1. Creating a Library Learning Analytics Database
Michael Doran, Systems Librarian
University of Texas at Arlington
Library and Information Technology Association

2. LITA Forum - Michael Doran - Nov 19, 2016
To be covered…
What is a library learning analytics database?
Why is it needed?
A look under the hood
Security & privacy issues
Library vs. campus systems
LITA Forum - Michael Doran - Nov 19, 2016

3. LITA Forum - Michael Doran - Nov 19, 2016
Learning analytics
Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. [1]
[1] From “1st International Conference on Learning Analytics and Knowledge 2011” via Wikipedia article on “Learning analytics”
LITA Forum - Michael Doran - Nov 19, 2016 1

4. Creating a library learning analytics database…
…what problem(s)
does that solve?
LITA Forum - Michael Doran - Nov 19, 2016

5. Obligatory graphic of silos
“silos” photo by Doc Searls CC BY 2.0
LITA Forum - Michael Doran - Nov 19, 2016

6. LITA Forum - Michael Doran - Nov 19, 2016
Problems
Library use data resides in separate systems
Library systems typically don’t contain the student demographic information (e.g. major, academic program, GPA, student classification, etc.) needed to do learning analytics [a GOOD thing]
Library data sets may use different unique identifiers (e.g. Institutional ID number vs. NetID) preventing linking them together
LITA Forum - Michael Doran - Nov 19, 2016

7. Data Data Data Data Data Data Centralized database
Use data from various library systems
Data
Data
Data
Data
Data
Demographic
data from
Library Learning Analytics Database
Data
Centralized database
Chart
12 syllables
campus system
LITA Forum - Michael Doran - Nov 19, 2016

8. “LIBLAND” LIBrary Learning ANalytics Database
LITA Forum - Michael Doran - Nov 19, 2016

9. LIBLAND Data Data Data Data Data Data Centralized database LIBLAND
Use data from various library systems
Data
Data
Data
Data
Data
Demographic
data from
LIBLAND
Data
Centralized database
LIBLAND
campus system
LITA Forum - Michael Doran - Nov 19, 2016 1

10. Examples of systems with library use data
LITA Forum - Michael Doran - Nov 19, 2016

11. Entrance/exit gate turnstiles
Users swipe their “Mav Express” ID card to both enter and exit.
Renovation in 2014
Exit
Entry
LITA Forum - Michael Doran - Nov 19, 2016

12. Interlibrary Loan Requests (e.g. ILLiad)
LITA Forum - Michael Doran - Nov 19, 2016

13. Group Study Room Reservations (e.g. OpenRoom)
LITA Forum - Michael Doran - Nov 19, 2016

14. Off-campus Access to E-resources (e.g. EZproxy)
Note: approximately 15,000 (out of 43,000) Spring 2016 students were online only.
LITA Forum - Michael Doran - Nov 19, 2016

15. ILS Catalog (e.g. Voyager)
LITA Forum - Michael Doran - Nov 19, 2016

16. LIBLAND Data Data Data Data Data Data Centralized database LIBLAND
Use data from various library systems
Data
Data
Data
Data
Data
Demographic
data from
LIBLAND
Data
Centralized database
LIBLAND
campus system
LITA Forum - Michael Doran - Nov 19, 2016 1

17. Examples of systems with demographic data
LITA Forum - Michael Doran - Nov 19, 2016

18. Campus LDAP Directory (“CEDAR” at UT Arlington)
“provide a consolidated standards-based directory which can provide consistent and complete information on students, faculty, staff, courses, organizations, and other electronically-describable entities and relationships”
Central Enterprise Directory and Authentication Realm (CEDAR)
LITA Forum - Michael Doran - Nov 19, 2016

19. Blackboard Analytics
The center (for Distance Education] aspires to [...] be a resource to faculty and program administrators driving the use of learning analytics, including student learning outcomes; [...]
From UT Arlington’s Center for Distance Education
LITA Forum - Michael Doran - Nov 19, 2016

20. LITA Forum - Michael Doran - Nov 19, 2016
Your Campus?
Access to, or data dumps from:
LDAP directory
Peoplesoft
Banner
LMS (Learning Management System) …
LITA Forum - Michael Doran - Nov 19, 2016

21. Demographic data sources
Past, present, and future students
CEDAR/LDAP
137,000 records;
16 attributes
Bb A
43,000 recs;
16 attrib’s
LDAP criteria: utaPersonAffiliation=student
Blackb’d: Student registered for the term/semester in question
Total CEDAR records [filter: (|(utaID=*)(utaEmplID=*))] = 897,067
utaPersonAffiliation = Primary affiliation and all secondary affiliations, as those of: faculty, student, staff, alum, member, affiliate, employee, applicant
Current semester’s students
LITA Forum - Michael Doran - Nov 19, 2016

