KM in the Jerkplace: Episode Two -- Knowledge Engineering for Solitary Scrum Masters

(c) http://3.bp.blogspot.com/

Installment Summary: The Big Four knowledge survivalist jumps into the awaiting arms of the engineering camp for a once mighty developer of media software – back when hardware mattered. At first the opportunity is virgin territory. This inviting place to plant the knowledge flag is signified by efforts to source and build a search capability for leveraging the company’s collective assets. The initial optimism is however tempered by factional infighting and an unwillingness to fly those engineering colors under the SAME flag.

The Factory Gates Open for Knowledge Engineering

A week before I was to ship out as a SharePoint business ninja within IT, I hitched onto a passing knowledge raft. This water-logged trial balloon was powered by the knowledge-seeking curiosities of the engineering arm of Keen Core Technology – arms dealer to Hollywood, TV, and recording industries, and now under siege by an unceasing array of disruptor insurgencies from all sides of the media production spectrum.

While I had worked along-side IT and engineers with MBAs (a.k.a. “management consultants”) I had never been subsumed into the belly of the engine room: that is IT itself. I learned software-making as a repeatable cycle in need of documentation as-in coding the coders. I learned about daily stand-ups as the perfect antidote for task-drenched programmers who would rather be writing code than getting sucked into meetings.

My mission at Keen Core was to classify the wikis, channel the documentation stream, and socialize the release cycle of the half-dozen or so product development teams. Ultimately this meant distilling all these outputs into a single automated helping of digestible knowledge called “search.” The fact that there was no enterprise-wide answer to the perennial how-do-we-know-what-we-know question meant two things to the engineering crew of Keen Core:

1. Conceptual – how do we boil this ocean of applications, file-shares, lapsed repositories, and group-based collaborations from Outlook to Google Docs?
2. Practical – once boiled, how do we care and feed this resource so we can retreat to our safety zones in the comfort of knowing we can test our forward-leaning hunches against our collective history?

The Knowledge Safety Net

From a theoretical perspective the wish list that brought me to Keen Core began and ended with the same staggering and sober realization: we can scale the production of code but we don’t have a clue how to trap, catalog, and ultimately leverage the by-products of that effort.

This overwhelming sense of an organization’s inability to get out of its own way is not well-served by a top-down inventory of all assets – whether they live in the U.S. Patent Office or under “the digital landfill” as AIIM's John Mancini would say.  Rather than over-analyze the backlog of dumpster-grade documents, we looked to establish the safety net – not the uber knowledge archive.

There was nothing random to this sampling. Domain experts come out of the wood work – reluctantly sometimes because they’re often “heads down” …

• On some failure-is-not-an-option mission, or
• Closing in on some new shortcut to faster, better, cheaper.

These are not the sycophants of social media in search of the likability badging trophy. 

These are the folks who build stuff. They might not communicate effectively and their managerial skills lapsed long ago – if they ever had them. They are socially speaking apolitical, meaning they are drawn to fixing problems, not towards handling them. They are by-and-large drawn from the ranks of engineering and they are my brilliant, argumentative, recalcitrant, misunderstood people.

These are the ones who emerge when the call goes out for who-knows-how-stuff-works. And like their own circles, the documentation they travel in lands off the documentation radar. It lives on the outskirts of any centralized repository that confers authority, explains connections, or unpacks the experience that inspired it. In the case of the Keen Core safety net it was little more than providing a link to an obscure server I might or might not find password accessible. But after a series of non-threatening prods I had my unofficial off-the-map collection of references that the engineering teams swear by.

Not the sanitized intranet they were used to swearing at.

The Bake-off

The legendary chef Julia Child once said, “Always start out with a larger pot than what you think you need.” She might as well have been describing the process for picking an enterprise search engine. This proof-of-concept or PoC is your due diligence for matching internal priorities and selection criteria to your bake-off results. PoCs demand an improbable mix of reference able work product – no matter where it comes from, the application particulars, or the sub par referencing used to catalog the electronic version of what lives inside organizational roles and responsibilities.

Once I had my vetted safety net, I was clear to map them to the safe harbor of the search interface where memories get tested, experiments are run, and explanations are concocted.  That mapping included a healthy respect for the mismatch between Googling for cat videos that stick to our social billboards and researching a backlog of databases that live behind a corporate firewall. A PoC was undertaken to reduce the vast, uncharted wilderness of Keen Core to a single search box and a choice of search vendors – hence the “bake-off” that played out against the following design choices:

#1 – Fact versus Conceptual Search: Most business problems are not reducible to the distance of the closest pizzeria with the highest reputation ranking. In other words the answer is neither immediate nor obvious. It’s not persuasive on its own but needs the back-story to connect its relevance to the problem at-hand. That connection can only be provided by the searcher – not the search engine. The conceptual search idea was welcome by my colleagues as they were well-acquainted with the status and responsibilities of domain-expert-as-content-curator.

#2 – Single Answers versus Iterative: Because of their research-focused nature, most business or enterprise search problems are not only conceptual but iterative. They are greatly influenced by changes in time frame, authorship, formatting, narrative style, and context – the reason the artifact exists in the first place. Enterprise search results defy definitive or conclusive answers. They’re conversational – not just among peers but with the search interface itself which guides the searcher with:

1. Related events, 
2. People, 
3. Locations, and 
4. Organizations that suggest …
5. Further probing, 
6. Competing explanations, or even …
7. Complete redirections of our original assumptions.

