How Discovery Impacts on Users’ ExperiencesLilly HO, Assistant Director of Technical Services

Library and Learning Commons, Zayed University

How does Discovery Impact on Users’ Experiences?

Discovery in academic libraries Discovery: Summon, Primo Central, Enterprise What are the highly desirable features of these

discovery? Why are these features highly desirable? How do these features impact on users’ experiences? Opportunities for future enhancements in discovery

services Approach of Technical Services towards Future

discovery

Discovery in Academic Libraries In the 21st century, the academic library supports

both research activities and teaching outcomes of faculty members and students through discovery services.

Discovery is changing the way that library users find and access library materials, especially electronic resources.

These discovery services embrace new technologies to provide:

Discovery in Academic Libraries Easy Information Retrieval

One-stop access to all library resources with a single search box on the library website.

Easy, Effective and Reliable Searches Display of local holding information effectively

with unified index or real-time searching capability of full-text library content.

Users’ Experience of Search and Retrieval is GREATLY improved

Discovery: Summon, Primo Central, EnterpriseDiscovery Summon Primo

CentralEnterprise

Year of 1st Launch

2009 2009 2005

Company ProQuest ExLibris SirsiDynixFeature Interface Interface,

ServicesInterface

Search Single unified index

Central index (Real-time)

Web-scale

Retrieval Full-text article level

Full-text article level

Non-article level*(Marshall Breeding, 2014)

Discovery: Summon, Primo Central, Enterprise

(F. William Chickering, 2014)

What are the Highly Desirable Features of Discovery?

(F. William Chickering, 2014)

What are the Highly Desirable Features of Discovery?

One-stop search for all library resources

A discovery tool should include all library resources in its search including the catalog with books and videos, journal articles in databases, and local archives and digital repository. This can be accomplished by the unified index or federated search, an essential component for a discovery tool. Some of the discovery tools are described as web-scale because of their potential to search seamlessly across all library resources.

Faceted navigation Discovery tools should allow users to narrow down the search results by categories, also called facets. The commonly used facets include locations, publication dates, authors, formats, and more.

Relevancy Relevancy results criteria should take into consideration circulation statistics and books with multiple copies. More frequently circulated books indicate popularity and usefulness, and they should be ranked higher on the top of the display. A book of multiple copies may also be an indication of importance.(F. William Chickering, 2014)

What are the Highly Desirable Features of Discovery?

Recommendation/related materials A discovery tool should recommend resources for readers in a similar manner to Amazon or other e-commerce sites, based on transaction logs. This should take the form of “readers who borrowed this item also borrowed the following…” or a link to recommended readings. It would be ideal if a discovery tool can recommend the most popular articles, a service similar to ExLibris’ bX Usage-based Services.

Auto-completion/stemming A discovery tool is equipped with the computational algorithm that it can auto-complete the search words or supply a list of previously used words or phrases for users to choose from. Google has stemming algorithms.

Functional Requirement for Bibliographic Retrieval (FRBR)

The latest development of RDA certainly makes a discovery tool more desirable if it can display FRBR relationships. For instance, a discovery tool may display and link different versions, editions or formats of a work, what FRBR refers to as expressions and manifestations.(F. William Chickering, 2014)

Why are these Features Highly Desirable?

User’s searching experience particularly improves in FIVE areas: Searching Relevancy Search refinements Use of data from the local library catalogue Use of discovered content

Why are these Features Highly Desirable?

Convenience Effectiveness

Efficiency

Search & Retrieval

Reliability

How do these Features Impact on Users’ Experiences?

Searching One-stop access interface, which is relying on a

central index of pre-harvested data, provides deep discovery of vast scholarly collections.

Most discovery tools do not have a recommendation system. Instead, they have adopted different approaches. Most discovery tools (like Summon) make recommendations from bibliographic data in MARC records such as subject headings for similar items.

But, Primo is one of the few discovery tools with a recommendation system similar to those used by Amazon and other Internet commercial sites. Its bX Article Recommender Service is based on usage patterns collected from its link resolver, SFX.

How do these Features Impact on Users’ Experiences?

Searching Auto-completion/Stemming is a highly useful

feature that Google excels at. When a user types in keywords in the search box, the discovery tool will supply a list of words or phrases that users can choose readily. Stemming not only automatically completes the spelling of a keyword, but also supplies a list of phrases that point to existing items. This feature is included in Summon and Enterprise.

