Check out this article at the Concordia University Library News Blog: Goodbye, BearHunt. BearHunt is (soon to be ‘was’) their federated search system. They didn’t like it and they’re not shy about telling you how much they didn’t like it. I’ve never seen so many negative comments about a federated search solution. I counted ten complaints. I’ve broken them out in my reproduction of Concordia’s article here:

Goodbye, BearHunt

QuickSearch via BearHunt will no longer be available beginning March 1st. There are a number of reasons that the library chose to discontinue this federated search service. Most important, as everyone is tightening their belts,

BearHunt came at a substantial cost while offering no new content.

Also important,

usage was low compared to cost.

When it first became available, we were excited to try a federated search, but along with other CLIC libraries and the rest of the library world,

we’ve realized that the technology needed to support the idea isn’t quite there yet.

The relevancy rankings don’t seem to work correctly or consistently,

links were frequently broken,

searches executed slowly, and

the interface left a lot to be desired.

We also felt

there was a possibility that it was misleading searchers to think they were searching ‘everything’, while in fact there are a number of both purchased and freely available resources that aren’t included in a BearHunt search.

Also,

the search is not complete in that it stops at a predetermined time interval instead of continuing until all searches have had a chance to complete.

In the end,

BearHunt and federated search as it now exists seems at odds with our mission to teach academic research skills tailored to specific situations and inquiries, using the full breadth of our resources.

We will look forward to new federated search products with anticipation, especially if they meet our criteria of completeness and have added-value in their presentation.

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There’s lots of conversation in the library world about the limitations of federated search. You’ve heard them all - speed (or lack thereof), limitations arising from not searching the native sources directly, challenges to relevance ranking, etc. etc. etc. In the enterprise, federated search challenges take on added dimensions.

InformationWeek recently published an article, “InformationWeek Analytics Research: Federated Search.” (You may need to register to read it.) The article names three obstacles to wider acceptance of federated search in the enterprise:

The problem isn’t technology. It’s the three Ps that plague many an IT initiative: politics, privacy, and perception.

Here’s just one example of a thorny issue that’s not technical: E-mail. Why not make e-mail searchable in the enterprise?

We understand the fear: E-mail search is one of the most politically charged areas CIOs will encounter. Almost every organization’s official policy is that e-mail is owned by the company and employees have no expectation of privacy, yet almost every survey respondent limited e-mail search to the individual level, with only 3% allowing search within departments or teams.

There’s good food for thought in this article. Searching enterprise data can be very different from searching journal articles.

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How do you make relevance ranking better? Lukas Koster argues, at the CommonPlace.net blog that:

You want the results that are the most relevant for your search, with your specific objectives, at that specific point in time time, for your specific circumstances, and you want them immediately.

The concept isn’t new; use as much information as possible about users and their search experience to target more relevant results. That’s search personalization. What I appreciate about this article is that it provides a nice introduction to the various aspects of personalization.

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Discovery services have begun to spring up. This article is my attempt to catalog and characterize them. Consider this article to be an introduction that sets the stage for future analysis articles.

What is a discovery service?

A discovery service is a search interface to pre-indexed meta data and/or full text documents. Discovery services differ from federated search applications in that discovery services don’t search live sources. By searching pre-indexed data discovery services return search results very quickly. Discovery services are touted as an evolution beyond federated search and in some ways they are. Some discovery services either provide integration with federated search or provide an API for others to do the integration. I believe that hybrid “federated discovery” services are likely to prevail over pure discovery services and I will dedicate an article to them.

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Daniel Tunkelang, Endeca co-founder and Chief Scientist, wrote a guest article articulating a particular problem with federated search. In the article, Daniel wrote:

But federation is no panacea, at least as it is implemented today. A federated search application brokers a query, sending it to multiple search providers (i.e., the search interfaces to a variety of content repositories), whose results it then attempts to assemble into a coherent whole. Unfortunately, since most search providers provide little more than the top-ranked result pages, federated search applications are largely reduced to assembling a unified ranking of those disparate result pages.

This functionality is significant, and I do not mean to dismiss it. But it is not enough. In particular, this approach to federation necessarily assumes a lowest common denominator of search functionality–a consequence of the requirement to evenhandedly broker among a variety of search applications that vary in the richness of their APIs.

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[ Editor's Note: This is a guest article by Daniel Tunkelang. (See his bio below.) Daniel is passionate about designing search systems that improve users' experience with information retrieval. This passion comes across very strongly in his book about faceted search, which I recently reviewed.

This article addresses a limitation with federated search that could be removed if content sources provided specific metadata to federated search engines to improve relevance ranking. Good food for thought. ]

Daniel Tunkelang is the Chief Scientist and a co-founder of Endeca, a leading vendor of search technology. Before joining Endeca’s founding team, he worked at the IBM T. J. Watson Research Center and AT&T Bell Labs. Daniel pioneered the annual workshops on human-computer information retrieval and recently published a book on faceted search. He blogs at The Noisy Channel.

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The SLA 2009 Annual Conference is fast approaching. Blog sponsor Deep Web Technologies will have a booth at the conference. If you’re going to be attending they’d welcome your visit. Abe Lederman, founder and President of Deep Web Technologies, will be a presenter. His talk and contributed paper are titled “Science Research: Journey to Ten Thousand Sources.” The talk will be on Monday (June 15) from 3:30 to 5:00 as part of the “Adapt, Leverage and Communicate (Part I)” contributed paper session.

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Yesterday I wrote “Beyond federated search?” where I raised the concern about using services that provide indexed content as a way to bypass federated search and its associated challenges.

Jonathan Rochkind left two thoughtful comments which I’d like to respond to.

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I think it’s safe to say that, given the choice between searching a content source in real time vs. searching it from an index, we’d all opt for searching the index. This assumes, of course, the index is as current as the content that might be federated. I’ll be the first to admit that federated search is a necessary evil. But, necessary it is. I’ve been hearing people talk about life beyond federated search and I just don’t get it. Until every single content provider makes the full-text of all of their documents that can be federated available for harvesting and indexing, federated search isn’t going away.

Serials Solutions’ new Summon Unified Discovery Service is touted as going beyond federated search. The promotional video boasts how there are no connectors, no inconsistent metadata, and no waiting for results to come back. This is all well and good but how do you deal with quality content sources that are not available through the service?

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[ Editor's note: Dr. Walter Warnick, Director of the Office of Scientific and Technical Information (OSTI) of the U.S. Department of Energy, is the author of this article. I've had the pleasure of working with Dr. Warnick for over six years in various capacities. Dr. Warnick is extremely passionate about the critical role of federated search in furthering OSTI's mission of making high quality scientific and technical information available to researchers and to the American people. It was Dr. Warnick who pioneered the use of federated search in the Federal government. I consider Dr. Warnick to be a luminary in the industry and will recognize him as such in an upcoming interview.

By way of disclosure, I consult for OSTI and for Deep Web Technologies (DWT). DWT sponsors this blog and powers the search behind a number of OSTI’s federated search applications.

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