This relatedness was realized in the proof of concept. Human-mediated tagging was neither doable nor desirable but the prospective search technologies proved up to the task for grouping these relations as search facets.

#3 – Search versus Source Dependent: The key to building our knowledge safety net is not so much keyword searching as enterprise sourcing: The ability not just to crawl volumes of pages, folders, and files but to evidence why anyone bothered to do so. Search scoping is essential because it brings the sense-making role of any single artifact apparent to colleagues with otherwise no shared experience beyond a common holiday calendar and pay cycle. Sourcing logic reinforces the cohesive logic of coordination across business lines and supporting functions:

1. Want to know what the customer sees before it’s out on your website? Search on marketing. 
2. Want to understand our products better? Search on training. 
3. Visual learner? Precede to training videos, etc. 
4. The more technical explanation? Go to the core requirements hammered out by account managers and the engineers who design to them.

Everyone at Keen Core understood the different lenses for sifting through the same content. The challenge was that only engineering had a seat at the bake-off table.

Enterprise Assets or Liabilities?

The good news is that each of these ingredients was factored into an enterprise search proof of concept for the engineering crew at Keen Core. The correct sources were indexed and configured to a search-driven interface reflecting both the nature of the index and the information-seeking goals of the searcher. Better still I got to run a true side-by-side comparison between two enterprise search vendors (Coveo and Google). The thinking here: My colleagues could base their tool of choice on their actual problem-solving.

The bad news is that Keen Core’s enterprise resembled a potluck more than a catered sit-down. The number of place settings changed with who wanted a seat at the table. The unsettled seating arrangements made it hard to move forward without revisiting some tired assumptions like:

• The Google Slam Dunk: Hey, wipe that Google web smirk off your enterprise requirements for Google Search Appliance. We’re talking two different engines here!
• The How Big-is-Our-Data Routine? What constitutes a fair test sample when a vendor solution crawls across diverse operating systems, repositories, and legacy apps (with licenses no one bothered to renew)?  
  
• The How-Open-is-Open Question? What's bothering your colleagues about access to resources? What's the important stuff we can get access to if we need it?  What are the content bottlenecks that hinder a silo-bound organization?

Conclusion: At every milestone selecting the right vendor was resistant to simple risk-to-benefit reductions. Multiple trade-offs were the norm. So were the dug-in heels of competing vendor camps. All of these larger lessons were lost to the conflicting agendas of poker-faced stakeholders – regardless of the actual bake-off winner.

Next week: The bake-off verdict is clouded by a crash diet spending plan courtesy of a stock delisting and a CEO whose blunt leadership style distances him from all non-depreciable costs -- including the company’s ingrained know-how on the building of its products.

***

The blog series KM in the Jerkplace is a work of fiction. Names, characters, businesses, places, events and incidents are either the products of the author’s imagination or used in a fictitious manner. Any resemblance to actual persons, living or dead, or actual events is purely coincidental.

LinkedIn First, LinkedOut Later...

To a metadata freak, LinkedIn is a marvel of information science. It is the botanical garden of social media.

Every germinating seed is dutifully watered in flower beds tended by a volunteer army of self-selected gardeners. The blossom worth budding here is that the attentiveness is anchored to the premise that our professional fortunes depend on this.

The LinkedIn premise is a massive database of self-administered professional life narratives. Access is determined by a network of click-happy connections: show you mine if you show me yours (both the resumes and the contacts).

The database gets regular feedings and weedings because -- hey -- those are my bowling trophies and and inflationary job titles and biopic documentaries I put on my reality series reward card program. Psst ... got any seed money?

What I'm unpacking here through unlicensed metaphor is a database of resumes. The splendor of the architecture is that the profile templates are self-organizing. There are no semantic web quibbles over taxonomies versus folksonomies, what vocabulary is worth controlling and which tag clouds deserve to float above the fog. In doing so, LinkedIn has achieved organic adherence to the age-old riddle:

How do I describe my uniqueness in the least invasive and most universal way possible?

That vessel is the cross-fertilization of the knowledge garden we researchers, sales animals, and job-seekers can all cultivate, horse-trade, or hunt down online through the sprinkler system known as LinkedIn's "advanced search features."

I did a session on this for the career options folks at my Alma mater of Hampshire College last month. It was fascinating to map the academic disciplines signified by each of the colleges schools to the requisite job skills, career paths, and institutional dimensions reverberating in the professional odysseys of Hampshire grads.

Then just last week I get pinged at work by Jon Lee, a Hampshire cohort from a 1.5 separation degree of overlapping concentric social circles circa 1980-84. Who better than a former Hampster and current job-seeker to put that ivory-coated knowledge harvest to the test?

Jon writes:

So, anyway, I want to harvest some of these connections. At first I thought I'd contact the person I knew, tell them who I was looking for and ask them to search the name and find the 2nd degree connection. A little awkward and time consuming (for the person I'm asking the favor). Yeah, so then I see the "Get Introduced Through A Connection" link. I choose my connection, then:



He continues...

My question is this... What happens, how does this work?

I hit send, a message goes to you. Do you only see my note to you - or the message to X (Leslie B. in this example) as well? And what about the person you know, who knows Leslie? How is that connection made? Automatically - or do you have to find the connection for me? Do they see my message to you, my message to Leslie?

