Collection Assessment Strategies in Context: Using Data to Inform the Shift from Print to Electronic Collections Library Assessment Conference, August

Collection Assessment Strategies in Context: Using Data to Inform the

Shift from Print to Electronic Collections

Library Assessment Conference, August 3, 2014

Anne C. Osterman, Virtual Library of VirginiaMichael A. Matos, American University

“Collection assessment, at its best, is an art not a science, and the

numbers that it generates are a means not an end.”

– Jennifer Z. McClure, 2009

Agenda for Today• General introduction • Collection assessment approaches • Planning for and designing an effective collection

assessment project • Navigating the available data • Outside services and resources • Tips and techniques for analyzing library data in

common software packages • Data Analysis• Applying a visual approach to the presentation of

results

GENERAL INTRODUCTION

Reasons for Collection Assessment

• Determine breadth and depth or strengths and weaknesses of a collection, or a specific subject in that collection, for accreditation or reporting to administration/funders

• Understand how users interact with and use the collection

• Understand relationship with other libraries, such as when planning for cooperative action

• Inform a weeding/move to storage/shifting project• Analyze effectiveness of past budget allocations or

inform new allocations

HistoryUp until around the 1930s, collection

assessment was largely about description.

How many books does the collection have in which subjects?

1930s 1950s 1960s 1980s1970s 2000s

In the 1930s through the 1950s, list checking became an important approach.

Does the collection have certain books?

In the 1960s, studies about relevance to the population and usage emerged.

How many of the books were actually used?

Broader connections were made across collections in the 1970s, and qualitative

methods became important.What books does that library have, and

should mine have the same ones?

The Conspectus emerged as an important tool in the 1980s and 1990s, merging quantitative with qualitative data and

creating a shared vocabulary for collection strength.

How strong is our philosophy collection – instructional support or research level?

The growth of computing and the adoption of the Integrated Library System in the 1980s opened new possibilities for

gathering data.

I don’t want a sample – I want all the data.

The growth of e-resources in the 1990s and 2000s changed the collections as well

as the means and available data for collection assessment.

Can the use of print books predict the use of e-books?

1990s 2010s

In the 2000s, LibQUAL+ emerged as a programmatic survey of user perception.

How do our users perceive the collection, and what do they expect from it?

In the 2010s, data mining has emerged as the next major step in assessment.

What can the hidden patterns in our data tell us?

1990s

The Leading Edge of Data Analysis

• Data Warehousing and Marts• Analytics• Next-Gen ILS developments

Data Warehousing and Data Marts

• Conceptualized in the 1960s, data warehousing become popular with businesses in the 1990s

• A data warehouse is the holistic set of available data, both historical and current

• A data mart is a subsection of the data warehouse built for a particular reason or audience

Data Warehousing in Business

Sales Data

Customer Information

Supply Chain

Extraction Transformation

and Loading

Extraction Transformation

and Loading

Management

Reports

Data Mining

External Data

Data Warehousing

Data Warehousing

The Data Warehouse in the Library Context

Circulation Data

Acquisition Data

JCR Data

ILS Extraction and Data

Warehousing

ILS Extraction and Data

Warehousing

External DataExternal Data

Usage Stats

Collections Assessment (Strength)

Collection Assessment (Qualitative)

ManualData

Merge

Other Data Sources

ERMS

UseData

Analytics• Analytics processes and systems make extensive use of data,

quantitative analysis, and explanatory and predictive models to drive and automate decisions and actions

• They can be connected to live sources of data as well as stored data.

DataWarehouse

Live Sources of

Data

Analytics

Analytics in the Field of Customer Interaction

Business Analytics as Applied to Higher Education

Next-Gen ILS Assessment Tool: Intota Assessment

• Available as a stand-alone product from the Intota library services platform

• Combines data that have traditionally been stored in separate silos, such as local usage, Books in Print, and Resources for College Libraries

• Focused on informing actions, such as collection evaluation and deselection

From http://www.thedigitalshift.com/2013/11/ils/serials-solutions-launches-collection-analytics-tool-intota-assessment/

Next-Gen ILS Assessment Tool: OCLC’s Collection Evaluation

• Part of the WorldShare Management Services system

• Focused on monographic content• Allows libraries to compare

resources against 1 to 50 peer institutions, a variety of predefined groups, and authoritative lists from sources such as Choice, Booklist, Library Journal, and Publisher’s Weekly

Next-Gen ILS Assessment Tool: Alma Analytics

• Based on Oracle Business Intelligence Enterprise Edition

• Allows libraries to create reports that they can then share with other Alma libraries

• Includes physical format and electronic resource usage

• Can be integrated into a customized dashboard view that shows data trends

• Developing the ability to provide comparative analytics, such as from cross-institutional usage information


Image used with permission from Ex Libris.


