Auto-classification and metadata –the missing link.
I am doing some research on auto-classification and would sincerely appreciate your input, thoughts, and insight. This is the third in a series on auto-classification. The other two postings are Auto-classification – Has it time come? Too bad no one knows what it does! The second blog is Auto-classification, the only way out.
Auto-classifiers certainly help in organizing and managing content with an automated approach. Pretty basic. I think the key to accurate classification is the associated metadata. The types of classification metadata include intrinsic, administrative/management, descriptive, and semantic. All are useful, however, the more descriptive the metadata, the better the auto-classification will be.
Why is metadata so important? Here are some reasons:
- The Challenges of Content Overload
- 80% of enterprise data is unstructured (IDC)
- 60% of documents are obsolete (e.Law)
- 50% of documents are duplicates (equivio)
- The benefits of automatic semantic metadata generation
- Elimination of costs and errors associated with end user tagging
- Identification and protection of secure content assets from unauthorized access and portability in accordance with compliance procedures
- Automatic identification and tagging of documents of record
- Normalization of content across functional and geographic boundaries
- Integration with search
- Ability to apply policy consistently across diverse repositories and
environments
Given the fact that accurate and meaningful metadata is often the missing link in auto-classification, my question is why more organizations aren’t jumping on the bandwagon? In fact, in a recent AIIM survey, that we co-sponsored, it appears that the term is understood, but not how to get there.
What do you think?