The hypothetical scenarios go on for a few more paragraphs before the logic is tortured right out of the motivation for getting to the actual conversation stages -- the linking out phase of the process. I appreciate these questions because they underscore the associative clunk factor of shuffling through an overloaded circuit of lateral connectors.

The community spirit of pay-it-forward reciprocity might work for random acts of kindness. But maybe not so much for calculating and indiscriminate emails -- especially from people we know more for their degree of separation than we do about them. Period.

The artifice of the social media back-scratch points to the exit ramp or the link-out. This is the realization that as gorgeous as that well-groomed garden is, all the growth happens within the narrow confines of Linkedin.com. It is a walled in garden. That's why a thousand Facebook weeds makes more advertising perfume than the most painstaking bouquet of freshly cut resumes at LinkedIn.

You need to step on a few weeds, maybe even some poisonous ones before any meaningful conversations can happen. That's where a nose for research meets an eye for opportunity and an ear for discussion. That kind of growth can only happen in soils and climates where the greatest variety of vegetation takes root.

If I didn't answer your question, Jon, that may be because six years and 750 connections later, I still haven't plunked down $24.99 a month to find the answers.

LinkedIn First, LinkedOut Later...

To a metadata freak, LinkedIn is a marvel of information science. It is the botanical garden of social media.

Every germinating seed is dutifully watered in flower beds tended by a volunteer army of self-selected gardeners. The blossom worth budding here is that the attentiveness is anchored to the premise that our professional fortunes depend on this.

The LinkedIn premise is a massive database of self-administered professional life narratives. Access is determined by a network of click-happy connections: show you mine if you show me yours (both the resumes and the contacts).

The database gets regular feedings and weedings because -- hey -- those are my bowling trophies and and inflationary job titles and biopic documentaries I put on my reality series reward card program. Psst ... got any seed money?

What I'm unpacking here through unlicensed metaphor is a database of resumes. The splendor of the architecture is that the profile templates are self-organizing. There are no semantic web quibbles over taxonomies versus folksonomies, what vocabulary is worth controlling and which tag clouds deserve to float above the fog. In doing so, LinkedIn has achieved organic adherence to the age-old riddle:

How do I describe my uniqueness in the least invasive and most universal way possible?

That vessel is the cross-fertilization of the knowledge garden we researchers, sales animals, and job-seekers can all cultivate, horse-trade, or hunt down online through the sprinkler system known as LinkedIn's "advanced search features."

I did a session on this for the career options folks at my Alma mater of Hampshire College last month. It was fascinating to map the academic disciplines signified by each of the colleges schools to the requisite job skills, career paths, and institutional dimensions reverberating in the professional odysseys of Hampshire grads.

Then just last week I get pinged at work by Jon Lee, a Hampshire cohort from a 1.5 separation degree of overlapping concentric social circles circa 1980-84. Who better than a former Hampster and current job-seeker to put that ivory-coated knowledge harvest to the test?

Jon writes:

So, anyway, I want to harvest some of these connections. At first I thought I'd contact the person I knew, tell them who I was looking for and ask them to search the name and find the 2nd degree connection. A little awkward and time consuming (for the person I'm asking the favor). Yeah, so then I see the "Get Introduced Through A Connection" link. I choose my connection, then:



He continues...

My question is this... What happens, how does this work?

I hit send, a message goes to you. Do you only see my note to you - or the message to X (Leslie B. in this example) as well? And what about the person you know, who knows Leslie? How is that connection made? Automatically - or do you have to find the connection for me? Do they see my message to you, my message to Leslie?

The hypothetical scenarios go on for a few more paragraphs before the logic is tortured right out of the motivation for getting to the actual conversation stages -- the linking out phase of the process. I appreciate these questions because they underscore the associative clunk factor of shuffling through an overloaded circuit of lateral connectors.

The community spirit of pay-it-forward reciprocity might work for random acts of kindness. But maybe not so much for calculating and indiscriminate emails -- especially from people we know more for their degree of separation than we do about them. Period.

The artifice of the social media back-scratch points to the exit ramp or the link-out. This is the realization that as gorgeous as that well-groomed garden is, all the growth happens within the narrow confines of Linkedin.com. It is a walled in garden. That's why a thousand Facebook weeds makes more advertising perfume than the most painstaking bouquet of freshly cut resumes at LinkedIn.

You need to step on a few weeds, maybe even some poisonous ones before any meaningful conversations can happen. That's where a nose for research meets an eye for opportunity and an ear for discussion. That kind of growth can only happen in soils and climates where the greatest variety of vegetation takes root.

If I didn't answer your question, Jon, that may be because six years and 750 connections later, I still haven't plunked down $24.99 a month to find the answers.

Investigation Entry

The cognitive psyches have weighed in and it's nearly unanimous -- a brain on wireless is one that's rewired. Our circuits are abuzz with new spongy cells burning neural pulses into the trendy new places brains like yours and mine are looking for action. We're as easy to find as the answers to our searches. That's because we're conversing freely and openly, punching our surfing sessions into Google-enabled keypads -- the MRI scoring each mental discharge.

Critics like Nicholas Carr argue that more neurons firing (or even faster processing) doesn't necessarily mean a brain capable of lucid thinking for sense-making or problem-solving in support of sound, evidence-based decisions:

"Dozens of studies by psychologists, neurobiologists, and educators point to the same conclusion: When we go online, we enter an environment that promotes cursory reading, hurried and distracted thinking, and superficial learning. Even as the Internet grants us easy access to vast amounts of information, it is turning us into shallower thinkers, literally changing the structure of our brain."

