Considering New Discovery Layers Tom Adam, Information Literacy Librarian, University of Western Ontario Alan Bell, University of Waterloo Nora Gaskin, McMaster University Sian Miekle, University of Toronto Martha Whitehead, Associate University Librarian, Queens University Library

Tom Adam University of Western Ontario

What were doing… Why? Variables and options ILS and the Discovery Layer Interface Decisions Are we there yet?

Whats it all about? Embrace change Work backwards Consider the user

What we know about what we do

How we are perceived…

Our Brand…

What would you do?

the User Experience… OCLC Perceptions survey Extract issued 2006

Where do you start? 89% I use a library website. ITS RIGHT HERE & ITS 2% I use a search engine like google.

COST-EFFECTIVE EASY TO USECONVENIENTFAST CREDIBLE ACCURATE Libraries are… Search Engines are… Reasons … CREDIBLE ACCURATE RELIABLE COST-EFFECTIVE EASY TO USE CONVENIENTFAST RELIABLE

Search engines fit perfectly with my lifestyle.

Our Legacy…

What can we do? Make the search engine better… Canadian Undergrad

Martha Whitehead Queens University Library

Discovery Layer? Next Generation Catalogue? Discovery Layer ILS - circ Image s These s Vendor ILS – bib, holdings E-J Fed Search

About discovery From inventory to discovery (and back again) Keyword searching versus index browsing Relevance ranking: precision, recall and first page principle

Open Source or Vendor open source e.g. VuFind, eXtensible Catalog, SOPAC ILS vendors e.g. Primo (Ex Libris), Encore (III) other vendors e.g. Endeca, BiblioCommons AquaBrowser, OCLC, Serials Solutions

Local or Hosted, Customize or Not Local: –hardware/software infrastructure –some local configuration possible Hosted: –minimal local hardware/software –ideally a service to manage user generated content Either: data matters

Web 2.0 Why? –interaction with collections –reliance on peer and expert opinion –social search What? Where? How? –user generated content academic concerns, placement, web scale –usage logs, recommender systems

Summary: some factors to consider User experience degree of integration search intelligence extensibility Local (or consortial) capacity time and money

Sian Miekle University of Toronto

Introducing the Discovery Layer Data loading User experience Local vs.hosted solutions

Data loading decisions Should data be loaded in new system? Advantages: Self-contained interface Data available to functionality of new system Challenges: Shifting the data Synchronizing the data

Discover Layer Application ILS Build indexes 8.5M items6.4M bib records2.3M authorities144K MARC holdings Restart application Convert to XML for search & display Data transfer (nightly)

XML […] The Canadian almanac & directory. Copp. Clark [etc.], Annual. [1st]- year; Title varies: , Scobie & Balfour's Canadian almanac, and […] […] Not quite 1000 MARC fields, 26 subfields, but…

Convert to XML MARC data […] The Canadian almanac & directory. Copp. Clark [etc.], Title varies: , Scobie & Balfour's Canadian almanac, and […] […]

01/30/09

User experience: using facets

User experience: changing search model

User experience: feedback 169 comments, Sept 08 – Jan 09 2:1 in favour of the new interface 50 comments requesting features (26 ideas) –6 ideas based old search models 6 grads, 3 library staff –6 ideas for new features 4 grads, 2 undergrads, 1 library staff –14 ideas: functionality missed from old system 6 faculty, 12 grads, 12 library staff, 3 undergrads

Local vs. hosted solutions Time to think Flexibility –Content: BIP, web pages, other data repositories –Presentation: visual, multiple, changing Challenges –Infrastructure –Staff Shared local solution? –Share common tasks –Share resources

Nora Gaskin McMaster University

1. User interface choices & decisions 2. User feedback & behaviour

UI Choices: Basic Search Screen just a search box & go? include choice of search indexes? (fielded searching) include alpha as well as keyword indexes? include limiting at time of search?

Search n Go: UWO (Encore)

Search n Go: Queens N.Y. (Aquabrowser)

Search n Go & Limit by Collection: Vanderbilt (Primo)

Choice of Keyword Indexes: U of T (Endeca)

Choice of Keyword Indexes & Databases: Villanova U. (VuFind)

Choice of Keyword & Alpha Indexes: Florida State U. (Endeca)

Choice of Keyword & Alpha Indexes: McMaster (Endeca)

Choice of Keyword/Phrase Indexes & Limit by Format, Location: Waterloo (Primo)

UI Choices & Decisions Search, search within results, start over – Oh my!

Search Within Results; Search button; Start Over link

New Search button; Search Within Results button

UI Choices: defaults facets: open, closed or a mix? after a closed facet has been opened, keep it open? after a search, keep the previously selected index chosen, or return to the default?

UI Choices: facets which? hierarchical or flat? what to call them? display order order of values within facets: alpha or most hits at the top? all and or some or?

UI Choices & Decisions Search logic –match on any 1, 2, 3 terms, all terms? Display –how to display the full bib & item details Alpha indexes –how to display?

1. User interface decisions 2. User feedback & behaviour

McMasters Initial Implementation Spring 2007 usability testing feedback via Tell us what you think button in catalogue most feedback within first 3-4 months

Some interesting results from usability tests... only 1 of 5 subjects used the dimensions (oh no!) some subjects relied on type-ahead to complete all queries

User Feedback: Negative

Suggestions/Problems/Question s

User Feedback: Positive

Most-Used Facets, Jan.-Dec. 2008

Alan Bell University of Waterloo

The hope, the promise One search box to provide fast and convenient access to all of our resources, regardless of format –Enable access to our digitized cultural memory –Address disjointed library experience –Attempt to remain relevant to web savvy users –Provide Google-like relevance and react to challenges on the commercial internet

Considerations, challenges Existing OPAC features Becoming an aggregator –Can we ever get metadata/access to everything? –Native interfaces –A lot of data Controlled vocabulary cross walks Local modifications and needs Partners/Community and Collaboration