IU Digital Library Brown Bag October 19, 2011
Overview of
IU Digital Collections Search
Hui Zhang
Jon Dunn
Indiana University Digital Library Program
IU Digital Library Brown Bag
October 19, 2011
Outline
Introduction and motivation – Jon
Demo – Jon
Technical implementation – Hui
Next steps and future work – Jon
Why cross-collection search?
Support discovery across multiple content formats, collections, and repositories at IU
Use cases:
◦ Multiple formats/collections within a single thematic grouping (e.g. Hoagy Carmichael )
◦ Show off the richness and diversity of IU’s digital collections (PR – see open.iu.edu
)
◦ Find digital content at IU for teaching or research use
Why cross-collection search?
Support discovery across multiple content formats, collections, and repositories at IU
Use cases:
◦ Multiple formats/collections within a single thematic grouping (e.g. Hoagy Carmichael )
◦ Show off the richness and diversity of IU’s digital collections (PR – see open.iu.edu
)
◦ Find digital content at IU for teaching or research use
Digital collections evolution:
Discrete collection web sites
Digital collections evolution:
Services
METS Navigator Archives Online PhotoCat
Video Streaming Service Variations
Digital collections evolution:
Services
Advantages
◦ Can develop workflows for content ingestion and description that are both optimized and scalable
◦ Content stored in a common repository (Fedora)
◦ Can develop discovery interfaces optimized for particular content (e.g. images vs. music)
◦ Common services to expose content into other platforms (e.g. Google)
Disadvantages
◦ “Siloing” discovery by content type can be an issue
Cross-collection search:
First iteration
Only selected collections with metadata in
Fedora
◦ Includes Archives Online and most image collections
◦ Not video streaming, Variations, encoded text,
IUScholarWorks, various “legacy” collections
Metadata only (MODS)
◦ Stored natively as MODS in Fedora
◦ Disseminated on the fly from other formats
(PhotoCat2)
◦ Transformed via XSLT from EAD
(Archives Online)
Cross-collection search:
First iteration
Demonstration
Challenge:
Item-level records from EAD
Apache Solr Overview
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•
•
•
A Java-based web application, open source search server, Apache Lucene at its core
Demonstration
Solr vs. relational database
• Pros: full-text search, text analysis, flexible fields
• Cons: no relational operation on fields
Solr vs. Lucene
• Pros: web application, centralized configuration, facet
• Cons: security, slower
Solr Schema and Configuration
Schema: specify how the index is built
◦ field, field type
◦ dynamicField, copyField, uniqueKey
◦ Text analysis: stop, stem, synonym, tokenization
Configuration: specify Solr itself, query, data import
Converting MODS to Solr XML
Solr XML
◦ <add><doc><field>…</filed>…</doc></add>
◦ Can simply be “POST” into the Solr index
Translation of MODS to Solr XML
◦ Use XSLT
◦ Called by the indexing program
Extract facet values
◦ Format: MODS:typeofResource
◦ Collection: customized based on item’s Fedora
PID
<add>
<doc>
<field name="id">iudl:10000</field>
<field name="title_t">Women Medical Students</field>
<field name="name_t">Photographic Services, Photographer</field>
<field name="name_facet">Photographic Services</field>
<field name="subject_topic_t">Medical students</field>
<field name="subject_topic_facet">Medical students</field>
<field name="subject_city_t">Bloomington</field>
<field name="subject_city_facet">Bloomington</field>
<field name="subject_state_t">Indiana</field>
<field name="subject_state_facet">Indiana</field>
<field name="type_of_resource_t">still image</field>
<field name="type_of_resource_facet">still image</field>
<field name="genre_t">Photographs</field>
<field name="genre_facet">Photographs</field>
<field name="w3c_taken_date">04-13-1956</field>
<field name="year">1956</field>
<field name="item_id">P0028020</field>
<field name="coll_id_mods">/archives/photos/</field>
…
</doc>
</add>
Solr Indexing
Carried by two Java programs running under
DLP’s Fedora Index Service framework
The service can be invoked by a RESTful
HTTP request, the Solr indexing is triggered based on conditions specified in the properties file
The MODS records are extracted from the
Fedora repository (natively stored) or generated by the getMODS disseminator
(Photocat2 collections)
Overview of Blacklight
An open source project developed for libraries with many potentials:
◦ As a library catalog
◦ As the discovery interface to a digital repository
Optimized to handle diversified content
(facet browsing)
Originally developed by University of
Virginia, has a growing community of active contributors and users
Now part of Hydra Project
Written in Ruby, runs on Rails, requires Solr
Customize Blacklight for DLP
Collections
Integrate blacklight with MODS-based index
◦ Blacklight by default expects MARC fields
New functions and features
◦ Render thumbnail in result view
◦ Use collection website as the landing page
Style and layout
◦ Standard IU banner and footer
◦ Color, font, and window size
Future Improvements
Automatic update of Solr index
◦ Fedora repository communicates with the
Solr indexing program via JMS about item update
Include full-text content
◦ It is challenging to have full-text content and metadata in one index
◦ Optimize the indexing and search algorithms
◦ Search against full-text and use metadata as facets
Future Improvement (cont’d)
Add more collections
◦ Other collections from Fedora
◦ Non-Fedora DLP collections
◦ Archives of Institutional Memory
◦ IUScholarWorks Repository?
◦ IUPUI Digital Collections (ContentDM)?
Conduct usability evaluation
Explore integration w/ new Blacklight-based discovery layer for IUCAT
Variations on Video IMLS grant
◦ Hydra/Blacklight-based discovery on PBcore
Questions?
Beta: http://webapp1.dlib.indiana.edu/dcs/
Send comments to: diglib@indiana.edu
