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Andrew Nagy, Serials Solutions Scott Garrison, Western Michigan University.

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Presentation on theme: "Andrew Nagy, Serials Solutions Scott Garrison, Western Michigan University."— Presentation transcript:

1 Andrew Nagy, Serials Solutions Scott Garrison, Western Michigan University

2  Developed and implemented VuFind at Villanova  still involved in developing it  Joined Serials Solutions in late 2008 to focus on Summon  APIs and integration (e.g. with VuFind)

3  Master’s level private Catholic university  Undergrad enrollment = ~6,000  One main library  ~850,000 bibliographic records  ~300 subscription databases  Voyager, SFX, MetaLib

4  Associate Dean for Public Services and Technology at WMU Libraries since 2007  Co-taught a course on Linux-based open source tools for libraries at UNC-Chapel Hill SILS  Has used and advocated open source systems and tools since ~1993  Chose VuFind for WMU in 2008

5  Carnegie research university  Undergrad enrollment = 25,000+  5 libraries serving multiple sites statewide  1.6M+ bibliographic records  400+ databases  4,500+ print journals  42,000+ online journals  Voyager, SFX, CONTENTdm, Luna

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7  Hasn’t kept up with Web, users’ expectations  Limited customization  Antiquated, rigid search technologies  Designed for known-item searching  Libraries have set expectations, learned to compensate accordingly

8  More every year in multiple packages  More alternatives, more confusion  Multiple A-Z lists to maintain, use  Interfaces change regularly  Query syntax varied, requires instruction???  “The version of ______ I teach is _______”

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10  Allows some general, discipline searching  Mixed, incomplete results  As slow as the slower silos  If local, very network-inefficient  Many different metadata schemas, less sophisticated searching

11  Vendor acquisitions, consolidation, catch-up  Open source options are emerging  Some products are still years away  All of the above leads to great FUD

12 dis ⋅ cov ⋅ er [di-skuhv-er] –verb (used with object) 1. to see, get knowledge of, learn of, find, or find out; gain sight or knowledge of (something previously unseen or unknown): to discover America; to discover electricity. 2. to notice or realize: I discovered I didn't have my credit card with me when I went to pay my bill. 3. Archaic. to make known; reveal; disclose.

13  Searching for the 21 st century  Built on 21 st century technology  Highly configurable interfaces  Puts our metadata to better use  Works for OPAC and other silos but relies on federated search, though evolving

14  Library budget cuts => more careful choices

15  Broad discovery of both known and unknown items in our collections, not just in their discipline  Be more like Google: simple, easy, fast  fewer places to look for more kinds of content  big recall is OK as long as most relevant is first  get to the actual item in fewest clicks possible

16  Get a new ILS?  Get a next-generation catalog?  Get a federated search tool?  Get a discovery tool?  Whither the link resolver?

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18  Provides simple, easy access to the library’s local collections  Supplements “classic” OPAC  Refines searches with “facets”  Includes external sources and community features  Wikipedia, tagging

19  Open source  VuFind  Blacklight  eXtensible Catalog  built on Lucene/Solr/Drupal  Commercial  AquaBrowser  WorldCat Local  Primo  Encore  Endeca

20  Mellon Award for Technology Collaboration winner 2008!  ILS-agnostic, runs alongside OPAC  Works for libraries of all sizes  Uses Apache Solr and AJAX  Feature rich  text messaging, Wikipedia author biographies, tagging and commenting, public lists

21  alpha fall 2008, beta spring 2009, “1.0” fall 2009  Customized the source in a variety of ways  SolrMARC importer, Voyager driver  search definitions, indexes, facet display  Usability tested 2008-2009  Still tweaking our indexes, relevance  “1.2” version coming spring 2010

22  Has helped us around limitations in Voyager  Recall => huge adjustment for librarians  Has prompted us to reconsider how we work  Themes from usability testing  fewer failed searches  user less likely to give up searching  users curious about things like tagging

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25  Librarians, users  will use Amazon to find and discover  will use Google to find and discover  will use del.icio.us to find and discover  Then they use the library catalog/website to find out if the library has it (link resolver buttons help even if it’s in five silos)

26  Local index of collections: MARC, OAI, etc.  Simple, elegant interfaces  Customizable  Mashups  Tuned relevancy ranking  Facets  Citation management tools  Links to value-adds like ILL, recommenders

27  Why only local collections?  What about article content?  What if users want to discover items outside their discipline-specific databases?  Can’t we do better than federated search?

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29 Web-scale dis ⋅ cov ⋅ er [web skeyl di-skuhv-er] - adjective-noun pairing Harvesting, ingesting, and normalizing an extensive amount of container and subcontainer metadata in a scalable infrastructure that many institutions can share rather than traditional “hosted services”.

30  Unifies local and subscription content  digital or physical books, e-journal articles, databases, etc.  library catalog, publishers, open access, etc.  Web-scale repository  Highly tuned relevancy  Pluggable API for “shopping mall” access

31 Web-Scale Discovery Service Enables quick discovery of the most credible resources anywhere the library has them Digital or physical Books, e-journal articles, databases, etc. Library catalog, publishers, open access, etc.

32 Simplified Illustration

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34  March 2009: became beta partner  April 2009: delivered catalog records  May 2009: had Summon instance  June 2009: used internally, refined e holdings  Summer 2009: kept improving  September 2009: linked to it on our site  Fall 2009: user testing

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36  Even bigger adjustment for library staff  Has reminded us of record problems  Shows known OpenURL target problems  How to present it along with VuFind?  the NGC is a subset of the W-sD  we’ve already tweaked the NGC pretty far  W-sD’s interface is similar to NGC  how to incorporate link resolver data?

37  Keep the NGC for containers and W-sD for everything else  use limits in query string to exclude containers  means two separate, different interfaces to choose from

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40  Use your NGC’s interface to query the W-sD’s index  radio button for containers vs. non?  unified results, or tabs?  limits you to NGC’s interface? Toggle?  opportunity to tweak the NGC closer to W-sD  subjects and other facets likely vary between them

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42  Use only the W-sD and scrap the NGC  impractical after heavy NGC investment and adjustment

43  Use the APIs you have for the NGC, W-sD, and link resolver and build your own mashup of all of them  requires a heavy investment of resources  involves merging functional requirements for three separate systems into one  requires very careful project management, keeping scope creep, long tail issues to a minimum

44 questions? andrew.nagy@serialssolutions.com scott.garrison@wmich.edu


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