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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 18th Apr 2026, 05:33:06pm CEST

Agenda Overview

Session

D134: Workshop 8: THE DATA QUALITY PLAYBOOK FOR ENGINEERING DESIGN

Time:

Monday, 18/May/2026:

2:00pm - 5:30pm

Session Chair: Kostas Stylidis, Chalmers University of Technology, Sweden
Session Chair: Bastian Quattelbaum, Hochschule Niederrhein University of Applied Sciences, Germany

Location: Conference Hall Orlando 2

HOSTED BY THE DS DATA-INFORMED SIG

Session Abstract

Join us for a comprehensive workshop on “The Data Quality Playbook for Engineering Design”, where participants will explore a wide range of techniques and methodologies for effective data collection across different contexts, including academic research, industrial practice, and field studies. The workshop addresses both digital and analogue data collection methods, equipping participants with practical tools adaptable to their specific research and design needs.

A central focus will be placed on data quality criteria—such as accuracy, reliability, validity, and completeness—to support the creation and use of robust and trustworthy data sets. Through hands-on activities, participants will engage with best practices in data collection using surveys, interviews, observational studies, and digital tools such as mobile applications and cloud-based databases.

The workshop will also facilitate discussion on common challenges and practical solutions for maintaining data quality across different collection contexts. Finally, an outlook will be provided on how high-quality data sets can be connected to and leveraged by AI-based agents and tools in engineering design.

Objectives

To familiarize participants with a variety of data collection methods suitable for different research and design contexts.

To develop an understanding of key data quality criteria and how to apply them in practice.

To promote best practices for ensuring high data quality across both digital and analogue data collection approaches.

Key outcomes

Participants will engage with a curated toolkit of data collection strategies, which will be collaboratively examined and reflected upon during the workshop.

Participants will demonstrate increased awareness of the role and importance of data quality criteria in engineering design research and practice.