How do these Features Impact on Users’ Experiences?

Relevancy Traditionally, relevancy is uniformly based on a

computer algorithm that calculates the frequency and relative position of a keyword (field weighting) in a record and displays the search results based on the final score. Other factors have never been a part of the decision in the display of search results.

In the discussion on discovery services, relevancy based on circulation statistics and other factors came up as a desirable possibility and make the relevancy ranking even more sophisticated.

Primo’s popularity ranking is calculated by use, meaning that the more an item record has been clicked and viewed, the more popular it is.

How do these Features Impact on Users’ Experiences?

Search refinements Faceted navigation allows users to further divide

search results into subsets based on pre-determined terms. It is highly configurable as many discovery tools allow libraries to decide on their own facets.

Summon and Enterprise users relied heavily on the refinements (like book, journal article), making use of them most often as a post-search refinement technique. They allow for facet types to be both included and excluded.

How do these Features Impact on Users’ Experiences?

Use of data from the local library catalogue The ability to add library catalog data as well as

retrieve and display call numbers, locations, and real-time availability information on the results list.

This customer-oriented approach benefits to users who are looking for all information related to their search request.

How do these Features Impact on Users’ Experiences?

Use of discovered content FRBR relationship among work, manifestation,

expression, and items. For instance, a search will not only retrieve a title, but different editions and formats of the work.

So far, most discovery tools are not capable of displaying the manifestations and expressions of a work in a meaningful way.

Primo can display FRBR relationship.

Opportunities for Future Enhancements in Discovery Services

Expectations regarding Application Programming Interfaces Expanding API Ecosystem Social features – communities of collaboration Rich media materials and collections Research data sets Discovery and access related to special collections

materials Analytics capabilities Altmetrics

(Marshall Breeding, 2015)

Approach of Technical Services towards Future discovery

Effective information literacy instruction Examine the search histories for the use of limiters

provided by the discovery such as peer reviewed, date, language or geography, advanced search Boolean, subject term.

Evaluate information needs by measuring the performance of the discovery service and which resources are retrieved as a result of its use.

Effective search strategy Support the training on users’ specific abilities to use

appropriate keywords to articulate the information needs with discovery.

Support the teaching on the use of available facets and limiters as well as the skill on narrowing results when using the discovery.

Approach of Technical Services towards Future discovery

Evaluation on discovery regularly The system appears to be easy to learn, teach and use. The facets, sort options etc. are sufficient for narrowing

search results. The system can properly index and display various

formats. The system provides sufficient user functions (email,

favorites, patron requests, etc). The system’s article index covers the sufficient amount

of the scholarly journal subscriptions. The system’s technical specification is sufficient for

local needs (such as available APIs, hosting options, etc).

Examples & Demonstration Zayed University Library at

http://zu.summon.serialssolutions.com/ (Summon) The Open University of Hong Kong Libraries at

http://www.lib.ouhk.edu.hk/ (Primo) University of the Virgin Islands at http

://uvi.ent.sirsi.net/client/en_US/default/ (Enterprise)

References Anita K. Foster & Jean B. MacDonald (2013) A Tale of Two Discoveries:

Comparing the Usability of Summon and EBSCO Discovery Service, Journal of Web Librarianship, 7:1, 1-19, DOI: 10.1080/19322909.2013.757936

F. William Chickering & Sharon Q. Yang (2014) Evaluation and Comparison of Discovery Tools: An Update, Information Technology and Libraries, June 2014

Marshall Breeding (2014) Library Resource Discovery Product Profiles - Context, Library Perspectives and Vendor Positions: Major Discovery Product Profiles, Library Technology Reports, 50:1, 33-52, https://journals.ala.org/ltr/article/view/4753/5677

Marshall Breeding (2015) The Future of Library Resource Discovery: A white paper commissioned by the NISO Discovery to Delivery (D2D) Topic Committee, NISO, http://www.niso.org/apps/group_public/download.php/14487/future_library_resource_discovery.pdf

Marshall Breeding (2016) Library Systems Report 2016 Power Plays: Commitment to Production Products, American Libraries, https://journals.ala.org/ltr/article/view/4753/5677

Nadine P. Ellero (2013) An Unexpected Discovery: One Library's Experience With Web-Scale Discovery Service (WSDS) Evaluation and Assessment, Journal of Library Administration, 53:5-6, 323-343, DOI: 10.1080/01930826.2013.876824

Thank You!