22. Attributes (from demographic data sources)
LDAP (CEDAR)
Blackboard Analytics
UTA ID
Student classification
Academic program
Major
Grade points
Hours complete
GPA (calculated)
Student status (i.e. enrolled now?)
Ethnicity
Gender
Permanent address zip code
Student address zip code
Enrollment code
Enrollment session
Expected graduation date
Library student employee?
UTA ID
Enrollment term
Academic program
Gender
Ethnicity
Age
Tuition residency
Student type
College/school
Department
Academic plan
Is academic partner?
Is online student?
Instruction mode
Academic load
Academic standing
Attributes chosen was done in consultation with Director of Quantitative Assessment (who coordinated with Library Management Team)
LITA Forum - Michael Doran - Nov 19, 2016

23. Attributes (from demographic data sources)
privacy
LDAP (CEDAR)
Blackboard Analytics
UTA ID
Student classification
Academic program
Major
Grade points
Hours complete
GPA (calculated)
Student status (i.e. enrolled now?)
Ethnicity
Gender
Permanent address zip code
Student address zip code
Enrollment code
Enrollment session
Expected graduation date
Is library student employee?
UTA ID
Enrollment term
Academic program
Gender
Ethnicity
Age
Tuition residency
Student type
College/school
Department
Academic plan
Is academic partner?
Is online student?
Instruction mode
Academic load
Academic standing
Note some attributes we are NOT retrieving
ID number… but not name
Age… but not date of birth
Zip code… but not street address
LITA Forum - Michael Doran - Nov 19, 2016

24. LITA Forum - Michael Doran - Nov 19, 2016
3 other important
data tables
LITA Forum - Michael Doran - Nov 19, 2016

25. LITA Forum - Michael Doran - Nov 19, 2016
Other Data Table #1
Knowing the affiliation of users who are not students helps fill in the gaps when linking library use data.
LITA Forum - Michael Doran - Nov 19, 2016

26. LITA Forum - Michael Doran - Nov 19, 2016
CEDAR/LDAP
698,000 records;
1 attribute
All records that
have a UTA ID
Only attribute is Primary Affiliation
student
faculty
employee
staff
affiliate
CEDAR/LDAP
137,000 records;
16 attributes
Bb A
43,000 recs;
16 attrib’s
Attribute is “utaPrimaryAffiliation”
student
faculty
employee
staff
affiliate
LITA Forum - Michael Doran - Nov 19, 2016

27. LITA Forum - Michael Doran - Nov 19, 2016
Other Data Table #2
Cross-reference table for different unique identifiers
LITA Forum - Michael Doran - Nov 19, 2016

28. All the UTA IDs (and associated NetIDs)
Problem: Library data sets may use different unique identifiers (e.g. Institutional ID number vs. NetID) preventing linking them together.
Demographic data only has UTA ID as an identifier
Much of the use data (e.g. ILLiad, Ezproxy, OpenRoom) only has the users’ NetID as an identifier
LITA Forum - Michael Doran - Nov 19, 2016

29. LITA Forum - Michael Doran - Nov 19, 2016
Other Data Table #3
Cross-reference table for cryptographic hash values
LITA Forum - Michael Doran - Nov 19, 2016

30. Making a (cryptographic) hash of it
A one-way hash function is an algorithm that takes a string (in this case, a UTA ID number) and returns a fixed- length alphanumeric string (the “hash value”).
foo.pl
LITA Forum - Michael Doran - Nov 19, 2016

31. Making a (cryptographic) hash of it
Slightly different strings get vastly different hash values
The same string always gets the same hash value*
LITA Forum - Michael Doran - Nov 19, 2016

32. Making a (cryptographic) hash of it
*The same string always gets the same hash value
Which is problematic, since UTA IDs are known to be 10-digit numbers. It wouldn’t be difficult to generate hash values for all the 10 digit numbers in the ranges used for UTA IDs and have a 10-digit number/hash value table, essentially reversing the process.
LITA Forum - Michael Doran - Nov 19, 2016 1

33. LITA Forum - Michael Doran - Nov 19, 2016
Cryptographic salt
A cryptographic salt is random data that is used as an additional input to a one-way hash.
bar.pl
LITA Forum - Michael Doran - Nov 19, 2016

34. LITA Forum - Michael Doran - Nov 19, 2016
Cryptographic salt
The same input string (UTA ID) gets a different hash value each time…
…because it’s being combined with a different random salt each time the SHA256 algorithm is applied.
LITA Forum - Michael Doran - Nov 19, 2016

35. LITA Forum - Michael Doran - Nov 19, 2016
This will allow us to do
data anonymization
[To be continued…]
LITA Forum - Michael Doran - Nov 19, 2016