The more interesting question to me is not about brain shape or mental depth but the enfeebled analytical muscles of an unquestioning generation of digital natives. That's not to say Carr's cautionary polemic is an indictment of GenY. I'm sure for every would-be hedge fund trader there's a budding journalist willing to hold a day job too. But we've barely begun to assess the damage of coming of age in a world where:

* Capital (not English) is the universal language of the species

* First Amendment rights are surrendered with the wave of a coupon, and

* The healthy skepticism of an informed electorate is confused for the faltering missteps of a business model (that being the demise of newspapers and the cleansing power of public investigations)

Rather than lamenting the golden age of impeachable offenses it might be more productive to consider some of these recoverable assets if we taught investigation skills to home bound couch-surfers sniffing for cheese in their own white Google lab coats. Here are a few initial thoughts:

1) Paying for information doesn't necessarily mean a vendor or an identity thief owns your credit card. Another form of payment is attention. Short of subpoenaing a suspect's surfing sessions how does one capture that?

2) The web 2.0 world is a giant echo chamber when you're trying to be heard. But if you can tune your research ear you can better understand the motivations of your search targets and the social circles that they travel in.

3) With the advent of suggested search Google is now in the business of completing your thoughts for you -- or at least sketch them out early enough to reward their Ad Word buyers for their advertising dollars. Other than to follow the herd there is no useful purpose to keywording one's way through a Google-based investigation.

4) A stealth researcher doesn't file FOIA requests or hack into the hard drive of a person of interest. They can use frameworks like Oceans, Lakes, and Ponds to determine where to search and source conjugation in order to determine what to believe.

5) It's not just about the right approach. The right tool-set is essential for knowing what evidence passes the smell test and comes with the pattern-matching potential the researcher needs to press their case. Here's what Carr has to say about the random and undisciplined way that critical mental thought rolls out to sea in most search sessions:

The depth of our intelligence hinges on our ability to transfer information from working memory, the scratch pad of consciousness, to long-term memory, the mind’s filing system. When facts and experiences enter our long-term memory, we are able to weave them into the complex ideas that give richness to our thought. But the passage from working memory to long-term memory also forms a bottleneck in our brain. Whereas long-term memory has an almost unlimited capacity, working memory can hold only a relatively small amount of information at a time. And that short-term storage is fragile: A break in our attention can sweep its contents from our mind.

That buffer that Carr finds lacking in working memory is a reservoir of resilient research exhibits called an RSS reader. Consider the sound operation of one to be the price of investigation entry.

So that's the start of teaching Gen-Yers how to teach themselves at the Academy of Higher Skepticism. When those questions become the properties of digital natives, the immigrants will feel a whole lot better about turning over the messes of our creation. We'll also stop waxing nostalgically for the big three networks, the Sunday papers, and paid subscription media.

Investigation Entry

The cognitive psyches have weighed in and it's nearly unanimous -- a brain on wireless is one that's rewired. Our circuits are abuzz with new spongy cells burning neural pulses into the trendy new places brains like yours and mine are looking for action. We're as easy to find as the answers to our searches. That's because we're conversing freely and openly, punching our surfing sessions into Google-enabled keypads -- the MRI scoring each mental discharge.

Critics like Nicholas Carr argue that more neurons firing (or even faster processing) doesn't necessarily mean a brain capable of lucid thinking for sense-making or problem-solving in support of sound, evidence-based decisions:

"Dozens of studies by psychologists, neurobiologists, and educators point to the same conclusion: When we go online, we enter an environment that promotes cursory reading, hurried and distracted thinking, and superficial learning. Even as the Internet grants us easy access to vast amounts of information, it is turning us into shallower thinkers, literally changing the structure of our brain."

The more interesting question to me is not about brain shape or mental depth but the enfeebled analytical muscles of an unquestioning generation of digital natives. That's not to say Carr's cautionary polemic is an indictment of GenY. I'm sure for every would-be hedge fund trader there's a budding journalist willing to hold a day job too. But we've barely begun to assess the damage of coming of age in a world where:

* Capital (not English) is the universal language of the species

* First Amendment rights are surrendered with the wave of a coupon, and

* The healthy skepticism of an informed electorate is confused for the faltering missteps of a business model (that being the demise of newspapers and the cleansing power of public investigations)

Rather than lamenting the golden age of impeachable offenses it might be more productive to consider some of these recoverable assets if we taught investigation skills to home bound couch-surfers sniffing for cheese in their own white Google lab coats. Here are a few initial thoughts:

1) Paying for information doesn't necessarily mean a vendor or an identity thief owns your credit card. Another form of payment is attention. Short of subpoenaing a suspect's surfing sessions how does one capture that?

2) The web 2.0 world is a giant echo chamber when you're trying to be heard. But if you can tune your research ear you can better understand the motivations of your search targets and the social circles that they travel in.

3) With the advent of suggested search Google is now in the business of completing your thoughts for you -- or at least sketch them out early enough to reward their Ad Word buyers for their advertising dollars. Other than to follow the herd there is no useful purpose to keywording one's way through a Google-based investigation.

4) A stealth researcher doesn't file FOIA requests or hack into the hard drive of a person of interest. They can use frameworks like Oceans, Lakes, and Ponds to determine where to search and source conjugation in order to determine what to believe.

