Taxonomy in Extreme Places

How often do you get to be immersed in a completely alien work environment?

As a taxonomist, I get to learn about so many different domains through my work, from mouse genetics to greeting card manufacturing. Each company has its interesting quirks and workplaces…Like the toy manufacturer, whose workers had their cubicles adorned with all sorts of inspiration and materials: multi-colored fur, googly-eye collections, pictures of themsleves as superheroes…

But this week, I got to experience something completely different.

We just started a content strategy project with a semiconductor equipment manufacturer which aims to help their service groups (the folks who fix the machines) get the right information at the right time. This is an interesting project involving issues around technical writing and information architecture (DITA), integration across many different knowledge systems and databases, and getting information to users in a less than hospitable environment – the clean room.

A clean room is essentially a manufacturing or research facility that has low levels of environmental pollutants, such as dust and microbes. Pollutants are kept to a minimum through air filtering and circulation, as well as a strict dress code involving what are “lovingly” referred to as “bunny suits“. A clean room suit involves:

  • Glove liners
  • Rubber gloves x 2
  • Hair/beard net
  • Face mask
  • Shoe covers
  • Coveralls
  • Hood
  • Booties
  • Safety glasses

You get dresImagesed in a specific sequence so as to reduce contamination… first being the glove liner, rubber glove #1, hairnet, face mask, and shoe covers. Then you enter a second room where you add the hood, coverall, booties, rubber glove #2 and safety glasses. You then walk over some sticky paper into an air lock, where you are blasted with some air, and you’re now ready for the clean room.

Two minutes in a bunny suit and you gain a quick appreciation for the difficulties inherent to working in such an environment. It’s hot under all those layers, you have poor peripheral vision in the hood, the glasses constantly get fogged up from your breath under the mask, and it’s hard to walk. (Well, I have to admit that the “hard to walk” part is probably because I was wearing high-heels in my booties – ill-advised and embarassing! I also made the newbie mistake of taking a cough drop before putting on my mask, and I ended up breathing menthol air into my eyes and fighting back tears the whole time.)

But if I’ve set the scene up appropriately, you can start to imagine the challenges inherent to knowledge work in this environment. First of all,Image it’s hard to get access to information – carrying around a laptop is difficut, your hands are slippery, there’s nowhere to set it down in this lab, nowhere to plug it in… Even if you did find a place for it, you can’t use a track pad when you are wearing 3 layers of gloves – it’s hard to type and the gloves don’t create enough friction for the pad to capture movement. You might use a tablet and stylus, but there are holes in the floor, so if you drop it… You might use a handheld device, but again with gloved hands good luck typing on that tiny keypad, and the screen is much too small to show detailed tool schematics. You don’t have access to the internet, so all the information has to be available on the machine, and there are hundreds of parts for each machine.

Add the next layer: search, systems and content structure. These folks currently have to search across mutliple systems to try to find documentation on specific problems… starting with the original manual, which is likely for the product as it was shipped, not as it was configured at the client site. There are multiple databases where there might be troubleshooting tips or solutions, but you have to check them individually. The content is not well tagged or structured, so if you do find a document that might be useful, it’s typically a gigantic PDF that you have to comb through.

As you can see, this is a challenging problem: how do you get the right information (the right amount of it) in a way that is well structured and accessible to them in the clean room environment? What part of it involves structured writing in XML vs. system integration vs. taxonomy and metadata and how do we pull all those pieces together to offer a simple interface to a service professional?

We’ll be working on this project for the coming weeks, so I’ll keep you posted on the conclusions and insights. But in the mean time, I’m sure this will probably be my personal “one to top” in terms of taxonomizing in extreme places. Perhaps I’ll beat it if we ever do any work with cave spelunkers, submarines, or NASA…

Share your extreme taxonomy stories in the comments!

Photo credits:

http://lasp.colorado.edu/images/engineering/tech_cap/clean-room-suit.jpg
http://ixbtlabs.com/articles2/cm/intel-israel-dec2k5.html

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The Fractal Nature of Knowledge

Here is the question posed by Arnold King (http://arnoldkling.com)

I am interested in the phenomenon of knowledge specialization.For example, in medicine, there are many more specialties and sub-specialties than there were 30 years ago. My guess is that if libraries are still using classification systems, there should be a lot more categories. My guess is that major universities have many more departments than they did 30 years ago.

I think this is important in economics because I think that businesses and economic systems have become harder to manage as a result. In short, the leaders tend to know less about the specialized information that is further down in the organization, because the amount of the latter is increasing (I conjecture).

I would like some quantitative indicators of the rate at which new knowledge categories or sub-categories are being developed. Do you know how to even go about searching for such indicators?

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I spent some time thinking this over. I may have ranged too far from the question and I know I am preaching to the choir here, but thought the issue of economic value creation and knowledge categorization would benefit from a bigger picture perspective.

The problem with the question is that knowledge is fractal in nature. It is endlessly complex and classification depends on scale and perspective. It’s not a matter of “there should be more categories… “; there are more. It simply depends on where you look and your perspective. Continue reading

Hype cycles revisited – taxonomies under the gun

My last post discussed the idea that knowledge management has gone through the hype cycle and people are abandoning the term for more fertile buzzwords. According to Gartner, taxonomies are now at the “Peak of Inflated Expectations” headed for the “Trough of Disillusionment” in the hype cycle, which begs reflection on the concept of taxonomies. Continue reading

Knowledge management – is the hype over?

There’s been some talk about knowledge management becoming a thing of the past…

KM is not passé, but has been through the hype cycle. To quote Gartner Group, I would say we are on the “plateau of productivity” meaning organizations are more realistic about what they can achieve with KM and the vendors have for the most part abandoned the term for more fertile buzzword territory.

Continue reading

Encouraging participation in communities or repositories

Someone on the Taxonomy Community of Practice (TaxoCoP) recently wrote about methods to improve usage of knowledge management repositories. The challenge of encouraging and measuring participation is a tough one. You might build a terrific application with a great taxonomy and people may not use it.

A repository is only as good as the content it contains – in order for it to contain valuable information, people need to contribute. People will not contribute unless they see the value. Think of the creation side of the equation – forums like the TaxoCoP are places where people collaborate and share knowledge. We have great contribution because we have… great contribution… Continue reading