Image used with permission from Ex Libris.

COLLECTION ASSESSMENT APPROACHES

Kinds of Collection Assessment

• Collection-based– “Collection-based techniques examine the size,

growth, depth, breadth, variety, balance, and coverage of library materials – often against an external standard or the holdings of one or more libraries known to be comprehensive in the relevant subject area.” (Peggy Johnson, 2009)

• Use- and User-based– “Use- and user-based approaches look at who is using

the materials, how often, and what their expectations are.” (Peggy Johnson, 2009)

Collection-Based Assessment: Regardless of Format

• Collection profile• Collection counts• Materials budget allocations• Citation analysis from external research or

resources

Collection-Based Assessment: Focus on Print

• Checking against lists and bibliographies• Scanning shelves• Analyzing against collection standards• Content overlap with peer/aspirational

libraries

Collection-Based Assessment: Focus on Electronic

• Title overlap in packages• Comparing content by acquisition model –

subscription, DDA, perpetual access• Comparison of databases/e-journal A to Z lists

Use- and User-Based Assessment: Regardless of Format

• Surveys of user opinion• Focus groups• Citation analysis from your population’s

research and publications

Use- and User-Based Assessment: Focus on Print

• Circulation/in-house use studies• Interlibrary loan/document delivery studies• Anthropological studies of user behavior• Gate counts

Use- and User-Based Assessment: Focus on Electronic

• Sessions, accesses/views, and downloads • Percentages of collection/package used • Use by acquisition model – subscription, DDA,

perpetual access• Turnaway reports• When and where resources are used, how did

the user link to the resource, how long did they stay in the resource

• Usability testing

Levels of Usage

• Borin and Yi (Collection Building 27:4) identify three levels of usage– access (web hits, database logins, gate counts,

catalog searches)– use of collection (viewing/downloading/printing,

circulation/reserves)– impact (student paper bibliographies,

theses/dissertations, faculty publications)

Differences between Print and Electronic Assessment

• Libraries are often dependent on the vendor for data for electronic resources

• Licensing, Digital Rights Management, platform, access, and other factors can be just as important as the digital content

• Much more granular tracking of use – by the chapter, by the article – is possible with electronic resources

• Circulation of print books vs. page views/chapter downloads/etc. of e-books are different expressions of use

Differences between Print and Electronic Assessment, cont.

• Electronic assessment can account for access denied/turnaways

• Access and holdings are much more complex in the electronic format – there is no central repository like WorldCat

• Open access is a factor• There can be challenges with duplicate usage

counts across databases on the same platform, particularly with broad searches enabled

• The content is sometimes not the same between print and electronic for the same title

Example: No Image in an Art Book

Project COUNTER

• Counting Online Usage of NeTworked Electronic Resources

• Tracks standard usage for electronic books, reference works, journals, databases, and now multimedia and articles

Selected Changes in COUNTER 4

• The introduction of Record Views and Result Clicks as metrics for databases

• A requirement to define Section types for e-books

• A new report for multimedia resources such as audio, video, and images

• A set of new reports that enable usage of content on mobile devices to be reported separately

COUNTER’s Usage Factor

• New! A usage-based measure of impact, value, and status for a journal. The first registry will be published in 2016.

• Possible through the implementation of another new initiative, article-level COUNTER reports.

PLANNING FOR AND DESIGNING AN EFFECTIVE COLLECTION ASSESSMENT PROJECT

The Process

• Set Goals• Identify Data• Collect Data• Review Data• Select an Analysis Tool• Analyze Data• Format analysis results for distribution

General Principles• Set clear goals from the beginning of the project

– planning in the beginning saves time in the end.• Although initial goals should be clear, allow for

unexpected discovery.• Become knowledgeable in all the available data

you might use as well as the limitations of that data.

