By Alexander Villafania
INQUIRER.net

LAS VEGAS, NEVADA — IBM has its own army of scientists. Some of them are housed in IBM’s New York City office. However, many are spread across Big Blue’s subsidiaries in the US and abroad.

They can be very technical but most of the time the topics are within the bounds of being understandable. A few are able to make the most difficult technical jargon understandable. These scientists are present at the IBM Information on Demand Conference 2008, as they spoke to the company’s corporate clients.

On the other hand, some are IBMers have the ability to snatch a bit of intelligence even from the most technical persons and make them wonder: “Where have I been?” Take Jeffrey Jonas, for example, Distinguished Engineer and Chief Scientist of Entity Analytic Solutions of the IBM Software Group. He sat down with a few reporters from Asia and Eastern Europe to talk about where information is being taken now and how it can be utilized for various purposes.

Ok, so you’re wondering first what’s Entity Analytics? It sounds highfalutin but it simply means it’s the next step towards relationships between information across multiple sources.

It’s not data management and definitely it’s not artificial intelligence but this concept means data is becoming smart.

Jonas used the terms “seeing data as a question,” “data stitching,” “self-correcting data,” sequence neutrality,” and “perpetual analytics,” with each term becoming more confusing.

For the 60 minutes that Jonas spoke to nearly a dozen journalists, only a few ever dared to ask what he meant by these, hoping to use some stock knowledge to at least better understand what he meant. Jonas spoke slowly, as if he was talking to a group of grade school kids. But that’s only because 1) he talks fast and 2) he knew half the group of journalists didn’t use English as a secondary language.

But then again, Jonas did make sense of what he said. And like a good grade school teacher, he used analogies to make himself more understandable. His favorite: jigsaw puzzles.

Jonas said that the level of understanding about stored information is as basic as trying to find a piece of puzzle then forcing it to fit into another piece when it’s not supposed to.

He said data is ever changing and it means that every location where that data is stored has to be changed but not without looking at the relevance of that change.

A jigsaw puzzle means nothing without the other pieces and those who are required to know the relevance of one piece of data has to look at the bigger picture that the jigsaw has to offer. He said that as each piece is put in place, slowly, the idea of the bigger picture becomes clearer and those who read the data will be better informed.

Jonas said that data has to be treated like a question. “Be persistent,” he said.

The relevance of data is not when it is processed in scheduled batches but in real time. The value of data is only as good as the time that it is being received. He said it’s also better to have data disambiguated than having a host of analysts trying to resolve those “maybes.”

Where has his level of expertise been used?

It is used by IBM for its fraud, risk and compliance applications. These are used by financial institutions as preventive measures against fraudulent transactions. Jonas’ work is also used in law enforcement and intelligence networks.

His work has been applied on privacy security and homeland security. He is helping the United States, for one, protect itself from terrorist acts. While the concepts he described to media seemed futuristic, the US government is already using them to identify who can be doing things they are not supposed to do on US soil. This is how technology is being used for intelligence and Jonas is an expert in this field.

It got me thinking that the terms Jonas used might be confusing, but still his work has saved lives.

Jonas maintains a blog where he talks about his work and his passion as a triathlete.