Names of Things

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What are the characteristics of object names? In my last post I began to deconstruct the object classification hierarchy for the White Knight’s song in Lewis Carroll’s Through the Looking Glass. As a reminder, we identified a few discrete statements about a song’s metadata:

  • There is a “thing” that is a SONG, which is “A-SITTING ON A GATE.”
  • That SONG has a SONG_NAME, which is “THE AGED AGED MAN.”
  • That SONG_NAME has a SONG_NAME_CALLING, which is “HADDOCKS’ EYES.”
  • The SONG has a SONG_CALLING, which is “WAYS AND MEANS.”

Abstractly, we have an object that has a base level object type classification (it is a SONG) as well as two distinct attributes: a NAME, and (what I must call for simplifying the discussion) a CALLING. These are objects in their own right, although only one is specified to have an attribute – the song’s NAME has a CALLING attribute. OK, done, everything is clear.

Except that I still am bothered by a nagging ambiguity in the White Knight’s pronouncement that "The song really IS 'A-SITTING ON A GATE'" since that confuses what the real definition is of the thing under consideration: is it a song, or is it an “A-SITTING ON A GATE”? Now, we are left to interpret the semantics on our own based on the context of specification, and here are some options:

  • Multiple inheritance: “A-SITTING ON A GATE” is an object class and the instance of the song actually inherits its attributes from more than one base object class.
  • Aliasing: “A-SITTING ON A GATE” is also a NAME attribute that is an alias or alternative to the primary SONG_NAME that is “THE AGED AGED MAN.”
  • Reference: “A-SITTING ON A GATE” is the actual thing that is referred to separately by unique names “THE AGED AGED MAN” and “WAYS AND MEANS.”

These are all aspects of naming, classification and ultimately unique identification - and resolving what things are and what they really mean and in which context is critical to properly modeling and using data, as we’ll consider next time.

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David Loshin

President, Knowledge Integrity, Inc.

David Loshin, president of Knowledge Integrity, Inc., is a recognized thought leader and expert consultant in the areas of data quality, master data management and business intelligence. David is a prolific author regarding data management best practices, via the expert channel at b-eye-network.com and numerous books, white papers, and web seminars on a variety of data management best practices. His book, Business Intelligence: The Savvy Manager’s Guide (June 2003) has been hailed as a resource allowing readers to “gain an understanding of business intelligence, business management disciplines, data warehousing and how all of the pieces work together.” His book, Master Data Management, has been endorsed by data management industry leaders, and his valuable MDM insights can be reviewed at mdmbook.com . David is also the author of The Practitioner’s Guide to Data Quality Improvement. He can be reached at loshin@knowledge-integrity.com.

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