• Keep thinking context – trends over time, user population, budget changes.

• Keep the story in mind – how would you tell an administrator about your project?

Set Goals Carefully

• What would answer the question?• Would the outcome be actionable?• Is this a one-time report or should it be done

regularly?

Start with Big Questions that You Care About

• Does the collection development approach make good use of the available budget?

• Is the collection meeting the user population’s needs?

• Does the collection make good use of the available space?

• Are your staffing levels correct for your collection and its formats?

Exercise One: Asking the Right Questions

Ex1: SWOT Analysis of Your Goals

Strengths Weaknesses

Opportunities Threats

+ -

Internal

External

NAVIGATING THE AVAILABLE DATA

Data Sources

• Library Systems (ILS, ERMS, Link Resolver)• Vendors• Library or Institution Website• Institutional/User Population Statistics• Lists/Bibliographies• Scholarly Works

Item-Level Collection Data

• Format• Serial or one-time• Publication date• Acquisition date• Publisher • Call number• Price

Item-Level Use Data

Print•Last circulated date•Circulation/renewal/in-house uses

Electronic•Section requests, page views, copies made, pages printed, PDF or HTML downloads•Turnaways

Other User Behavior Data

• Database/catalog use (searches, sessions, result clicks, record views)

• Interlibrary loan data • Entries into search boxes• Systems used• Origination of search• OpenURL requests• Gate counts

User Characteristics Data

• Type of user • On or off campus• Time when using library or library resources• What device they are using to access

resources

User Preferences Data

• Surveys• Focus Groups

Staffing Data• Titles selected– By a person– Based on a profile– As a package

• Items and formats acquired• Items and formats cataloged– Original– Copy

• Print books circulated • E-resource troubleshooting questions asked

User Population Context

• Population supported• Program size• Degrees awarded• Research dollars awarded

Standard-Based Comparisons

• Measure holdings against authoritative lists and rankings, such as Choice reviews, Publishers Weekly, Journal Citation Reports, Eigenfactor, altmetrics

Library-Based Comparisons

• With peer institutions• With aspirational institutions• Within or among consortia• With preservation initiatives such as

HathiTrust or Internet Archive

Summary Data

• Title counts• Acquisition rates• Annual expenditures• Average circulations/uses• Ratios of print to electronic or books to

journals• Percentage of available titles used• Average age

Data in Context

• Cost – Per use– Per title– Per FTE

• Circulation/Use– By subject– Compared to the

whole– Per user

• Volumes/Titles– By subject– Per user

• Material Expenditures– By subject

Data in Meaningful Groupings

• Groupings of numerical data – Publication date– Usage

• Low/Medium/High values

Data in Meaningful Groupings

Exercise Two: What Data Makes Sense?

Ex2: What Data Would be Helpful?

• Scenario One: What print volumes should you send to storage or weed?


• Scenario Two: How can the use of your print collections inform future electronic purchases?


• Scenario Three: Are your collections and budget allocations in line with the needs of the population they support?

OUTSIDE SERVICES AND RESOURCES

WorldCat Analysis: Holdings Analysis

• Compare your library’s collection with others by using volume counts per subject area

• Compare factors such as average date of publication among subclasses and classes

• Hard to overcome the great complexity of editions and formats, although FRBR helps

• Dependent on what libraries mark as their holdings in WorldCat

• Can provide a list of titles your library does not own

WorldCat Analysis: Title Count by Publication Year

WorldCat Analysis: Pre-Defined Comparisons

WorldCat Analysis: Comparison to WorldCat as a Whole

WorldCat Analysis: Title-Level Lists

Bowker’s Book Analysis System: Holdings Analysis

• Compares your library collection against Resources for College Libraries

• Works with data from your ILS, not WorldCat• Relative percentages of subject areas can

identify strengths and weaknesses• Creates lists of “core” materials that your

library doesn’t have

Library Analytics Toolkit

• Built through funding provided by the Harvard Library Innovation Lab

• Focused on better decision making through visualization

• Includes print and e-resource data• Code for the Toolkit is freely and publicly

available

Library Analytics Toolkit

http://librarylab.law.harvard.edu/toolkit/

Jisc LAMP Project

• LAMP = Library Analytics and Metrics Project• Developing a prototype, shared library

analytics service for UK academic libraries• Focused on combining data sets and

displaying them in a meaningful way

Jisc LAMP Project

http://jisclamp.mimas.ac.uk/

Sustainable Collection Services

• Guest speaker!