5) It's not just about the right approach. The right tool-set is essential for knowing what evidence passes the smell test and comes with the pattern-matching potential the researcher needs to press their case. Here's what Carr has to say about the random and undisciplined way that critical mental thought rolls out to sea in most search sessions:

The depth of our intelligence hinges on our ability to transfer information from working memory, the scratch pad of consciousness, to long-term memory, the mind’s filing system. When facts and experiences enter our long-term memory, we are able to weave them into the complex ideas that give richness to our thought. But the passage from working memory to long-term memory also forms a bottleneck in our brain. Whereas long-term memory has an almost unlimited capacity, working memory can hold only a relatively small amount of information at a time. And that short-term storage is fragile: A break in our attention can sweep its contents from our mind.

That buffer that Carr finds lacking in working memory is a reservoir of resilient research exhibits called an RSS reader. Consider the sound operation of one to be the price of investigation entry.

So that's the start of teaching Gen-Yers how to teach themselves at the Academy of Higher Skepticism. When those questions become the properties of digital natives, the immigrants will feel a whole lot better about turning over the messes of our creation. We'll also stop waxing nostalgically for the big three networks, the Sunday papers, and paid subscription media.

What's a Bad Question? Good Question.

You've heard it before -- especially in a public setting seeded with unfamiliar faces: "There are no stupid questions."

Mostly the moderator who says this is responding to a lack of feedback -- especially when the presentation they gave is either alien or controversial to at least some of the participants.

In all honesty the stupidity lies with the moderator for boxing themselves into an exchange-proof presentation. But if we were even more honest about the kinds of questions that drive search analysts and KM folks batty it's a misinformed question built on the premise of unfounded assertions, urban legends, and generalized assumptions that stretch the appropriateness of their fit too far.

For example it's entirely understandable that some rocket scientist raised on Google believes they could pepper their query with the names of propellants and launchers and then truncate on a few choice biological weapons. What's misinformed about that? Nothing if you're on the web. However if it's done on your firm's SharePoint server and rockets are not what you sell and maintain then you run into two walls right away:

1. Complex question +
2. Uncommon terms =
3. Dumb question

Of course the site admin who sees it is no likely point this out than the search tool itself. Can you imagine buying the Google appliance and for every "zero hit" set of search results the response is "Did you mean to search this on public Google?" The problem metaphorically is that Rocket Star is sticking to his guns by running an ocean-sized search request inside the information pond that is my intranet.

Here's a QA framework I developed that illustrates the response range in terms of the battles worth fighting (stay with the upper quadrants):


Short of remedial information literacy classes the best work-around is to focus on the use of one or two unique terms so that my user can see the lay of the Rocket land in my shop before plundering ahead with anything more esoteric or complex. I can also engineer a search outcome that breaks the question down in terms of the topic addressed. But that works best for blank, receptive brains -- not for domain experts.

Ultimately the best run around the no bad questions mindset is to connect people and dispense with relevancy scoring for documents. Once we're past that we can actually prove what a good question can be. But only by providing a sound answer and people deliver those better than PowerPoints.

What's a Bad Question? Good Question.

You've heard it before -- especially in a public setting seeded with unfamiliar faces: "There are no stupid questions."

Mostly the moderator who says this is responding to a lack of feedback -- especially when the presentation they gave is either alien or controversial to at least some of the participants.

In all honesty the stupidity lies with the moderator for boxing themselves into an exchange-proof presentation. But if we were even more honest about the kinds of questions that drive search analysts and KM folks batty it's a misinformed question built on the premise of unfounded assertions, urban legends, and generalized assumptions that stretch the appropriateness of their fit too far.

For example it's entirely understandable that some rocket scientist raised on Google believes they could pepper their query with the names of propellants and launchers and then truncate on a few choice biological weapons. What's misinformed about that? Nothing if you're on the web. However if it's done on your firm's SharePoint server and rockets are not what you sell and maintain then you run into two walls right away:

1. Complex question +
2. Uncommon terms =
3. Dumb question

Of course the site admin who sees it is no likely point this out than the search tool itself. Can you imagine buying the Google appliance and for every "zero hit" set of search results the response is "Did you mean to search this on public Google?" The problem metaphorically is that Rocket Star is sticking to his guns by running an ocean-sized search request inside the information pond that is my intranet.

Here's a QA framework I developed that illustrates the response range in terms of the battles worth fighting (stay with the upper quadrants):


Short of remedial information literacy classes the best work-around is to focus on the use of one or two unique terms so that my user can see the lay of the Rocket land in my shop before plundering ahead with anything more esoteric or complex. I can also engineer a search outcome that breaks the question down in terms of the topic addressed. But that works best for blank, receptive brains -- not for domain experts.

Ultimately the best run around the no bad questions mindset is to connect people and dispense with relevancy scoring for documents. Once we're past that we can actually prove what a good question can be. But only by providing a sound answer and people deliver those better than PowerPoints.

In Defense of Poor Searching

I recently did a trial run with an online distance learning university. The other auditioners were the other prospective teachers in the program -- each with their own expertise and curriculum for teaching it.

We all needed to post an introductory lecture and discussion question to the school's web server. The other instructors would then field the question and three days of required threadings would ensue.

I found the response to my own web investigations course materials instructive. The feedback was useful not so much for its originality as a confirmation that the same excuse for poor information management practices is a dead-ringer for the reluctance I face on a daily basis as a knowledge planner for a management consulting firm.

