Information Trapping and Information Traps

There are information hunters that have only one answer in mind and will torture the databases they interrogate until the correct response comes out. Then there are information farmers who are more interested in seeding potential hotbeds of knowledge through social nets and communities of practice. Then there are information scavengers or what are more diplomatically termed information "trappers."

Trappers are searchers who have seen enough search results to build their queries in advance of probable outcomes -- especially likely scenarios that pack a passing storm of relatable events. A common trigger for such events could be hirings and firings in anticipation of a job search. Another could be more environmentally-charged --say that newly proposed wind farm, toll hike, or carbon tax.

The eruptions of protest over a project approval, bid denial, or decision in the balance is bound to attract two outcomes:

1. News -- defined as consequences (awards, penalties), or, binding changes to policies and the fact base (selectively drawn from each side of the debate)

2. Conjecture -- the opinions of partisan supporters and opponents (typically in much greater page volumes than actual news)

Properly calibrated an information trap can tell you which side is winning the larger PR war -- newscycle by newscycle.

Tara Calishain dedicated her most recent in a series of search guides to setting traps. Her rationale is that you don't have to boil the ocean with ad hoc queries. Instead you can use RSS feeds and page alerts to reduce the fire-hose effects of voluminous results. You get targeted updates. You log off on top of what could otherwise feel like a bottomless situation. Best of all it's prompted by changes to your areas of interest -- not the subjects themselves which threaten to re-introduce you to already familiar themes and topics.

In the past we referred to this as the standing query. Lee Eichelberger, a usability guru with search engine vendor FAST deemed them Taxonomies of Use in this past winter's piece on Information Supply/Demand patterns and the growing requirements for enterprise Knowledge Planners. Whatever your terminology the major value add of setting traps is that they are triggered by events. But if you extend your query builds into the full richness of the aggregate, the wider patterns in your event stream emerge:

* Complaints are up!
* Viruses are leveling off!!
* My momentous press release went out last Tuesday -- yawn!!!

Calishain's effort should be lauded as one of the first efforts to seriously chronicle the notion of news flow as it relates to search returns. She provides serious guidance on which trap to set based on prior volumes of coverage and expected rates of change.

The trap here is that the actual use cases of actual trappers are buried under the details of the products in the toolbox -- the feature function sets of email services, content aggregators, and search engines. Many of these capabilities are susceptible to change by the time any reader would commit these details to their own trapping efforts -- especially the free utilities that most readers would try before investing in ore than the book. It's a time-tested recipe for selling updated editions of technology guides.

To Calishain's credit her task sequencing and engaging style enables her to cover far more ground than any web-based tutorial. It's certainly more hands-on and credible that what any vendor could ghost write through a technology press or research group. That said, it would be even more useful for students and practitioners alike to focus next time on use cases -- the actual trappings.