IS IT REALLY THAT BAD?Verifying the extent of full-text linking problems

Karen R. Harker, MLS, MPHCollection Assessment LibrarianUNT Libraries

“I find searching for journal articles and actually finding full articles to a very difficult. Sometimes it just links to another site and then to a fragment of an article.”

“It's hard to find links to online articles--some links say they can't find it, but sometimes you can still locate it and I don't know why the main "find links" page doesn't bring it up.”“Sometimes, if a link is not

provided to an article in the search results, it is very difficult to find. The article linker often comes up with no results even though it says the article is in UNT's collection.”

Frustrated with "Find Full-Text" when "it doesn't work“; “if it's not 100% perfect, there is really no point” in offering the service.

What have you done?

Link-CheckingRANDOM

Selection Cannot Be Predicted

What is required?

Intermediate to advanced Excel (but NOT programming)

Knowledge

About your collection

About the problem

Clear questions

Think about...your problem

your collection

your link resolver

your people

Brainstorm

Come away with…

What Kind of Research Questions?

Just a few

Be Specific

Compared to what?

What is important to you?

Such as…

Are links from EBSCO more successful than links from Ovid?

Is full-text linking better or worse compared to last year?

Is Serials Solutions’ 360 link resolver more likely to get to the full-text from our key resources than EBSCO’s?

What is the chance that a client will get the full-text of an article

on the first click?

Start with the Results

Sources Full-Text No Full-Text Total

EBSCO 90 10 100

Ovid 85 15 100

Totals 175 25 200

Comparing One Source With Another

Confidence Level

Chi-Square Test

Target Chi-Square

0.90 0.161 1.00-0.90=0.10Is Chi-Square test < Target? No

Is Ovid Significantly Different from EBSCO? No

Sources Full-Text No Full-Text Total

EBSCO 90 10 100Average 75 25 100

Totals 165 35 200

Comparing One Source With the Average

Confidence Level

Chi-Square Test

Target Chi-Square

0.90 0.001 1.00-0.90=0.10Is Chi-Square test < Target? Yes

Is EBSCO Significantly Different from the Average? Yes

Targets Full-Text No Full-Text Total

EBSCO 90 10 100Expected or Ideal Rate 95 5 100

Totals 185 15 200

Comparing One Target With The Expected or Ideal Rate

Confidence Level

Chi-Square Test

Target Chi-Square

0.90 0.022 1.00-0.90=0.10Is Chi-Square test < Target? Yes

Is EBSCO Significantly Different from Ideal Rate? Yes

Random Sampling

Review or background, depending on your viewpoint

Sampling Terms Universe

Sampling Population

Sampling Frame

Sample

All Citation

sCitations in databases to which we have access to articles to which we have full-text access

Only Journal Articles

Selection Methods

Convenience sampling

The chance of being selected is not known

The probability of any one citation being selected is known.

Non-probability Probability

Simple Random Sampling

Every citation that meets the criteria has an equal chance of being selected.

See Demo.

NOTE: Articles vary greatly by source, target and year.

Stratified Sampling

Every citation in discrete homogeneous groups has an equal chance of being chosen.

Try Demo again…

Useful to zero-in on a possible problem

Stratify by source, target & year, but would be time consuming

Sampling Population

Samples Selected from Each Stratum

Strata

Cluster Sampling

When the sampling population naturally “clusters” (e.g. source and targets).

The way they cluster doesn’t affect your outcome.

Divide population into these clusters

Randomly select the clusters to be a part of the sampling frame

Randomly select sample from selected clustersUseful for very large populations.

Sampling Population

Samples Selected from Selected Clusters

Clusters

This Methodology

Simple randomized cluster1. Select a sample of ejournals

(clusters)2. Search each database for articles3. Randomly select a citation (sample)4. Test and record results

Most useful for questions that are focused on the sources.

Other Questions, Other DesignsComparing link-resolvers: Matched-pair

1. Select a sample of ejournals2. Using one of the link resolvers, search the

source for articles in these ejournals.3. Randomly select a citation4. Test and record results5. For the next link resolver, search each

source for the same citation (the matched pair).

6. Test and record results.

For problems related to environment (browsers, location of user, etc.): Use the same

method as the link-resolver, only change the browser or location.