Here's the responding thread:

"The problem we have with that is out staff just between too many tasks to remember all the options. "

It's true that the multitude of search options can be a little intimidating to a tech-savvy workforce and absolutely petrifying to the average Googler with no support (both technical and managerial). The trick is to let each student seek out their natural fulfillment. They've already agreed to wonder outside their comfort zones in signing up for the course. It's my job to get them to drive the search car to where they want to be -- not to confuse them under the "search hood."

Each new tool and method needs to be about problem-solving with the problem being something they've experienced firsthand many times prior to taking the web investigations course. One way to keep their receptive heads open to so much new material is to get them tagging their important discoveries on del.icio.us. I find that by not expecting them to memorize particular sites it frees them up to retain more of the course material, and more importantly, problem-solve more effectively.

Just as important to what's retained is what's left out I stop short of assigning any books or texts in a course that cuts a very diverse technology profile: some are never offline -- some are challenged to send an email attachment. I teach to the problem and then introduce filtering approaches (syntax) and the word choices and ordering (semantics).

The search section concludes with each student creating their own CSE ("Custom Search Engine") using the Google Coop tools. It complements the framework of Ocean-Lake-Pond -- that the size of your data set is just as important as the query you formulate.

Talk about an overlooked search lesson.

In Defense of Poor Searching

I recently did a trial run with an online distance learning university. The other auditioners were the other prospective teachers in the program -- each with their own expertise and curriculum for teaching it.

We all needed to post an introductory lecture and discussion question to the school's web server. The other instructors would then field the question and three days of required threadings would ensue.

I found the response to my own web investigations course materials instructive. The feedback was useful not so much for its originality as a confirmation that the same excuse for poor information management practices is a dead-ringer for the reluctance I face on a daily basis as a knowledge planner for a management consulting firm.

Here's the responding thread:

"The problem we have with that is out staff just between too many tasks to remember all the options. "

It's true that the multitude of search options can be a little intimidating to a tech-savvy workforce and absolutely petrifying to the average Googler with no support (both technical and managerial). The trick is to let each student seek out their natural fulfillment. They've already agreed to wonder outside their comfort zones in signing up for the course. It's my job to get them to drive the search car to where they want to be -- not to confuse them under the "search hood."

Each new tool and method needs to be about problem-solving with the problem being something they've experienced firsthand many times prior to taking the web investigations course. One way to keep their receptive heads open to so much new material is to get them tagging their important discoveries on del.icio.us. I find that by not expecting them to memorize particular sites it frees them up to retain more of the course material, and more importantly, problem-solve more effectively.

Just as important to what's retained is what's left out I stop short of assigning any books or texts in a course that cuts a very diverse technology profile: some are never offline -- some are challenged to send an email attachment. I teach to the problem and then introduce filtering approaches (syntax) and the word choices and ordering (semantics).

The search section concludes with each student creating their own CSE ("Custom Search Engine") using the Google Coop tools. It complements the framework of Ocean-Lake-Pond -- that the size of your data set is just as important as the query you formulate.

Talk about an overlooked search lesson.

Use Case: RSS Readers as News Radars

Here's a current use case to track "events on the ground" through Feed Demon. There have been reported instances in the media recently of attempts to confuse or intimidate potential voters, particularly new or youth voters. College age voters are traditionally the most under-represented part of the electorate.

Whether it's due to cynicism or naivete a third more concrete factor (inexperience) makes this group prone to believing falsehoods and misleading statements aimed at creating doubt about their residential status. Ahem. So participation in their democracy will jeopardize their financial aid or even come back to haunt their parents during next year's tax season. What could be more American than not voting?

One way to monitor attempts at voter suppression around college campuses is to use a broadly descriptive search statement on Google News:

location:nh college students registration election

You'll find a piece of syntax snuck in here. It helps us focus exclusively on content sources on Google News originating from the Granite State. New Hampshire is my location of choice as the nearest swing state to me with area colleges signifying the swingiest of voting blocs.

You'll also note that the semantics of this search statement are not in anyway prejudicial or skewed towards a certain outcome. Any attempt to tune this search at the outset would overly constrain the result set (n=109) as of yesterday's test run. In other words a more effective content analysis occurs by introducing results-based logic once the feed appears in Feed Demon.

That's where you can construct "Watches" to pull instances of terms like:

* suppression
* fraud
* misleading
* confusion, etc.

...from the New Hampshire tracking folder where these hits reside.

Don't forget to sample several of the more questionable hits. They will acquaint you with terms you hadn't considered or steer you away from outcomes that are clearly off-the-mark from your search objectives.

The second stage of tweaking your RSS reader as news radar is to harvest the feeds sprouting from the sources included in your search results. Gathering up the list is easier than confirming each source's deployment or policy regarding RSS. The range is huge! Some papers package their outputs by sections of the paper. Some don't. Some dispense with RSS altogether, figuring that it will only cannibalize their beleaguered media empires.

There are a couple of alternatives to site hopping in search of the bright, orange RSS icon. One work-around is to include the inurl: syntax in the regular Google web search:

inurl:rss OR inurl:xml [insert semantics from Google News search] intitle:new intitle:hampshire

This workaround should get you a pre-confirmed list of feeds although it doesn't guarantee that they originate from ground zero live-free-or-eat-granite country.

