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This is Part 1 of a 2 Part Series. Part 2 will focus on semantic web, faceted navigation, maybe some graph theory. I’m not there yet.

The purpose of this article is to discuss dealing with the practically infinite amount of information that is now available to us via the internet. Information is becoming increasingly distracting and I think can lead to serious impact especially on areas of research where true focus is needed.

Intro

If I can sit on a couch with my phone / PDA / laptop and find the answer to Jeopardy questions fast enough, what value is there in knowing an obscure date or fact? Absolutely none. Facts on their own are simply trivia. I think everyone has agreed with this for a long time. Rote-memory teaching techniques may be good if your goal is to know the names of all the bones in the human body. And granted, their are certain vocabularies which must be learned in order to understand fields of work. Bones of the body are part of the vocabulary of doctors / biologists and the like. But yet again, knowing an individual word’s definition may not have much value. So where does the value begin?

Concepts are Key

Our ability as humans to understand and create relationships between the pieces of information provides for an additional level of understanding. Communicating concepts and relationships via a complex language allows us to collaborate and grow those ideas, to build on the work of others.

So what happens now when in the age of google, flickr, twitter, wikipedia, email, calendars alerting you to do crap… an age where we are constantly bombarded with ‘trivia’… how do we work with such large volumes of data? It’s not like we’ve simply invented a better tool and we need to learn to use the tool and then the quality of our work or art will increase. A new tool does free you from previous restrictions, but always introduces dependencies of its own. You have to carry it around. People must be trained on how to use it. Going to Wikipedia every time you hear about something you’re curious about is not the answer. It’ll give you enough ‘cocktail language’ to discuss it at a party. People were doing that when Discovery channel came out. All of a sudden everyone is an expert on something they watched on TV. But where does this get us other than filling our minds with more crap? I agree that much of the content on TV can be considered valuable information, but there is a limit to how fast we can learn, and a limit on how long we can retain that knowledge without systematic repetition.

Human memory sucks

Repetition has been known for quite some time to offset the curve of forgetting. There are several flash-card like pieces of software out there that track what you know and don’t know and schedule the intervals of repetition accordingly. They work great for things like learning and maintaining words of a foreign language. Again this is a tool for committing to rote memory. I played around with Mnemosyne a bit, and even used it to help study for the BJCP exam. It works very well, but it has to be a conscious effort to sit down and have the software ask you questions every day.

As mobile computing becomes faster, there may become less and less need to keep trivial knowledge in our heads. Computers can organize and search far larger sets of data than any brain. You can even print out a report of what they know! If I can recall the fact at will, does it matter if the data was stored in a computer or in my mind?

Let the Computer Do It

So lets assume that all non-operational trivial knowledge has been dumped to the computer. I can still brush my teeth and so forth. Do I care to remember what brand toothpaste I like? Why? When I’m at the store I’ll ‘remember’ it then. Does this make me dumb? No way. It allows for better focus. Focus on the concepts, not the constantly interrupting trivia. I want to call someone on the phone, not figure out how the freaking phone works. Spending more time managing the devices that are supposed to assist in your life is madness.

So how do we focus on the concepts? How do we organize the data that’s important to us so that we can see the relationships, work with those relationships, find what we need when we need it? Organized correctly within a computer, we can have a far larger understanding of more and more concepts and their relationships. Google is not the answer. Google’s input is trivia. Output is things that are related to the trivia. Good, but not good enough.

The classic way of organizing information has been with a simple taxonomy. The folders and sub-folders in your computer, in your web bookmarks. For a small set of data it is fine. As these structures grow, one must understand the taxonomy in order to navigate it. When looking at any one ‘folder’ for example, one must think if what they are looking for might be under that folder. How does this thought process work?

Example: I’m looking for speakers. I see a folder called audio. I now mentally think audio is related to speakers because speakers create sound / audio output. So I drill down and find the speakers folder. Yet at the same level I see a folder called linux. What? Why is that there. I drill in and see that there are links about using linux to process audio. OK now I see the relationship, but it was not obvious when up at the audio level.  Taxonomies can handle situations like this by applying rules to the organization. These now become domain specific and definitely require knowledge by the user to navigate them. Why are we creating structures that require that the user infer meaning out of them in order to use them? The more complex the structure, the more rules must be applied. This can only grow so far before becoming unweildy, especially to the casual user.

Prelude to Part 2

So let’s say I have a search feature. Great. I search for speakers and find them right away. Some are tagged with audio. Some with audio and car. Now let’s shift gears and navigate the metadata (tags). I decide I want to see everything related to car audio and select both of those tags. Now I see the computer items and software that I plan on using to process audio in the car, because they were also tagged with audio and car, plus linux. The relationship is clear. Moreover, you could arrive at these same pieces of information via many other entry points, not just audio.

Loose tag / attribute based organization seems very compelling. Understanding and navigating the relationships between the metadata become the challenge.  This will be the topic of the 2nd piece of this 2 part series. Stay tuned!