For problems related to targets: Use the same

method, but… Randomly select

ejournals from each target

Other Questions, Other Designs

Using Excel to Help You Along

Practical Applications

Before we begin…

For those with Laptops, download files: Excel file:

http://digital.library.unt.edu/ark:/67531/metadc96818/

PDF of Steps:http://digital.library.unt.edu/ark:/67531/metadc96827/ Or, just follow along…

I need to check how many?

May be fewer than you’d think Need to know:

Sampling strategy Kind of analysis Expected rate Chance of a title being indexed in the

source Number of databases or sources to

examine Educated Guess

Selecting the Journal Titles (Clusters)

1. Download your ejournals list

May want to limit to only those used recently

2. Randomly select the correct number of journals based on sample size

3. Randomly assign each title to the databases or sources you will be searching.

Excel Tricks Remove Duplicates Fill Cell – assigns a new

ID number Sampling method in

Data Analysis Randomly selects IDs

from your list VLOOKUP – gets the

titles for the selected IDs RANDBETWEEN –

Randomly assigns each title to a source to be searched

Search Source

If

fo

un

d

Random Number

If found

Select Citation

If found

Test Citation

I f f o u n dRecord Result

If

fo

un

d

If Not Found

Test the Sources

1. Login to the database2. Search for articles in the first journal3. If none are found, note this in your

results and skip to next title.4. If some are found, note the total

number of articles.

Test Sources

If articles are found:1. Sort the list by author last name (if

possible)2. Note the total number of articles found3. Enter this number in the Sample Size

Calculator worksheet (Random Article Selector)

4. Note the “Select this article” number5. In the database, navigate to this article6. Click on the Find Full-Text button

Full-Text PDF!

Test Sources

Note the success of that link in your tally sheet

Rinse & repeat: For each journal in the list For each database to be tested

Search Source

If

fo

un

d

Random Number

If found

Select Citation

If found

Test Citation

I f f o u n dRecord Result

If

fo

un

d

If Not Found

Tips & Tricks

Search by ISSN, if possible.

Display the most citations per page

If full-text article is in that database, skip title. This is a non-

response the Response

Rate the Sample Size

Summarize the data

Count up all results in each source

Create ratios for each result (e.g. Full-text ratio) # Full-Text / # Titles Found

Average the ratios

Example Data: Raw Counts

Example Data: Ratios

Test the Results

So you have a ratio – so what? What does it mean? Is it high? Low? Compared to what?

Use the Chi-Squared test to compare the ratios Excel: CHISQ.TEST(actual range, expected

range) If the result is less than 0.10 (or 1.00 –

Confidence Level), then the difference is statistically significant. This may be good or not good, depending on

what your comparing against.

Comparing Against an Ideal % Actual range: the # of Successes & # of

Failures Expected Range: # expected to be success

& # of expected failures Example: CHISQ.TEST(B2:C2, B3:C3)

A B C D

1 Sources Full-Text No Full-Text Total

2 EBSCO 90 10 1003 Expected or Ideal Rate 95 5 1004 Totals 185 15 2005 Chi-Square Test 0.022

6 Significantly Different from Expected Count? Yes

Sources to Test Sources Full-Text No Full-Text Total1EBSCO 70 21 912Ovid 90 23 113

Totals 160 44 204Chi-Square Test 0.031632

Significantly Different? Yes

Sources to Test Sources Full-Text No Full-Text Total3ProQuest 87 18 1051EBSCO 70 21 91

Totals 157 39 196Chi-Square Test 0.032782

Significantly Different? Yes

Sources to Test Sources Full-Text No Full-Text Total2Ovid 90 23 1135Means 82.3333333 20.66666667 103

Totals 172.333333 43.66666667 216Chi-Square Test 0.322856

Significantly Different? No

Any F/T Ratio80%

Any Link Ra-tio

16%

No Link Ratio5% Overall Success

EBSCO Ovid ProQuest0

20

40

60

80

100

120

# Titles by Link Type

No LinkAny LinkAny Full-Text

Context is King

The value of the result depends on what you are measuring and comparing If the difference between two sources is not

significant, then they are statistically similar.

If the difference between two link resolvers is significant, then one is better than the other. NOTE: This doesn’t tell you by how much!

Use your best judgment

I am here to help you…

Karen R. Harker940-565-2688karen.harker@unt.edu