Name
Abstract | ||
|---|---|---|
Evaluating and selecting ideas is a critical and time-consuming step in collaborative ideation, making computational support for this task a desired research goal. However, existing automatic approaches to idea selection might eliminate valuable ideas. In this work we combine automatic approaches with human sensemaking. Kaleidoscope is an exploratory data analytics tool based on semantic technologies. It supports users in exploring and annotating existing ideas interactively. In the following, we present key design principles of Kaleidoscope. Based on qualitative feedback collected on a prototype, we identify potential improvements and describe future work.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3266037.3266106 | UIST '18: The 31st Annual ACM Symposium on User Interface Software and Technology
Berlin
Germany
October, 2018 |
Keywords | Field | DocType |
Information Visualization,Evaluation,Collaborative Ideation | Ideation,Semantic technology,Data analysis,Information visualization,Computer science,Sensemaking,Human–computer interaction,Exploratory data analysis,Kaleidoscope,RDF | Conference |
ISBN | Citations | PageRank |
978-1-4503-5949-8 | 0 | 0.34 |
References | Authors | |
8 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maximilian Mackeprang | 1 | 4 | 2.84 |
| Johann Strama | 2 | 0 | 0.34 |
| Gerold Schneider | 3 | 376 | 34.82 |
| Philipp Kuhnz | 4 | 0 | 0.34 |
| Jesse Josua Benjamin | 5 | 1 | 1.02 |
| Claudia Müller-Birn | 6 | 34 | 9.95 |