Last June, Gary Marchionini hosted a workshop on Information Seeking Support Systems, which I was privileged to attend. The workshop brought together researchers from industry and academia for two days of stimulating discussion about systems, models of information seeking, and evaluation. One of the results of the workshop was a Special Issue of IEEE Computer that Gary and Ryen White edited.

We published a position paper at the workshop, and followed up with an article for the special issue, out today. We look broadly at collaboration in information seeking, including some motivating scenarios of use, a model of the design space, and a short discussion of roles.

This is the same issue that Daniel mentions in his post.

Update: IEEE says they are undergoing a “software changeover”, and expect the TOC to be up early next week.

Update 2: The online copy is now available from IEEE and on our web site.

The upcoming CHI 2009 conference will be the 20th consecutive CHI I have attended.  My first CHI was in 1990, where I discovered the field of Human-Computer interaction, a term I had not come across in my undergraduate education as an electrical engineer.

One of the most memorable experiences at CHI was a tutorial on “Hypertext” taught by Bob Glushko. The concept was fascinating, and Bob was a good teacher. He did, however, say one thing that struck me as a challenge. He talked about nodes, links, and anchors, and said that to build hypertext systems, you needed a “graphics display and a mouse.” At the time, I was working at UCLA in the Office of Academic Computing (OAC) as a consultant and programmer. UCLA was an IBM shop, and we had a bunch of 24×80 green-on-black IBM 3178 (and equivalent) terminals. No mouse, no windows, no graphics. But we had something called ISPF, which allowed the program to read the cursor location on the screen, and VSAM with which I built a crude inverted index of our local online help.

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The ACM Digital Libary is an invaluable research resource for a wide range of academic disciplines. I would find it hard to write papers without it. Invaluable as it is, it could be more valuable still by supporting not just use by its subscribers, but also research by its subscribers.

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Max Wilson recently commented on an article by Zhang et al on time series analysis of search logs.  (Thanks to Daniel for the web link.) This is a topic I’ve been interested in for a while, in particular for finding evidence of exploratory search in the logs.  Max notes that the average session length is just under three interactions, and concludes that this really amounts to a single query/selection interaction. If that’s so, then the average behavior  characterized in the Zhang paper is not in fact exploratory.

I was looking forward to reading the paper, but my excitement was short-lived:

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Meredith Ringel Morris, Jeremy Pickens and I are editing a Special Issue of Information Processing & Management on Collaborative Information Seeking. Our goal is to bring together papers that describe explicit (intentional) collaboration during various aspects of online information seeking. In contract to recommendation or collaborative filtering work, we are looking for work that describes small groups of people working toward a common goal.

The deadline for submission is May 8, 2009.

More details on the call are available here.

Most popular web search engines are optimized for precision—getting that useful document in the in the top five or ten hits so that the user doesn’t have to page through the results to find it. This works well for known-item search (finding an address of a restaurant, a birthday of a movie star, etc.) and for searches that rely on combinations of keywords.

But some kinds of information needs don’t fit that pattern well. Sometimes the information being sought is spread over multiple documents, sometimes people need to find multiple instances of documents that match some query to compare or contrast them, etc. The task becomes more recall- rather than precision-oriented. Furthermore, these searches may be repeated over time, as the user finds information that causes the information need to change. Medical information seeking is one obvious such example. Are there others?

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