Category Archives: OPAC

Digital BBC World Service radio archives

The BBC World Service Archive Prototype is a website that provides access to the huge digital archive of radio programs of the BBC World Service. Yves Raimond and Tristan Ferne describe in a concise article (PDF, 8 pages) how Semantic Web technologies, automation and crowdsourcing are used to annotate, correct and add metadata for search and navigation. Ed Summers has a blog post about this project, making a comment I wholeheartedly agree with: “… [I]t is the (implied) role of the archivist, as the professional responsible for working with developers to tune these algorithms, evaluating/gauging user contributions, and helping describe the content themselves that excites me the most about this work.” I think this is not only a possible future role for archivists but also for librarians, especially catalogers and metadata specialists working with digital collections.


Topic maps and ILS

“Topic maps and the ILS: an undelivered promise” (Library Hi Tech, 26 (2008), 1, pp. 12 – 18) – a great, accessible way for librarians to explore possible applications for topic maps in a library setting. The authors are Suellen Stringer Hye and Edward Iglesias (who wrote some thoughtful comments on “Data, not records” on the ITIG ACRL-NEC blog).

The main merits of the paper are the demonstration of potential use cases of topic maps in libraries and the comparison of topic maps to discovery applications. Examining the assets and advantages that distinguish topic maps from these tools, the authors point to the power of topic maps: through associations, “each item or topic carries with it information about its context”, for example.

As mentioned in the paper, vendors of library software have not (yet), despite internal use of topic maps, included the technology in ILS development. Why not? What would it take for them to actively promote topic maps? And what about open source software? Of course this cuts both ways – there is no specific demand from libraries either. Maybe librarians need a clearer understanding of the benefits of topic maps compared to the fashionable discovery systems.

A discovery tool only goes so far, topic maps go further.

Associative index model

The paper “An associative index model for the results list based on Vannevar Bush’s selection concept” by Charles Cole, Charles-Antoine Julien and John E. Leide of McGill University, Montreal, which appears in the latest issue of Information Research, contends that algorithmically created methods of refining results lists in online catalogs are not well suited to meet the users’ information needs. The authors draw on Vannevar Bush (whose seminal text, “As we may think” (1945), is available here) and Charles Cutter to develop an associative index model.

Based on an understanding of cognitive processes during a search, the model establishes a second collocation set, triggered by the user’s associative thinking while perusing the first, system-derived results list. This second set is considered to better match the user’s actual information need. In my view it is only an externalization and formalization of thought processes at work in a more or less conscious way, including epistemological questions like, how do we look for information, how do we formulate a query, i.e. use natural language to reflect our information need, how do we process and organize the findings, how is association involved in search and selection.

Some questions remain open, for instance, why didn’t the authors revert to the FRBR user tasks instead of creating their own with slightly different meanings, or how would relevance feedback relate to their approach. I wonder what role topic maps could play in an associative retrieval tool – enabling users to identify subjects in their own words, i.e. from their thought associations, feeding improvements suggested by users back. A dynamic system getting “smarter” through user input which complements computational algorithms.

Source-sensitive facet?

To follow up on the last post, picking up Ranganathan’s law “Save the time of the reader”, one way of saving the time of the reader is to refine faceted search and browsing. The bigger the indexed corpus (and that would be the case when including abstracts, TOCs, indexes etc.), the more hits a query will yield, and there will potentially be a higher number of irrelevant results. It is also getting more difficult for the user to see why a certain result is returned if the search term doesn’t show up in the readily identifiable fields like title, author or subject heading. We don’t considerably save the user’s time if they have to wade through pages of search results, just because we don’t want them to miss a book they might find useful that came up due to the search term in the back-of-the-book index.

The discovery layers that more and more replace traditional library OPACs offer faceting of results by various criteria (language, format, year of publication etc.). How about introducing what I would call a “source-sensitive facet”? This facet will show where the search term occurs, whether it’s in the metadata, the subject heading(s), or in supplementary material such as TOCs, abstracts or indexes. Scottsdale Public Library has such a facet in place:

Their “Search found in” facet is apparently generated from the metadata proper, but you could also imagine indicating the location (e.g. an electronic document associated with a given item) where the search term was found: “Search found in TOC / abstract / index “. The document in question has to be typed for the system to recognize which type (TOC, abstract, index) it belongs to and display this information. Such a facet would make the results more transparent, since some users are confused about where their search term occurs in the data and why a specific item turns up in the list of results. Those interested enough to find out will have a tool at hand.