Another way is to work from the colleges themselves as news sources. The very first hit I pulled yesterday yielded this list of Students for McCain backers by their academic institutions:

State Co-Chairs

Greg Boguslavsky -- Dartmouth College
Shaun Doherty -- Rivier College

University Chairs

Lianna French -- New England College
Joe Doiron -- New England College
Brendan Bickford -- New Hampshire Technical Institute
Trevor Chandler -- Plymouth State University
Brittany Puleo -- Rivier College

Julie Kraus -- Southern New Hampshire University
Regina Federico -- St. Anselm College
Allison Krause -- University of New Hampshire
Brandon Mancuso -- Franklin Pierce College
Dasha Bushmakin -- Keene State College
Ryan Dorris -- Daniel Webster College

In closing the follow-up would be to Google each college with the inurl syntax, filtering the pages that can be used to build your tracking folder in Feed Demon.

Use Case: RSS Readers as News Radars

Here's a current use case to track "events on the ground" through Feed Demon. There have been reported instances in the media recently of attempts to confuse or intimidate potential voters, particularly new or youth voters. College age voters are traditionally the most under-represented part of the electorate.

Whether it's due to cynicism or naivete a third more concrete factor (inexperience) makes this group prone to believing falsehoods and misleading statements aimed at creating doubt about their residential status. Ahem. So participation in their democracy will jeopardize their financial aid or even come back to haunt their parents during next year's tax season. What could be more American than not voting?

One way to monitor attempts at voter suppression around college campuses is to use a broadly descriptive search statement on Google News:

location:nh college students registration election

You'll find a piece of syntax snuck in here. It helps us focus exclusively on content sources on Google News originating from the Granite State. New Hampshire is my location of choice as the nearest swing state to me with area colleges signifying the swingiest of voting blocs.

You'll also note that the semantics of this search statement are not in anyway prejudicial or skewed towards a certain outcome. Any attempt to tune this search at the outset would overly constrain the result set (n=109) as of yesterday's test run. In other words a more effective content analysis occurs by introducing results-based logic once the feed appears in Feed Demon.

That's where you can construct "Watches" to pull instances of terms like:

* suppression
* fraud
* misleading
* confusion, etc.

...from the New Hampshire tracking folder where these hits reside.

Don't forget to sample several of the more questionable hits. They will acquaint you with terms you hadn't considered or steer you away from outcomes that are clearly off-the-mark from your search objectives.

The second stage of tweaking your RSS reader as news radar is to harvest the feeds sprouting from the sources included in your search results. Gathering up the list is easier than confirming each source's deployment or policy regarding RSS. The range is huge! Some papers package their outputs by sections of the paper. Some don't. Some dispense with RSS altogether, figuring that it will only cannibalize their beleaguered media empires.

There are a couple of alternatives to site hopping in search of the bright, orange RSS icon. One work-around is to include the inurl: syntax in the regular Google web search:

inurl:rss OR inurl:xml [insert semantics from Google News search] intitle:new intitle:hampshire

This workaround should get you a pre-confirmed list of feeds although it doesn't guarantee that they originate from ground zero live-free-or-eat-granite country.

Another way is to work from the colleges themselves as news sources. The very first hit I pulled yesterday yielded this list of Students for McCain backers by their academic institutions:

State Co-Chairs

Greg Boguslavsky -- Dartmouth College
Shaun Doherty -- Rivier College

University Chairs

Lianna French -- New England College
Joe Doiron -- New England College
Brendan Bickford -- New Hampshire Technical Institute
Trevor Chandler -- Plymouth State University
Brittany Puleo -- Rivier College

Julie Kraus -- Southern New Hampshire University
Regina Federico -- St. Anselm College
Allison Krause -- University of New Hampshire
Brandon Mancuso -- Franklin Pierce College
Dasha Bushmakin -- Keene State College
Ryan Dorris -- Daniel Webster College

In closing the follow-up would be to Google each college with the inurl syntax, filtering the pages that can be used to build your tracking folder in Feed Demon.

In Praise of Feed Demon

Feed Demon is an unfortunate name for an outstanding Information Management Tool. It's being sold (free download) as a personal organizer for RSS feeds. What it does really is create a pond of edible fish from an oceanful of loosely connected firehoses.

The key is to expand your comfort zone around what's RSS-enabled on the web and what's plain .html. It's easy enough to skim the Google ocean floor for appearances of RSS in URLs or the news sections of .com sites. Certainly acquainting your news queries with feeds and steering away from email alerts is a step in this direction.

What's there to prevent a warm fuzzy around RSS feeds? Lots of feeds (including blogs) have pre-defined defaults that push users toward one reader or another. The trick is to isolate the plain vanilla XML without the wrapper so you can feed your local copy of Feed Demon without hiccups, pop-ups, or passwords.

The difference between querying a search tool and a feed reader is the difference between rolling the dice and staying on top of what you need to know. Anyone with a pile-on of automated emails knows how tedious and time-consuming it is to dig out from under a pile of alerts.

There's no way to overlay your own need-to-know priorities around screaming urgencies or passing fancies. Every alert looks like a priority -- until you open it. Yes, you can create multiple email accounts but then you've opened up another receptacle without reducing the garbage piling up in your in-box.

One of the other unsold factors about RSS Readers is that the very term presumes you actually have the time to plow through the thousands of hits that will find their way into your reader. You don't. The information is waiting for you but it won't burn a hole in your pocket if you fight off the temptation to be on top of everything at once. First take a deep breath. Now replenish your feeds without acknowledging every update that lands within your reach.

