Peter Griggs

Peter Griggs

Software Engineer @ Datadog

Papers

Database Updates Using Interactive Pan and Zoom Visualizations

Published:

Abstract

As datasets continue to get larger, there is a great need for visualization systems that scale well while maintaining interactivity. Kyrix [1] is a system that helps developers create scalable pan and zoom visualizations. It combines visualization paradigms for good performance like data tiling and prefetching with a database backend that creates spatial indexes for faster querying. This thesis modifies Kyrix to support direct manipulation of datasets through a data visualization. We add bindings to the Kyrix specification that allow the developer to enable updates in a visualization. The user can then interact with the visualization and update the data in order to test a hypotheses, add new data, or fix a data error. We showcase this functionality by implementing three different types of Kyrix visualizations: an NBA timeline visualization, an election forecasting visualization, and a scatter plot visualization of NBA game scores. We report the update performance statistics for each of the demo visualizations and provide an evaluation of changes to the Kyrix specification language.

Recommended citation: Griggs, Peter. (2021). "Database Updates Using Interactive Pan and Zoom Visualizations" (Meng Thesis). http://peterg17.github.io/files/thesis.pdf

Leam: An Interactive System for In-situ Visual Text Analysis

Published:

Abstract

With the increase in scale and availability of digital text generated on the web, enterprises such as online retailers and aggregators often use text analytics to mine and analyze the data to improve their services and products alike. Text data analysis is an iterative, non-linear process with diverse work-flows spanning multiple stages, from data cleaning to visualization. Existing text analytics systems usually accommodatea subset of these stages and often fail to address challenges related to data heterogeneity, provenance, workflow reusability and reproducibility, and compatibility with established practices. Based on a set of design considerations we derive from these challenges, we propose Leam, a system that treats the text analysis process as a single continuum by combining advantages of computational notebooks, spreadsheets, and visualization tools. Leam features an interactive user interface for running text analysis workflows, a new data model for managing multiple atomic and composite data types, and an expressive algebra that captures diverse sets of operations representing various stages of text analysis and enables coordination among different components of the system, including data, code, and visualizations. We report our current progress in Leam development while demonstrating its usefulness with usage examples. Finally, we outline a number of enhancements to Leam and identify several research directions for developing an interactive visual text analysis system.

Recommended citation: Leam: An Interactive System for In-situ Visual Text Analysis. S. Rahman, P. Griggs, Ç. Demiralp arXiv preprint, 2020 · CIDR, 2021. http://peterg17.github.io/files/cidr2021_leam.pdf