Toward an Interaction-Driven Framework for Modeling Big Data Visualization Systems

Abstract
Designing big data visualization applications is challenging due to their complex yet isolated development. One of the most common issues is an increase in latency that can be experienced while interacting with the system. There exists a variety of optimization techniques to handle this issue in specific scenarios, but we lack models for integrating them in a holistic way, hindering the integration of complementary functionality and hampering consistent evaluation across systems. In response, we present a framework for modeling the big data visualization pipeline which builds a bridge between the Visualization, Human-Computer Interaction, and Database communities by integrating their individual contributions within a single, easily interpretable pipeline. With this framework, visualization applications can become aware of the full end-to-end context, making it easier to determine which subset of optimizations best suits the current context.
Description

CCS Concepts: Information systems --> Information systems applications; Human-centered computing --> Human computer interaction (HCI)

        
@inproceedings{
10.2312:evp.20221125
, booktitle = {
EuroVis 2022 - Posters
}, editor = {
Krone, Michael
and
Lenti, Simone
and
Schmidt, Johanna
}, title = {{
Toward an Interaction-Driven Framework for Modeling Big Data Visualization Systems
}}, author = {
Benvenuti, Dario
and
Fiordeponti, Giovanni
and
Cheng, Hao
and
Catarci, Tiziana
and
Fekete, Jean-Daniel
and
Santucci, Giuseppe
and
Angelini, Marco
and
Battle, Leilani
}, year = {
2022
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-185-4
}, DOI = {
10.2312/evp.20221125
} }
Citation