Okay. So now I'm going to gush about the pond factor as it relates to catchable fish in Feed Demon:

First of all when you're about to freak out because your pond is threatening to become the size of a toxic, unswimmable lake you can press the anxiety button and any article over the prescribed limit will be marked as "read" -- that doesn't mean it goes away. You can still search it. You can even create automated filters that channel keywords into specific feeds and folders. It simply won't be considered fresh or new.

The search component works two ways: (1) you can search ad hoc among the thousands of feeds -- imminently preferable to doing the same among 8 billion pages indexed on Google. (2) you can set up filters in anticipation of hot topics you need to pulse (usually exact matches for a person or small entity within a larger group).

The folder concept is nothing unique. But folder designations are important for organizing the types of content that spans the feed streams. For instance it's one thing to use a To-Do list schema: gotta get a job, gotta push out a blog post based on what's latest, great. It's quite another to organize according to how the feed finds its way in: is it a series of job postings? Latest slew of news articles? Twitterings from top-of-mind text strings?

To pretend that these vastly different forms are all part of the same content soup is to conceed an important advantage of Feed Demon. Knowing who generates content and who it's intended for is the single most important attribute for understanding the context of any feed, regardless of the facts, views expressed, and the form for doing so. That understanding is what we're losing with the disappearance of traditional media. One way to reclaim this is to set up your folders according to media types be they newspapers, jobsites, blogs, social nets, etc.

I guess one aspect of Feed Demon that is more a solid feature than a best practice is the Dinosaur report that lists subscriptions which haven't been updated in the past 30 days. It's helpful to combine this feature with the "Find New Feeds" option that indexes a collective grouping of feeds among Feed Demon users. Sometimes this is helpful for determining correct terms and tags surrounding topics of interest. Other times it's more a distraction -- particulary when the feed remains turned on but the lights are out -- the feed's dried up.

In Praise of Feed Demon

Feed Demon is an unfortunate name for an outstanding Information Management Tool. It's being sold (free download) as a personal organizer for RSS feeds. What it does really is create a pond of edible fish from an oceanful of loosely connected firehoses.

The key is to expand your comfort zone around what's RSS-enabled on the web and what's plain .html. It's easy enough to skim the Google ocean floor for appearances of RSS in URLs or the news sections of .com sites. Certainly acquainting your news queries with feeds and steering away from email alerts is a step in this direction.

What's there to prevent a warm fuzzy around RSS feeds? Lots of feeds (including blogs) have pre-defined defaults that push users toward one reader or another. The trick is to isolate the plain vanilla XML without the wrapper so you can feed your local copy of Feed Demon without hiccups, pop-ups, or passwords.

The difference between querying a search tool and a feed reader is the difference between rolling the dice and staying on top of what you need to know. Anyone with a pile-on of automated emails knows how tedious and time-consuming it is to dig out from under a pile of alerts.

There's no way to overlay your own need-to-know priorities around screaming urgencies or passing fancies. Every alert looks like a priority -- until you open it. Yes, you can create multiple email accounts but then you've opened up another receptacle without reducing the garbage piling up in your in-box.

One of the other unsold factors about RSS Readers is that the very term presumes you actually have the time to plow through the thousands of hits that will find their way into your reader. You don't. The information is waiting for you but it won't burn a hole in your pocket if you fight off the temptation to be on top of everything at once. First take a deep breath. Now replenish your feeds without acknowledging every update that lands within your reach.

Okay. So now I'm going to gush about the pond factor as it relates to catchable fish in Feed Demon:

First of all when you're about to freak out because your pond is threatening to become the size of a toxic, unswimmable lake you can press the anxiety button and any article over the prescribed limit will be marked as "read" -- that doesn't mean it goes away. You can still search it. You can even create automated filters that channel keywords into specific feeds and folders. It simply won't be considered fresh or new.

The search component works two ways: (1) you can search ad hoc among the thousands of feeds -- imminently preferable to doing the same among 8 billion pages indexed on Google. (2) you can set up filters in anticipation of hot topics you need to pulse (usually exact matches for a person or small entity within a larger group).

The folder concept is nothing unique. But folder designations are important for organizing the types of content that spans the feed streams. For instance it's one thing to use a To-Do list schema: gotta get a job, gotta push out a blog post based on what's latest, great. It's quite another to organize according to how the feed finds its way in: is it a series of job postings? Latest slew of news articles? Twitterings from top-of-mind text strings?

To pretend that these vastly different forms are all part of the same content soup is to conceed an important advantage of Feed Demon. Knowing who generates content and who it's intended for is the single most important attribute for understanding the context of any feed, regardless of the facts, views expressed, and the form for doing so. That understanding is what we're losing with the disappearance of traditional media. One way to reclaim this is to set up your folders according to media types be they newspapers, jobsites, blogs, social nets, etc.

I guess one aspect of Feed Demon that is more a solid feature than a best practice is the Dinosaur report that lists subscriptions which haven't been updated in the past 30 days. It's helpful to combine this feature with the "Find New Feeds" option that indexes a collective grouping of feeds among Feed Demon users. Sometimes this is helpful for determining correct terms and tags surrounding topics of interest. Other times it's more a distraction -- particulary when the feed remains turned on but the lights are out -- the feed's dried up.

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.

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.