1. Quantum Sensing Trends Project Andrew Wharton December 8, 2012

2. Objective Visualization for the USAF to detect trends for Quantum Sensing research Easy, efficient tool Provide more than one perspective

3. Data One excel spreadsheet – Poor labeling – Formatting issues One BibTex file – Tough to export into CSV format Used Mendeley to export to RIS Then used JabRef to convert RIS into CSV *CSV is format desired for d3 use

4. Parsing and Filtering Inconsistent format between two files Also too much data—needed to filter Imported CSV into MySQL DB – Used queries to filter data – Export query results back to CSV Import CSV into d3

5. Initial Design Animated bubble chart using d3 Bubble represents keyword, size indicates frequency

6. Problems Too many years to share screen space – Unable to distinguish bubbles Could not easily detect trends over time – Identified this as a potential issue in the beginning, but decided to use colors to group bubbles across years – But, there were too many keywords, so colors were not unique Programming bugs – Animation was not working

7. Re-Design Keep it simple, but try something new using existing systems Create multiple components using Tableau, ManyEyes Integrate these components to provide user with opportunity to explore and discover in multiple ways

8. Idea Four components – Tag Cloud Provides overview – Bubble Chart Also provides overview, but in a different way – Bar Graph Shows breakdown over the years – Line Graph Easier way to identify trend over time All sortable by year, keyword(s)

9. Demo Click herehere

10. Result Not quite the “wow” factor as initial design Still answers questions Decided to discard BibTex data – Too few results, skewed the data and portrayed an inaccurate visualization Lessons learned with design and development – New frameworks = LOTS of overhead If few existing examples, re-prioritize based on time – Don’t go against basic design principles Being new is great, but a backup plan is needed in event of failure