Digital Convergence: A Blast from the Past
July 15, 2008
In 1999, I wrote two articles for a professional journal called Searcher. The editor, Barbara Quint, former guru of information at RAND Corporation, asked me to update the these two articles. I no longer had copies of them, but Ms. Quint emailed my fair copies, and I read my nine-year old prose.
The 2008 version is “Digital Convergence: Building Blocks or Mud Bricks”. You can obtain a hard copy from the publisher, Information Today here. In a month or two, an electronic version of the article will appear in one of the online commercial databases.
My son, Erik, who contributed his column to Searcher this month as well, asked me, “What’s with the mud bricks?” I chose the title to suggest that the technologies I identified as potential winners in 1999 may lack staying power. One example is human assigned tags. This is indexing, and it has been around in one form or another since humans learned to write. Imagine trying to find a single scroll in a stack of scrolls. Indexing was a must. What’s not going to have staying power is my assigning tags. The concept of indexing is a keeper; the function is moving to smart software, which can arguably do a better job than a subject matter expert as long as we define “better” as meaning faster and cheaper”. A “mud brick” is a technology that decomposes into a more basic element. Innovations are based on interesting assemblages of constitute components. Get the mix right and you have something with substance, the equivalent of the Lion’s Gate keystone.
Today’s information environment is composed of systems and methods that are durable. XML, for example, is not new. It traces its roots back 50 years. Today’s tools took decades of refinement. Good or bad, the notion of structuring content for meaning and separating the layout information from content is with us for the foreseeable future.
Three thoughts emerged from the review of the original essays whose titles I no longer recall.
First, most of today’s hottest technologies were around nine years ago. Computers were too expensive and storage was too costly to make wide spread deployment of services based on antecedents of today’s hottest applications such as social search and mobile search, among others.
Second, even though I identified a dozen or so “hot” technologies in 1999, I had to wait for competition and market actions to identify the winners. Content processing, to pick one, is just now emerging as a method that most organizations can afford to deploy. In short, it’s easy to identify a group of interesting technologies; it’s hard for me to pick the technology that will generate the most money or have the greatest impact.
Third, confusion was rampant in 1999. And today confusion is rampant. My thought was that confusion and information technology go hand in hand. In the last nine years, we have maintained the status quo with regards to confusion.
One of the major challenges we face, in my opinion, is that at this moment people use terms without defining them. As a result, people talk about technology and the listener defines the technology one way. The problem is that the speaker often defines the technology in another way.
We are living in a datasphere (a word I usurped from someone in the mid 1980s) and yet talking about needs, requirements, and functions is as difficult if not more difficult than it was in 1999. The result is, based on my experience, quite a few stupid decisions.
Let me close with one example. A major research entity in the United States owns Google Search Appliances, OpenText’s LiveLink, and Microsoft SharePoint. Why own all three? Each system can be set up to perform the same functions. How did this type of overlap come about?
The answer is that well meaning but uninformed people went to meetings, used terms no one took time to define and build consensus for a definition, and then proceeded to buy duplicative systems.
No wonder search, content processing, and text analytics are skating on thin ice. Organizations acquire systems, learn what the systems do, and then evidence dissatisfaction. The reality differs from each user’s personal definition of the technology.
Stephen Arnold, July 15, 2008
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