Since the last post about Blacklight, we’ve been asked a lot of questions about Blacklight and its development in IU Libraries. Those of you who missed reading it might want to check here. This post will focus on some of the questions that we have been asked most frequently.
What sorts of changes will there be in the new IUCAT?
People involved in the development phase are working hard to insure that a new discovery interface not only retains the functionality of IUCAT currently available, but also delivers improved functionality.
Most next generation type catalogs have a simplified search box, which is easy and quick to use for users with a simple question. Blacklight provides a simple format for the basic search and facet structure for limiting searches.
The generic Blacklight interface is customized according to the library’s individual needs and specific environments. Here are some examples that adopt Blacklight’s basic format.
- University of Wisconsin – Madison
- Stanford University
- University of Virginia
- Johns Hopkins University
The new IUCAT will have a single search box for the basic search, and faceted searching on the left side will allow users to constrain searches by controlled vocabulary items. There will also be an advanced search screen for more focused searches. As the development is still in progress, your comments and ideas will be highly appreciated.
How do Apache Solr and Ruby on Rails work to index library resources?
Blacklight’s two fundamental technologies are the Solr search server and the Ruby on Rails web application framework. Developed by the Apache Lucene project, Apache Solr is used for indexing and searching records, while Ruby on Rails is used to create the front end. Here is a nice graphic representation of the Blacklight system.
Sadler, B. (2009). “Blacklight Infrastructure.” In Project Blacklight: a next generation library catalog at a first generation university. Library Hi Tech, 27(1), 57 – 67.
A java-based program SolrMARC reads, indexes, and exports library’s MARC records to Solr and custom Ruby scripts are used for non-MARC items to map document metadata to Solr. The Ruby on Rails application looks to the Solr server for its data, passes search queries, and formats search results.