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, and the third edition of DSIA was held at IEEE VIS 2018. We are thrilled to announce the fourth edition of the workshop, to be held at IEEE VIS 2019 in Vancouver.
- 9:00-9:05: Opening Statement
- 9:05-9:50: Keynote: Magdalena Balazinska
- 10:00-10:30: Papers session (10min per talk)
- 10:30-11:00: Break
- 11:00-12:15: Panel
- Magda Balazinska, UW
- Danyel Fisher, Honeycomb
- Leo Liu, Adobe
- Carlos Scheidegger, U Arizona
- 12:15-12:20: Closing Statement
- 12:20: Lunch at TBA. We will walk together from the workshop.
Keynote: Magdalena Balazinska
We are very excited to announce that Magdalena Balazinska from the University of Washington will be the keynote speaker for the workshop.
Title The LightDB Video Database Management System
Abstract Video data management has recently re-emerged as an active research area due to advances in machine learning and graphics hardware, as well as the emergence of applications such as adaptive streaming, object detection, and virtual reality. In this talk, we start with a review of the key requirements of modern video data management and analytics applications. We then present Visual Road, a new benchmark that we developed to assess video database systems on the needs of those modern applications. Finally, we dive into the details of LightDB, a new system that we are building at the University of Washington for the storage, retrieval, and analysis of video databases, including overlapping videos and 360-degree videos.
Bio Magdalena Balazinska is a Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington and the Director of the University of Washington data science institute called eScience. She is also the Associate Vice Provost for Data Science and the director of the Advanced Data Science PhD Option. Magdalena’s research interests are in the field of database management systems. Her current research focuses on data management for data science, big data systems, cloud computing, and image and video analytics (including data management for VR/AR). Magdalena holds a Ph.D. from the Massachusetts Institute of Technology (2006). She is a Microsoft Research New Faculty Fellow (2007), received the inaugural VLDB Women in Database Research Award (2016), an ACM SIGMOD Test-of-Time Award (2017), an NSF CAREER Award (2009), a 10-year most influential paper award (2010), the UW CSE ACM Teaching Award (2013), the Jean Loup Baer Career Development Professorship in Computer Science and Engineering (2014-2017), two Google Research Awards (2011 and 2018), an HP Labs Research Innovation Award (2009 and 2010), a Rogel Faculty Support Award (2006), a Microsoft Research Graduate Fellowship (2003-2005), and multiple best-paper (and “best of”) awards.
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.
- Submission Deadline:
July 13, 2019July 20, 2019
July 30, 2019August 1, 2019
- Final versions due: August 17, 2019
- Event: October 21, 2019
Paper Format and Submission
We are accepting papers in two formats:
- Preliminary research, late-breaking results and work in progress: 4 to 6 pages excluding references in IEEE VIS paper format. Accepted papers will be given a full slot to present at the workshop and will have the option to publish in IEEE Xplore.
- Position abstracts, research ideas and desired future work: 1 to 3 pages excluding references in IEEE VIS paper format. Accepted position papers will be given a 5-minute “lightning” talk slot at the workshop to share their ideas/concepts/concerns.
Papers should be submitted through the Precision Conference System (under “New Submissions” and “VIS Workshops 2019”). Please contact the workshop organizers at firstname.lastname@example.org for any questions regarding the submission process or the workshop itself.
At least one author from an accepted paper will be required to attend the workshop. Registration for the workshop can be done via VIS 2019.
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.