team photo

Figure 1
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Figure 2
project photo

Computer Science and Engineering
Team 8

Team Members

Advisor

Kevin Dunn
Danny Fryer
Haseeb Khan
Aakib Shaikh
Richard Zheng

Steven Demurjian

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SIFT - Automated Document Analysis

Sonalysts, the US Government, and academia/research institutions conduct qualitative or observational research to gain key insights into the design of systems, using methods such as Cognitive Walkthrough (CWT), Knowledge Elicitation (KE) interviews, and/or focus groups. Currently, data collected via these methods are transcribed, iteratively coded based on thematic analysis; then insights or results are manually generated by tabulating data, custom visualizations are manually developed, and analytical products are generated to disseminate these findings to decision makers (via PowerPoint, Word, Excel, etc.).
SIFT will be a web-based platform to consolidate and automate this process, enabling simultaneous processing/analysis of data and configuration management across a diverse group of users, including human factors engineers, data scientists, UX designers, graphic artists, and software engineers. SIFT will be a web-based technology, enabling collaboration across LANs, WANs, or the open internet depending on use case. The goal is to create a means to more rapidly process text-based qualitative data, glean insights from the data (via analytics or visualizations), develop analytic products, and provide traceability from resultant designs (predominantly visual media), through analysis, and all the way back to raw data.