many organizational contexts. However, the role and contribution of both end-user development (EUD) and artificial intelligence (AI) technologies for data visualization and analytics are still not clear or systematically studied. This work investigates how effectively AI-supported EUD tools may assist visual analytics tasks in organizations. An exploratory case study with eight interviews with key informants allowed a deep understanding of data analysis and visualization practices in a large Italian company. It aimed at identifying the various professional roles and competencies necessary in the business context, understanding the data sources and data formats exploited in daily activities, and formulating suitable hypotheses to guide the design of AI-supported EUD tools for data analysis and visualization. In particular, the results of interviews with key informants yielded the development of a prototype of an LLM-based EUD environment, which was then used with selected target users to collect their opinions and expectations about this type of intervention in their work practice and organization. All the data collected during the exploratory case study finally led to defining a set of design guidelines for AI-supported EUD for data visualization.
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ISSN:1999-5903
1999-5903
DOI:10.3390/fi17080349