Curating content and form

Reading Cindy Romaine’s article “The Consumer Electronics Show – insights for SLA” on SLA’s Future Ready 365, the phrase that stands out for me is: “Data devices, or form factors, were very elegant and restrained. It seemed that there was an effort not to overwhelm the consumer with technical options, but to simplify and curate”.

Through collection management and selection, librarians curate content for their patrons. But just as a museum curator not only selects artworks for an exhibition but also takes care of showcasing them (by painting the wall where a painting is hung, for example), so librarians should not only focus on curating content but also curate form.

In my view, the presentation of our well-curated content should be as “elegant and restrained” in design as the devices Cindy talks about. No doubt our discovery systems offer a wealth of technical options (navigating, faceting, word/tag cloud etc.), but librarians should curate these options and where possible simplify so as not to try to do too much and overwhelm the users (who might just – unconsciously – shy away from a library catalog they don’t understand as intuitively as their electronic devices).

The simplicity and functionality of handhelds, cell phones or tablets shape user experience just as much as the web sites they visit, so aspects like these have to be factored in when thinking about catalog interfaces, and curation is as important for form as for content.

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.