SCOTT BERNIER | Senior Vice President OPTIMIZING DISCOVERY ER&L, April 2016 SCOTT BERNIER | Senior Vice President

Discovery Optimization is a collaborative effort across discovery providers, content providers & libraries. The contributions from each party have a direct impact on the end value…and all goals are aligned.

Collection Usage: the new reality of library platforms & user behavior Direct Usage of Specialized Resources Remains Discovery Services are Growing Adoption, Usage & Emphasis (focal point of library web sites) As libraries we are focused on the user experience As a community, we are embracing the new reality Moving beyond simple participation…into optimization

3 Major Areas for Optimization CONTENT 1. Exposing ENTIRE COLLECTION (Data/Records & Resources) RESULT LIST 2. Surfacing THE BEST RESULTS (Relevance Ranking) Facilitating ACCESS TO CONTENT (Linking) LINKING

Optimizing Content Exposure Partnerships across all content providers All publications from every publisher Streamline data delivery Beyond basic metadata Subject Indexing, Book chapter level detail As a means for discovering library resources Extending discovery value Non-textual data, Faculty connections, Facilitate ILL

Optimizing Content Exposure Apps & Cloud Services

Anticipating User Intent Highlighting Content Library Interaction Sampling of apps hosted for EDS 30+ EBSCO Discovery Field Engineers equals 100+ customer driven apps and plugins available

Curriculum Builder Instructors stay within the Course or Learning Management System, and can easily add EDS content into their courses Student reading lists in Moodle, Blackboard, Sakai, and more all LTI-compliant CMS/LMS <http://developers.imsglobal.org/catalog.html>

Item Request Clear full-text or request buttons are key MeSH Widget Button Widget PubMed Clinical Queries

Optimizing Results (Relevance) RESULT LIST Optimizing Results (Relevance) With billions of potential results, there has never been a time when precision relevance ranking has been more important for libraries Successful user experience is critical Not just a single search of your collection, but a truly worthy academic research tool A combination of factors enables optimal results for every search query…

Optimizing Results (Relevance) RESULT LIST Optimizing Results (Relevance) Comprehensive coverage + Detailed Metadata (including subject indexing) + Additional Editorial Value + Search Smarts (search technologies to maximize available information) = Precision Ranking (best results for every query)

RESULT LIST Optimizing Results (Relevance) Additional Editorial Value to further optimize Search Precision Enhanced Subject Precision EBSCO’s professional taxonomy team developed a knowledge base of topical concepts Then mapped vocabulary terms from multiple thesauri to these concepts When a user’s search term matches a known concept, the system uses appropriate mapped terms to precisely search against individual vocabularies

RESULT LIST Optimizing Results (Relevance) Additional Editorial Value to further optimize Search Precision Enhanced Subject Precision – WHY? Because each vocabulary uses its own terminologies to account for essentially the same concept, we are able to normalize search such that users don’t have to know how each index might develop its taxonomy Searchers use different search terms that are conceptually the same Because EBSCO has unique approach to discovery, we can further maximize the value of these subject indexes for the benefit of the user Ultimately, it’s about enhancing precision in search by augmenting unstructured keyword searches with structured subject index application

RESULT LIST Optimizing Results (Relevance) Additional Editorial Value to further optimize Search Precision Enhanced Subject Precision – Example: EBSCO Concept Knowledge Base: “Work-related injuries” Subject Index #1: “occupational injuries” Subject Index #2: “occupational-related injuries” Subject Index #3: “work-related injuries” When the user’s keyword search matches the “Work-related injuries” Concept, EDS applies a subject heading expansion using the preferred subject heading in that target database, thus matching highly relevant content. NOTE: This all occurs IN ADDITION TO our existing detailed relevance ranking

Optimizing Access to Full Text (Linking) Greatest possible accuracy A single click to the full text Remove potential points of failure Ensure common understanding of ideal scenarios (syntax, data, etc.)

Link optimization Link resolvers still flawed (20%+ fail) An additional % end in user frustration User Research shows that students learn (what not to do) Direct links can be better, but all links are not created equally

Full Text Linking - Simplified LINK RESOLVER CROSS REF DISCOVERY SERVICE RESULTS FULL TEXT CONTENT DIRECT LINKS

Linking Basics (Syntax) CONSTRUCTED OF MULTIPLE “BITS” OF DATA ISSN Volume Issue Page # Open URL (standard) Various forms of Proprietary Constructed URL (content provider “reacts well” to a specific link construction) Durable URL (Root + Unique Identifier) http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?arnumber={UniqueID} (Unique ID could leverage a DOI, for example.)

Linking Basics – What EBSCO is considering as a discovery provider Gain an understanding of the link construction each content provider can readily accept Which “Syntax” is OK/IDEAL for that content provider? How Does Data from the Origin (Discovery Service) Support the Syntax?

What do we need to know to optimize links? Syntax Supported by Content Provider (Y/N) Detail (Notes) Open URL Y Proprietary Specific Construction Unique ID Data

Example: 3 Records for Same Article Inspec JSTOR IEEE (publisher) ISSN Vol Issue Page # etc. Slightly different value for a given index field from these providers We receive data from IEEE Ideal link Syntax for IEEE is known Their preferred link construction Ideal Syntax can’t be constructed Generate ideal link for IEEE to deliver Fulltext Accurate direct link Link may not resolve May drop the user at journal or issue level

Ideal links for any record… Inspec JSTOR IEEE (publisher) Publisher data Ideal syntax IEEE Full Text DIRECT LINK Construct Ideal Link

More Linkouts to FULL TEXT Direct custom links SmartLinks+ Link Resolver

With EBSCO, there is more usage overall Direct Custom Links, Link Resolver & SmartLinks+ EBSCO generates more usage of publisher content than ever before through a combination of platforms - EBSCOhost and EBSCO Discovery Service

The link resolver is NOT A “SOURCE OF TRAFFIC” It is simply a “bridge” between the article record in a given platform and the full text on the publisher sides But, many times publishers can only see as far back as the link resolver I.E. – can’t see the origin (platform) where the user made request for full text Smartlinks plus Specific article or record PUBLISHERS Direct custom link EDS Link Resolver The origin of 40% of the traffic cannot be seen The most heavily used link resolvers are provided by companies that also offer a discovery service – adding to the confusion

NISO’s Approved Proposal Proposal was submitted to NISO to enable consistent visibility into where requests for full text originate When finalized, link resolvers will have guidelines on how to pass data to content providers in consistent manner Goal is to ensure that publishers (& Libraries) can accurately identify the levels of traffic from each platform (link resolvers are not platforms) Proposal approved

SCOTT BERNIER | Senior Vice President THANK YOU SCOTT BERNIER | Senior Vice President sbernier@ebsco.com 978 356 6500 ext. 2278