TIPS AND TECHNIQUES FOR ANALYZING LIBRARY DATA IN COMMON SOFTWARE PACKAGES

Cleaning Data with Excel• Quality Control– Minimum, Maximum, Mean, Median

• Cleaning Data– Find and replace– Concatenate– Left, Right, Mid– Substitution– Deduplication

• Categorization and Matching– Vertical and Horizontal Look Ups – If Statements

CONCATENATE• The CONCATENATE function joins up to 255 text characters into one text string.

The joined items can be text, numbers, cell references, or a combination of those items.

=CONCATENATE( Value to be concatenated, Item to be added, optional items [up to 255])

=CONCATENATE(A2,“00”)

Adds double zeros to the end of value in A2

LEFT, RIGHT, MID•LEFT returns the first character or characters in a text string, based on the number of characters you specify.•RIGHT returns the last character or characters in a text string, based on the number of characters you specify.•MID returns a specific number of characters from a text string, starting at the position you specify, based on the number of characters you specify.

=LEFT(A2,4) Returns the first four characters in A2=RIGHT (B2,2) Returns the last two characters in B2=MID(A2, 4, 2) Returns the two characters after the fourth character in A2

551519445Example:

SUBSTITUTE Substitutes new_text for old_text in a text string. Use SUBSTITUTE when you want to replace specific text in a text string; use REPLACE when you want to replace any text that occurs in a specific location in a text string.

=SUBSTITUTE(A2, “H”, “R”) substitutes the letter R for the letter H in A2.

NH1075.03NR1075.03

LOOKUPS

1.Allows you to search on one piece of data and return related data from a table

2.Can automate the search and return process3.Can search for exact or approximate values 4.Works with text and numeric data

The syntax is as follows:=VLOOKUP(lookup value, table array, column index number, [range_lookup])

=VLOOKUP(“2161-5063”, B3:C9, 3, False)

Table array: B3:C9

Column index number: 3

Range Lookup:False = Exact ValueTrue = Approximate Value

Answer: No, not in library holdings

Lookup value: 2161-5063

VLOOKUP

The syntax is as follows:=HLOOKUP(lookup value, table array, row index number, [range_lookup])

=HLOOKUP(17, A1:E2, 2, TRUE)Table array: A1:E2

Row index number: 2

HLOOKUP

Answer: Low book price level

Lookup value: 17

Range Lookup:False = Exact ValueTrue = Approximate Value

Exercise Three: Cleaning Data with Excel

ISBNsLC Call Numbers

Allocations

The Goal

• Use ISBN data from an ILS to give standardized publishers for the books in the report

IMPRINTNew York : Garland Pub., 1994.Englewood Cliffs, N.J. : Prentice Hall, c1988.Chicago : GIA Publications, c1997-<2004>New York : Random House, Inc., c2000-Thousand Oaks, Calif. : Sage Publications, c1995.Chicago : University of Chicago Press, 1987.Milwaukee, Wis. : American Chemical Society, Division of Chemical Education, Examinations Institute, c1998.

Brief Explanation: From the ISBN to the Publisher

• 0-00 through 0-19 represent particularly large publishers, because more numbers of the ISBN are left to distinguish individual books.

• This pattern continues through to 0-9500000 through 0-9999999, which represent much smaller publishers.

Brief Explanation: From the ISBN to the Publisher

• Using a listing of almost 116,000 publishers, the ISBN can be mapped to an individual publisher.

0195161467

Ex3: The goal: To clean and format the ISBN field so that it can be used to generate the publisher• Open the Sample Circulation Data file.• Sort the ISBN column from A to Z.• Create a new column to the right of the ISBN column and call it ISBN Step

One.• For the ISBNs needing two leading zeroes added (rows 2 and 3), enter

=CONCATENATE(“00”,A2) in the ISBN Step One column in the first relevant cell and drag the formula down to populate the other relevant cell.

