This is the website for the Workshop on Data Systems for Interactive Analysis (DSIA). The first edition of DSIA was held at IEEE VIS 2015, the second edition of DSIA was held at IEEE VIS 2017, the third edition of DSIA was held at IEEE VIS 2018, and the fourth edition of the workshop was held at IEEE VIS 2019 in Vancouver.
The DSIA Vision
Database researchers have developed techniques for storing and querying massive amounts of data, including methods for distributed, streaming and approximate computation. Machine learning techniques provide ways to discover unexpected patterns and to automate and scale well-defined analysis procedures. Recent systems research has looked at how to develop novel database systems architectures to support the iterative, optimization-oriented workloads of machine learning algorithms.
Of course, both the inputs and outputs of these systems are ultimately driven by people, in support of analysis tasks. The life-cycle of data involves an iterative, interactive process of determining which questions to ask, the data to analyze, appropriate features and models, and interpreting results. In order to achieve better analysis outcomes, data processing systems require improved interfaces that account for the strengths and limitations of human perception and cognition. Meanwhile, to keep up with the rising tide of data, interactive visualization tools need to integrate more techniques from databases and machine learning.
In this workshop, we will explore the idea that the next generation of database, machine learning, and interactive visualization systems should not be designed in isolation. For example, machine learning techniques might recommend improved data transformation and visual encoding decisions. Or, database query optimizers might take advantage of perceptual constraints, while prefetching methods reduce latency by modeling likely interactions.
This workshop seeks to jump start cross-pollination between these fields. The program will be split between invited talks from researchers in these communities, and speculative, ongoing work that straddles the areas.
The goal of DSIA is to foster innovative research at the intersection of databases, machine learning, and interactive visualization.
This workshop will focus on interactive systems: techniques, methods, architecture, systems that enable the user to interactively explore and analyze large amounts of data in the back end with little or no latency. We encourage late-breaking work, research in progress, and position papers in interactive analysis, broadly construed. For example, topics of interest to the workshop include (but are not limited to):
- design of database architectures for interactive analysis
- novel database applications for interactive analysis
- novel database techniques based on perceptual constraints and human-centered design
- evaluation of database systems for interactive analysis
- identify unique characteristics of databases for supporting visualization
- communication protocols between front and back ends
- techniques for data storage, retrieval, compression, transformation, sampling, and streaming
- techniques for metadata generation
- front-end architectures that exploit these novel back-end capabilities
We are interested, more generally, in the questions that arise at the intersection of these systems.
Code of Conduct
DSIA is committed to providing an inclusive and harassment-free environment. Please see the IEEE VIS Code of Conduct for details.
- Dominik Moritz, University of Washington.
- Joseph Cottam, Pacific Northwest National Laboratory.
- Leilani Battle, University of Maryland.
- Remco Chang, Tufts.
- Carlos Scheidegger, University of Arizona.
- Jeffrey Heer, University of Washington.
- Danyel Fisher, Honeycomb (previously Microsoft Research).
- Aditya Parameswaran, UC Berkeley.