Need for validating information

Many open issues drift around data publication, but validation is both the biggest and the haziest.

Some form of validation at some stage in a data publication process is essential; data users need to know that they can trust the data they want to use, data creators need a stamp of approval to get credit for their work, and the publication process must avoid getting clogged with unusable junk.

The computer can be programmed only to accept numbers between 11 and 16. However, this does not guarantee that the number typed in is correct.

For example, a student's age might be 14, but if 11 is entered it will be valid but incorrect.

Such investments in enterprise portals, document management systems, and text retrieval technology give companies better ways to present information. Good presentation of information means focused information relevant to the decision making in progress at any time.

Internal information should be consistent (but often isn't).

I’ve tried to stay away from deeper consideration of what data quality means (which I’ll discuss in a future post) and from the broader issues of peer review associated with the literature, but they inevitably pop up anyway.

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In these circumstances ensuring the recognition of "quality" data which can be relied upon is key.

Earlier articles discussed information overload - what is it? Future articles will consider how: Information Overload A search on Google using the "information" "overload" found 3,080,000 results. It's a good example of the excess of information which we face daily.

Information Causes Change Issues The increasing volume and sources of information mean that managers must be able to adapt constantly to ensure optimisation of information.

When we try to retrieve or search for information, we often get conflicting information or information which we do not want.

Therefore, validating information is another important aspect of information usage. In many cases "old'' or outdated information has as little value as no information at all, or worse, may have negative value.