CREATIVITY FORWARD: A FRAMEWORK THAT INTEGRATES DATA ANALYSIS TECHNIQUES TO FOSTER CREATIVITY WITHIN THE CREATIVE PROCESS IN USER EXPERIENCE CONTEXTS

Author:

Quinones-Gomez Juan Carlos1ORCID

Affiliation:

1. Department of Mechanical Engineering and Fluid Mechanics, Higher School of Industrial Engineering, University of Málaga, Málaga, Spain

Abstract

The latest technological advancements allow users to generate a large volume of data related to their experiences and needs. However, the absence of an advanced methodology that links the big data and the creative process prevents the effective use of the data and extracting all its potential and knowledge in this context, which is crucial in offering user-centred solutions. Incorporating data creatively and critically as design material can help us learn and understand user needs better. Therefore, design can bring deeper meaning to data, just as data can enhance design practice. Accordingly, this work raises a reflection on whether designers could appropriate the workflow of data science in order to integrate it into the research process in the creative process within a framework of user experience analysis. The proposed model: data-driven design model, enhances the exploratory design of problem space and assists in the creation of ideas during the conceptual design phase. In this way, this work offers an integrated vision, enhancing creativity in industrial design as an instrument for the achievement of the proper and necessary balance between intuition and reason, design, and science.

Publisher

Vilnius Gediminas Technical University

Subject

Political Science and International Relations,Sociology and Political Science,Cultural Studies

Reference115 articles.

1. Adams, R. S., & Atman, C. J. (1999, 10–13 November). Cognitive processes in iterative design behaviour. In Proceedings of the 29th American Society for Engineering Education/Institute of Electrical and Electronics Engineers Frontiers in Education Conference. San Juan, Puerto Rico. Institute of Electrical and Electronics Engineers, 11a6-13–11a6-18.

2. Defining the execution semantics of stream processing engines

3. Data-mining-based methodology for the design of product families

4. The role of big data analytics in Internet of Things

5. Big Data‐Savvy Teams’ Skills, Big Data‐Driven Actions and Business Performance

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