This watchlist was created in 2004 from several other lists and at that time it consisted of about 68.000 entries. I use the word entries, because in the years after it became fuzzy if one record is the same as one individual. By the end of 2008 the list had grown to over 1,1 million entries. In 2008 after the American Civil Liberties Union (ACLU) mentioned that the list had passed the 1 million, the government came with an explanation. Although we have recorded over 1 million entries in the database, the net result is that these records correspond to about 400.000 individuals. Terrorist often use different and thus multiple identities, use several (falsified) passports etc. But adding entries with only the first initials and last name, while an entry of the full first names and last name already exists will result in unwanted side-effects.

We all know, as being interested in data quality and identity resolution, that J. Robinson will result into much more matches (hits) than James Robinson. Indeed the number of found matches will sky-rocket and have to be evaluated manually. Might this be the reason, that we see more and more security personnel on airports?

In the latest audit report of the U.S. Department of Justice about this watchlist one other problem was analyzed. While extensive procedures were made for nominating and adding suspects to the watchlist, there is no procedure for removing people from the list. Based on a sample of almost 70.000 entries and investigation of the individuals an astounding number of 35% omissions was found. People who had died were still on the list, people who were no longer investigated upon, cases which had been closed etc. So this watchlist is growing and growing. Resulting in screening personnel who ensnare many innocent travelers as suspected terrorists. And wasting their time and divert their energies from looking for true terrorists. It seems to me that FBI and TSC can benefit from better Data Governance, what do you think?

Many of you will probably start thinking along the lines of data ownership, database access and hierarchy. But data quality processes are far more essential. First of all, you have to know who you are dealing with.The following video is self-explaining:

The wrong Guy

A survey of Human Inference in 2008 indicates that processes are the biggest experienced challenge in relation to Data Quality. However the subject that seems to be no problem is the budget. Human inference differentiates itself by interpretation of knowledge. So from this perspective I wonder how the respondents interpreted the word “processes”. Do they mean the processes within the value chain of their companies or do they actually mean the process of obtaining a budget for Data Quality? The latter would actually explain a lot.

HI Survey Results