• For the ISBNs needing one leading zero added (rows 4-24), use =CONCATENATE(“0”,A4).

• For the ISBNs with 13 digits (rows 25-32), remove the first three digits by using RIGHT(A25,10).

• For the ISBNs with 10 digits and unnecessary text after the numbers (rows 33-66), select only the ISBN using LEFT(A33,10).

• For the ISBN with 13 digits and unnecessary text after the numbers (row 67), select only the ISBN using MID(A67,4,10).

Ex3: The goal: To clean and format the ISBN field so that it can be used to generate the publisher

• Create a new column to the right of the ISBN Step One column and call it ISBN Step Two.

• To put the letter O where the zeroes are, enter =SUBSTITUTE(B2,"0","O") in the ISBN Step Two column. Carry the formula down the column.

• Create a new column to the right of the ISBN Step Two column and call it ISBN Step Three.

• Copy the content from the ISBN Step Two column and paste it (values only, not formulas) into the new column.

Sidenote: Using a Macro to Tell Relevant Digits

If the ISBN starts with OO or O1, this is a very large publisher, and you would use only the first three digits.

In the macro, this becomes:If Left(MyCell, 1) = "O" And (Mid(MyCell, 2, 1) = "O" Or Mid(MyCell, 2, 1) = "1") ThenMyCell = 3

Ex3: The goal: To clean and format the ISBN field so that it can be used to generate the publisher

• Go to the View tab (Tools on Macs) and click on Macros.

• Select the ISBN2Publisher macro and click Run.• Create a new column to the right of the ISBN Step

Three column and call it Standardized Publisher.• Enter the formula =VLOOKUP(LEFT(C2,D2),publist!

$A$1:$B$116000,2,FALSE) and carry it down the new column. This formula says to select the correct number of digits (column D) from the ISBN (column C) and look for that in the publisher worksheet.

• Do a quick check with the original Publisher column to see if the Standardized Publishers make sense.

Cleaning Data with OpenRefine

• Formerly Google Refine• Good for cleaning data– Uses facets– Easy to locate problem data– Allows complex transformations – Can cluster data for transformation

• Tracks all edits – can undo/redo at any point• Can copy all edits and apply them to other

data

Reserves Data in an Excel File

Import it into OpenRefine

Working with Text Facets



Using Clusters

Using Clusters

Using Clusters

Using Clusters

Using Clusters

Using Clusters

Working with Numeric Facets

Working with Numeric Facets

Trimming Values

Trimming Values

Trimming Values

Trimming Values

Trimming Values

Trimming Values

Trimming Values

Trimming Values

Trimming Values

History of Actions

History of Actions

Structuring, Summarizing, and Visualizing Data with Excel

• Structuring Data– Tables– Color Coding

• Summarizing Data– Pivot Tables

• Visualizing Data– Charts and Graphs

Conditional Formatting and Table ViewConditional Formatting•Increases the visibility of data based upon set parameters

Format as a TableLets one apply filters and sorting parameters to entire table

Sorting

Filtering

Takes data in a flat table and summarizes in a way that is much easier to read.

Pivot Tables

Using Graphs for Analysis

Exercise Four: Structuring, Summarizing, and Visualizing Data with Excel

Ex4a: To look for trends of circulation by publisher

• Open the Sample Circulation Data_clean file.• From the Home tab (Tables for Macs), click on

Format as Table.• Make sure it selects A1 through E619 as the

data.• Try out the table, selecting different filters.• Return the data to all showing.


• Select Column D, Total Circulation.• Click on Conditional Formatting, then Highlight

Cells Rules, then Greater Than. Put 100 in the cell value and click OK.

• Click the dropdown arrow at the top of Column D, Total Circulation, and select Sort by Color.

• Click on Conditional Formatting and select Clear Rules.


• Create a new worksheet in the file.• Go to Insert (or Data for Macs) and select

PivotTable.• Click on the spreadsheet/arrow icon.• Go back to the first sheet and select all the data.

It will say Table1 in the box.• Put Publisher in the Row Labels box and Total

Circulations in the Values box. Change the circulations to Average Circulations with only two decimal points showing.


• Remove Publisher from Row Labels and replace it with Call Number Initial Letter.

• Click on the Insert (or Charts for Macs) tab and select a chart.

