The Suma Project

The problem

• Many libraries perform manual counts of people in spaces doing something at some time
• The process involves tedious collection mechanisms, lots of paperwork, and much room for error
• There is no coordinated effort to help departments analyze their data

by Joyce Chapman, Suma Community development and data analysis specialist.

Spreadsheets

• Dissimilar formats
• Fragmentation across time and topic
• Time-consuming analysis

We are data conformists.

Our solution

An open source tablet-based app (well, toolkit) to aid library staff in assessment of how patrons are using library spaces.

In other words…the gathering, storing, exporting, analyzing, and visualizing of data across spaces/activities/time and around events.

Suma principles

1. Support frequent data collection for a wide range of initiatives
2. Provide useful and usable tools for a wide range of staff
3. Support the integration of data querying and exploration into regular decision-making processes

Data collection

Suma data collection

Space Analytics

• Routine application of data to decision-making processes
  • Staffing
  • Hours
  • Service point locations
  • Outreach
• Ability to compare behavior before and after various changes
• Ability to explore usage data to better understand users

The web has had this for years

Staff as sensors

Understanding our users

• Where do our users go?
• What are they doing?
• When are they doing it?
• What could they be doing?

Technical Principles

• Data Integrity
• Performant Interfaces
• Reusable Tools

System Overview

System Overview

System Overview

System Overview

Data Synchronization

Core Technologies

• Zend PHP Framework
• MySQL, Web SQL Database, Persistence.js
• Bootstrap & Handlebars
• jQuery, Lodash, Moment.js
• D3.js

What does this enable?

Multi-dimensional Views of Data

Interactive Data Exploration

Data Export

• CSV File
• Chart Images

Structured Questions

• How does evening usage compare across initiatives?
• Do the types of questions vary based on time of day?
• Transaction length across points in semester?
• Evidence of roaming reference?

Future Work

• Comparative Analysis
• Proportional Analysis
• More Granularity (hourly)
• Improved Admin Interface

Example uses

• Hunt library opening metrics
• Special Collections outreach events
• Evaluation of roaming reference service
• Main sevice (reference) desk transaction analysis

Open Source

• 7+ active academic library pilot projects
• Hosted on GitHub
• Pull requests are always welcome

Open Source support (free kittens)

Project team

• Jason Casden
• Bret Davidson
• Joyce Chapman
• Rob Rucker
• Rusty Earl
• Eric McEachern

Thank You!

http://go.ncsu.edu/Suma

Jason Casden: jason_casden@ncsu.edu

Bret Davidson: bret_davidson@ncsu.edu