Author: alyxanderbur

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CommunityClick

CommunityClick

Led by: Mahmood Jasim
CommunityClick: Capturing and Reporting Community Feedback from Town Halls to Improve Inclusivity
CommunityClick: Towards Improving Inclusivity in Town Halls

Local governments still depend on traditional town halls for community consultation, despite problems such as a lack of inclusive participation for attendees and difficulty for civic organizers to capture attendees’ feedback in reports. Building on a formative study with 66 town hall attendees and 20 organizers, we designed and developed CommunityClick, a communitysourcing system that captures attendees’ feedback in an inclusive manner and enables organizers to author more comprehensive reports. During the meeting, in addition to recording meeting audio to capture vocal attendees’ feedback, we modify iClickers to give voice to reticent attendees by allowing them to provide real-time feedback beyond a binary signal. This information then automatically feeds into a meeting transcript augmented with attendees’ feedback and organizers’ tags. The augmented transcript along with a feedback-weighted summary of the transcript generated from text analysis methods is incorporated into an interactive authoring tool for organizers to write reports. From a field experiment at a town hall meeting, we demonstrate how CommunityClick can improve inclusivity by providing multiple avenues for attendees to share opinions. Additionally, interviews with eight expert organizers demonstrate CommunityClick’s utility in creating more comprehensive and accurate reports to inform critical civic decision-making. We discuss the possibility of integrating CommunityClick with town hall meetings in the future as well as expanding to other domains. 

Our next step in this project is to virtualize the iClicker component to enable silent attendees to share their opinions during online meetings and discussions.

If you are interested in working on or learning more about this project, please contact Mahmood Jasim at mjasim@cs.umass.edu

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Visualization of Differentially Private Data (VDPD)

Visualization of Differentially Private Data (VDPD)

Led by: Ali Sarvghad, Narges Mahyar
Current team: Mohammad Hadi Nezhad
Investigating Visual Analysis of Differentially Private Data

Differential privacy (DP) is an emerging technique for protecting sensitive data. This project investigates the principles of visual data exploration under differential privacy. In particular, we aim to understand if and how empirical visualization knowledge can be extended and adapted under DP.

If you are interested in working on or learning more about this project, please contact Ali Sarvghad at asarv@cs.umass.edu

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Bloom’s Taxonomy for Evaluation

Bloom’s Taxonomy for Evaluation

Understanding a visualization is a multi-level process. A reader must extract and extrapolate from numeric facts, understand how those facts apply to both the context of the data and other potential contexts, and draw or evaluate conclusions from the data. A well-designed visualization should support each of these levels of understanding. We diagnose levels of understanding of visualized data by adapting Bloom’s taxonomy, a common framework from the education literature. We describe each level of the framework and provide examples for how it can be applied to evaluate the efficacy of data visualizations along six levels of knowledge acquisition – knowledge, comprehension, application, analysis, synthesis, and evaluation. We present three case studies showing that this framework expands on existing methods to comprehensively measure how a visualization design facilitates a viewer’s understanding of visualizations. Although Bloom’s original taxonomy suggests a strong hierarchical structure for some domains, we found few examples of dependent relationships between performance at different levels for our three case studies. If this level-independence holds across new tested visualizations, the taxonomy could serve to inspire more targeted evaluations of levels of understanding that are relevant to a communication goal.

If you are interested in working on or learning more about this project, please contact Alyx Burns at alyxanderbur at umass dot edu.

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Creative-Pad

Creative-Pad

Led by: Narges Mahyar
On Two Desiderata for Creativity Support Tools

Creative-Pad is designed initially as a tool to help creative directors in an advertising agency to come up with new ideas to create an advertisement for their clients. These directors are often given a one-line brief describing a client product or service. For example, the sentence, “A car with more family space”, would describe a client’s new product which is a car targeted for family. The creative directors would have to design an advertisement suitable for promoting this product. They will need lots of ideas. Creative-Pad works by tapping into the internet as a rich source of information about all things. It takes in one or more keywords from the initial sentence and automatically searches the internet to retrieve any related information. It then processes the search results to extract interesting words and sentences. These words and sentences are then “beamed” in front of the creative directors to stimulate their thoughts for the new advertisement. An interface was specially designed to encourage creative thinking.