Ex4b: Putting budget allocations in context

• Open the Program Analysis file.• Select the data, go to Insert (or Data for Macs)

and select PivotTable.• The PivotTable will be created in a new sheet. • Put Fiscal Year in the Row Labels box, Program

in the Column Labels box, and Graduate Enrollment in the Values box. (It will say Sum – that is okay, since there is just one Program value per Fiscal Year.)

Ex4b: Putting budget allocations in context

• Click on the Insert (or Charts for Macs) tab and select a line chart.

• Look at the data for each Enrollment and Print variable, one at a time, in the chart.

• How should the budget allocations be adjusted?

DATA ANALYSIS(STATISTICAL DEEP DIVE)

Analyzing Data with SPSS

Independent Samples T-Test

• Determines whether there is a statistically significant difference between the means in two unrelated groups.

• Requires one independent, nominal variable that has two categories (with no crossover between the two categories) and one dependent, interval/ratio variable.

ANOVA

• Generalizes the T-Test for three or more groups.

T-Tests and ANOVA: When Might You Use These?

• Determining if there is a statistically significant difference of:– Usage by patron group or subject area– Cost per use by title by subject area– What time library resources are being accessed by

patron group– Cost per FTE by college using departmental

information

T-Test and ANOVA Assumptions

• The observations are independent.• The variances of the two groups you are

measuring is approximately equal.• The dependent variable is approximately

normally distributed.

Normality: Issues with Skewed Data

Normality: Issues with Ordinal Data

Regression

• Examining the statistical relationship between one or more predictor variables and a single response variable, often focusing on a linear relationship

Regression: When Might You Use This?

• Assessing or creating a budget allocation formula

• Analyzing survey answers based on demographic responses

• Cross-library studies of collection size related to factors such as research dollars

Regression: A Few Tips

• Start simple and make the model more complex only if needed

• Have a reason for including each variable• Don’t forget to test for interaction effects

among your predictor variables


• Look at scatter plots of each predictor variable with the response variable


• Don’t forget to do diagnostics to evaluate the model– Plot the residuals, or observed errors, against the

predictor variables and fitted values to make sure there are no visible patterns and to check for outliers

– Look at a normal probability plot, histogram, or box plot of the residuals to check normality

• Remember that correlation is not causation

Summary, Context, and Visualization

• Basic arithmetic will take you far and might be all you need

• Simplicity in the analysis can help in simplicity in explaining the results

• Looking at the data in graphs and charts can be tremendously helpful

SPSS: Examining Shelf Life by Class

H Q

SPSS: Examining Shelf Life by Class

SPSS: Examining Shelf Life by SubClass

HF: Commerce HM: Sociology

APPLYING A VISUAL APPROACH TO THE PRESENTATION OF RESULTS

Edward TufteRetired Yale Professor of Political Science and Computer Science.

Has written extensively on visualizing data. Here are some of his key concepts:

•Data-Ink Ratio: Avoid extensive use of graphics in developing a data illustration

•Data density: A data graphic should be data rich

•Lie Factor: the relation between the size of effect shown in a graphic and the size of effect shown in the data

•Chartjunk: An image that has little informational value (think pie charts without percentages)

“May well be the greatest statistical graphic ever drawn” – Edward Tufte

Carte figurative des pertes successives en hommes de l'Armée Française dans la campagne de Russie 1812-1813

Charles Joseph Minard, 1869

Don’t be afraid to be complexProvide your audience with range of variables you looked at in making a decision

Copyright: Edward Tufte, 2007

Draw the Eye to the Key Point

Chart from “Telling Your Library’s Story: How to Make the Most of Your Data in a Presentation” by Anne C. Elguindi and Bill Mayer in Library Data: Empowering Practice and Persuasion, ed. by Darby Orcutt, ABC-CLIO, 2010.

Use Arrows to Show Motion

Chart from “Telling Your Library’s Story.”

Use Shapes in Interesting Ways


Try Going Without a Graph


Data Visualization Software

Rather than creating static reports, data visualization software programs, like Tableau and Socrata, allow one to create a customizable data objects.

QUESTIONS?

Documents

Collection Assessment Strategies in Context: Using Data to Inform the Shift from Print to Electronic Collections Library Assessment Conference, August