Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data
Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making it possible to provide a high level of detail for incoming and recent data while providing contextual information about recent history. Visual aggregation reduces data resolution in order to show the context of data over large periods of time within a limited display space. With a controlled experiment, we evaluated the effectiveness of different types of aggregation for four types of stream-analysis tasks. Overall, the results show that a focus-plus-context design has little negative impact on the ability to successfully monitor and analyze streaming data, making it possible to show longer periods of time than other approaches. However, visual aggregation can be problematic for trend recognition tasks. This research demonstrates how the effectiveness of the visualization depends on the specifics of the analysis task.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1684693
- Resource Relation:
- Conference: International Conference on Advanced Visual Interfaces (AVI) - Ischia, , Italy - 9/28/2020 8:00:00 AM-10/2/2020 8:00:00 AM
- Country of Publication:
- United States
- Language:
- English
Similar Records
Novel Analysis and Visualization of Chemical Events for Public Health Surveillance
Mapping scientific frontiers : the quest for knowledge visualization.