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ONLINE SEARCHER: Information Discovery, Technology, Strategies

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Search Tips From a Seasoned Searcher
Volume 42, Number 1 - January/February 2018


Search simplicity often works better than search complex ity. We certainly like to load up our search terminology. Rather than curiosity rover hazard avoidance, we want curiosity rover hazard avoidance challenges stuck in ditch . The simple rule of a Boolean AND search is that every word you add to a search diminishes the return by screening out anything that doesn’t have all your search words. Thus, an article titled “Hazard Avoidance Issues in the Curiosity Rover” won’t appear in in this beefed-up search, since it uses the word “issues” in stead of “challenges” and says nothing about a ditch. Automatic synonomization used by major web search engines may equate “issues” and “challenges,” but library subscription databases will not.

My general rule of thumb is to start with the simplest search that still encompasses my problem. If the results are too broad, add a word or two. The real place to narrow results is on the results page. Thus, I do much less screening through an initial search and much more after I’ve had a look at my search results. In this way, I avoid overlooking some potentially good results, and I can still do a lot of result elimination intelligently in further stages after my initial search.


Be prepared to do more than one search, with more than one phase in each search you do. Google, for all its benefits, has taught users not to go beyond the results from an initial search. It is the conceit of Google that its search engine has a brain, and its algorithms are like magic. Why would you fiddle with search results when the amazing Google has delivered you the best results already, no muss, no fuss?

But search isn’t smart, at least not yet. It’s baby talk, like rover curiosity hazard avoidance , and it’s word-matching. Strangely, a lot of searchers seem to believe they are talking to Google as if it were an intelligent mind. They ask questions, fail to notice that extra words are screening out results, and generally have few clues as to how to man age search terminology to optimize results. But Google has no mind and doesn’t understand your questions. It matches words and uses opaque algorithms to determine relevance.

Here’s another basic rule of thumb: Your first result set from a search in most any database is going to be ugly. If you have a common search engine such as Google or Google Scholar, there is not much you can do about that except to try another search with different words. But more sophisticated databases give you a lot of options to turn an ugly set of results into something more elegant and relevant.

Faceting your search process by using limiters and other useful tools is both a skill and an art. Balking at making the effort to work with results is short-sighted and counterproductive. Unless you get 100 or fewer highly relevant results on the first shot (a rarity), you are going to have to work with your citations to cut down their quantity and hone their relevance. Getting 10,000 results constitutes bad news. Good use of the tools can get you down to under 100 in fairly short order.

If you have tried faceting and nothing is working, it’s not a disaster to have to start over with new search terms and then facet your results. This doesn’t mean the database was too complex and Google is better. Complexity in database searching, as long as the database provider has done its best to make procedures intuitive, is actually a good thing.


Here’s my final tip: Search is not a burden, it’s an adventure. We tend to stress out when we don’t find what we need right away. The Google-type mantra “Search is easy” tells a lot of people that when search becomes difficult, they are doing something wrong. If the stakes are high—as in, “My paper is due tomorrow at 1:00 p.m.”—delay and frustration are absolutely not wanted.

A change of perspective can work wonders. First, there is no reason to believe that search is going to be simple. You are an intelligent human being trying to communicate with non-human software. It’s like trying to explain something complicated to your dog. Second, most searches succeed if you are persistent and able to develop the skills to work the database. Third, the quest is fun. Yes, it is. We humans are unceasingly curious. We are problem-solvers. And there is no greater satisfaction than taking on a challenge and wrestling it to a solution. That is the adventure of search.


There may come a day when search is so intuitive, we will have little to teach prospective searchers. This is not that time. Search is still difficult, even when the “Search is easy” mantra has searchers believing there is not much to learn, which is a tremendously counterproductive idea. If people do not believe search is difficult, they have no motivation to learn how to do it better. Disabusing searchers of the notion that search engines are smart enough to deliver what they want when they want it is a key task for educators.

This seasoned searcher believes that it is essential to cre ate as many other sophisticated searchers as possible. The larger our databases, the more people need the skill to optimize their searches, creating near-exact matches between their mental concepts and their results. This isn’t an option, not as long as our search engines continue to operate at a baby-talk level.

Search is a skill and an art. It requires the same kind of expertise development demanded of anything else in the information world. We live in an amazingly complex, knowl edge-based world that needs mad skills to master. Presenting developing searchers with the best options to harness search and make it actually work has to be a key task of education. Anything less is a failure to educate.

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William Badke is associate librarian at Trinity Western University and the author of Research Strategies: Finding Your Way Through the Information Fog, 6th edition (, 2017).


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