36. Quick Review of What’s in LIBLAND
Other Data
Use Data
Demographic
Data
LITA Forum - Michael Doran - Nov 19, 2016

37. LIBLAND Data Data Data Data Data Data Centralized database LIBLAND
Use data from various library systems
Data
Data
Data
Data
Data
Demographic
data from
LIBLAND
Data
Centralized database
Stylized, simple, graphic
LIBLAND
campus system
LITA Forum - Michael Doran - Nov 19, 2016

38. LITA Forum - Michael Doran - Nov 19, 2016
Anonymize the data in an MS Access database.
LITA Forum - Michael Doran - Nov 19, 2016

39. LITA Forum - Michael Doran - Nov 19, 2016

40. LITA Forum - Michael Doran - Nov 19, 2016
Yikes!
LITA Forum - Michael Doran - Nov 19, 2016

41. LITA Forum - Michael Doran - Nov 19, 2016
Library use data
Demographic data
Start small(er)
System A
LDAP
Database
Directory
To get started on a “LIBLAND” project all you need are:
One library use data source
One demographic data source
LIBLAND
script
script
SQL load files
Database
LITA Forum - Michael Doran - Nov 19, 2016

42. LITA Forum - Michael Doran - Nov 19, 2016
Requirements
Expertise in:
Database design
SQL
Programming (a scripting language such as Perl, Python, or PHP)
Access to:
(A separate, secure) database server
Library systems containing use data
Campus systems with demographic data
LITA Forum - Michael Doran - Nov 19, 2016

43. LITA Forum - Michael Doran - Nov 19, 2016
scripts
Library use data
Demographic data
System A
LDAP
Recommend a scripting language like Perl, PHP, or Python
Script needs to:
Connect to system
Execute a query
Parse data
Output data (as SQL load file)
Database
Directory
LIBLAND
script
script
SQL load files
You will need “connector” library/module for the system you are connecting to: e.g. for Perl, the DBI/DBD::Oracle modules for connecting to an Oracle database, or Net::LDAP for connecting to an LDAP directory.
Database
LITA Forum - Michael Doran - Nov 19, 2016

44. LITA Forum - Michael Doran - Nov 19, 2016
SQL load files
Library use data
Demographic data
System A
LDAP
Scripts can/should output data as SQL “INSERT” statements
For output consisting of many rows of data…
Start SQL load file with
SET autocommit=0;
End with:
COMMIT;
Start a new INSERT statement every 10,000 rows
Database
Directory
LIBLAND
script
script
SQL load files
Database
LITA Forum - Michael Doran - Nov 19, 2016

45. SQL Load File mysql -u libland -p libland < illiad.sql
Command to load file:
mysql -u libland -p libland < illiad.sql
LITA Forum - Michael Doran - Nov 19, 2016

46. Granularity of Use Data Retrieved
privacy
We’re not pulling citation data…
LITA Forum - Michael Doran - Nov 19, 2016

47. Granularity of Use Data Retrieved
privacy
We extract the “destination host” but not the full URL (w/ query string) that identifies the exact resource.
Note: By default, EZProxy logs do not retain a username (“session ID” is default); capturing that data requires a configuration change.
LITA Forum - Michael Doran - Nov 19, 2016

48. Distributing LIBLAND Data
LITA Forum - Michael Doran - Nov 19, 2016

49. LITA Forum - Michael Doran - Nov 19, 2016
LIBLAND Tables
“Other” Data
Use Data
Demographic
Data
LITA Forum - Michael Doran - Nov 19, 2016

50. Tables... and Views
Views are virtual tables that get created on-the-fly via an SQL select statement.
Each view in LIBLAND contains the same data as in the table EXCEPT the UTA ID (or NetID) is replaced with the one-way hash value.
The views are what get exported from the LIBLAND server and imported into an MS Access database for distribution to staff.

51. On secure server
Distributed to staff

52. No Identifier (only a SHA-256 cryptographic hash) privacy
LITA Forum - Michael Doran - Nov 19, 2016

53. LITA Forum - Michael Doran - Nov 19, 2016
Why go to that trouble?
Data privacy is reason #1, #2, & #3
Bonus reason: If there is intent to publish or present the results of the analysis, you typically have to get institutional review board (IRB) approval. In advance.
However…
LITA Forum - Michael Doran - Nov 19, 2016

54. IRB Review Exemption (YMMV, always discuss with your IRB)
Institutional Review Board
LITA Forum - Michael Doran - Nov 19, 2016

55. LITA Forum - Michael Doran - Nov 19, 2016
University Analytics: "We
are the Borg. Your data
will be added to our own. Resistance is futile."
(Custom) Ed Hall cartoon reprinted by permission
ANALYTICS
LITA Forum - Michael Doran - Nov 19, 2016

56. LITA Forum - Michael Doran - Nov 19, 2016
Questions?
Please feel free to contact:
Michael Doran
Systems Librarian
University of Texas at Arlington
LITA Forum - Michael Doran - Nov 19, 2016