The Suma Project: Integrating Observational Data Assessment Into Space And Service Design

Transcript

1. THE SUMA PROJECT INTEGRATING OBSERVATIONAL DATA ASSESSMENT INTO SPACE AND SERVICE DESIGN Jason Casden | Bret Davidson NCSU Libraries
2. 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
3. by Joyce Chapman, Suma Community development and data analysis specialist.
9. SPREADSHEETS Dissimilar formats Fragmentation across time and topic Time-consuming analysis We are data conformists.
10. 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.
15. 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
16. DATA COLLECTION
17. SUMA DATA COLLECTION
18. 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
19. THE WEB HAS HAD THIS FOR YEARS
20. STAFF AS SENSORS
21. UNDERSTANDING OUR USERS Where do our users go? What are they doing? When are they doing it? What could they be doing?
22. TECHNICAL PRINCIPLES Data Integrity Performant Interfaces Reusable Tools
23. SYSTEM OVERVIEW
24. SYSTEM OVERVIEW
25. SYSTEM OVERVIEW
26. SYSTEM OVERVIEW
27. DATA SYNCHRONIZATION
28. CORE TECHNOLOGIES Zend PHP Framework MySql, WebSQL, Persistence.js Bootstrap & Handlebars jQuery, Lodash, Moment.js D3.js
29. WHAT DOES THIS ENABLE?
30. MULTI-DIMENSIONAL VIEWS OF DATA
34. INTERACTIVE DATA EXPLORATION
37. DATA EXPORT CSV File Chart Images
38. 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?
39. DEMO
40. FUTURE WORK Comparative Analysis Proportional Analysis More Granularity (hourly) Improved Admin Interface
41. EXAMPLE USES Hunt library opening metrics Special Collections outreach events Evaluation of roaming reference service Main sevice (reference) desk transaction analysis
42. OPEN SOURCE 7+ active academic library pilot projects Hosted on GitHub Pull requests are always welcome
43. OPEN SOURCE SUPPORT (FREE KITTENS)
44. PROJECT TEAM Jason Casden Bret Davidson Joyce Chapman Rob Rucker Rusty Earl Eric McEachern
45. THANK YOU! Jason Casden: Bret Davidson: http://go.ncsu.edu/Suma jason_casden@ncsu.edu bret_davidson@ncsu.edu