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Actenum

Actenum

Led by: Ali Sarvghad

In oil and gas industry, upstream operations have large complex schedules. Creating and maintain these large schedules requires expertise and tool support. The interconnected nature of many activities makes changing/updating/optimizing schedules a sensitive task. For instance, a small change in a single activity duration can large impacts on schedule duration and operational costs. In this project, we designed a visual solution to assist schedulers in understanding the identity (what changed) and magnitude (the effect size) on a schedule from different angles.

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Footprint & Footprint-II

Footprint & Footprint II

Led by: Ali Sarvghad
Visualizing Dimension Coverage to Support Exploratory Analysis

Footprint-II, a visual analysis history tool, was built to support coordination between analysts who worked in a different time/different place setting. The tool visualized the history of prior data explorations from three distinct angles: coverage of dimensions (e.g. Sales, Profit, Inventory Cost), coverage of data values, and the branching structure of the analysis. Our evaluation of this technique showed significant improvement in analysis coordination. Users of the tool better identified prior coverage by other and showed a greater focus on uninvestigated aspects of data.

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Avant-Garde

Avant-Garde

Led by: Ali Sarvghad

Avant-Garde is an online platform for multi-faceted visual analysis of HIV/AIDS data. This tool enables clinicians to explore heterogeneous HIV/AIDS data to understand the phylogenetic, demographic, geographic and temporal characteristics and relationships in data. Various coordinated views represent data from different angles. Brushing-and-linking and dynamic filtering enable users to quickly discover the hidden relationships in data. This research a collaboration between faculties of Computer Science and Engineering (CSE) and Medicine at the University of California, San Diego.

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Embedded Merge & Split

Embedded Merge & Split

Led by: Ali Sarvghad
Embedded Merge & Split: Visual Adjustment Of Data Grouping

This project investigates the use of novel and intuitive interaction techniques to support adaptive binning and grouping of data at the GUI level. Currently, exploratory data analysis tools only support the indirect manipulation of binning and grouping through interaction with various menus and sub-menus. We are investigating embedded interactions that enable a user to directly manipulate these criteria through interaction with graphical elements of a visualization.

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Revisiting Du Bois

Revisiting Du Bois’ Abolitionist Visualizations

2 rows of 7 visualizations are shown: The top row is made from new data, and the bottom row was made in 1900 by W.E.B. Du Bois

Led by: Andrew Cunningham, Alyx Burns, and Narges Mahyar
Looking to the Past to Visualize the Present: Revisiting W.E.B. Du Bois’ Abolitionist Visualizations
Talk

Amidst growing civil unrest in the United States, we are seeing a new wave of abolitionist thought, which challenges us to look at systems of historic oppression and imagine how we can fundamentally restructure them to bring about an equitable justice. In this poster, we revisit visualizations made in 1900 by sociologist and civil rights activist, W.E.B. Du Bois to help us view the modern state of race in America through a historical abolitionist lens. The juxtaposition of stylistically similar charts made over 100 years apart reveals that while America has made progress toward racial justice in some areas, there is still work to be done. We call upon the visualization community to highlight the experiences of marginalized people and to take part in visualizing data related to the pervasiveness of racism.

If you are interested in working on or learning more about this project, please contact Alyx Burns at alyxanderbur at umass dot edu.

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Collaborative Visual Data Analysis Around Large Interactive Surfaces

Collaborative Visual Data Analysis Around Large Interactive Surfaces

Led by: Narges Mahyar & Ali Sarvghad
Note-taking in co-located collaborative visual analytics: Analysis of an observational study
A Closer Look at Note Taking in the Co-located Collaborative Visual Analytics Process
Roles of notes in co-located collaborative visualization

To gain a deeper understanding of collaborative visual data analysis around large interactive surfaces, we designed and carried out an observational user study. Co-located teams worked on collaborative visual analytics tasks using large interactive wall and tabletop displays. Our findings reinforced the importance of record keeping as an integral activity during collaborative data analysis. In addition, we characterized notes according to their content, scope, and usage, and described how they would fit into the process of collaborative data analysis. We also suggested design guidelines for note-taking functionality for co-located collaborative visual analytics tools.