Term Database Categories: Too Many … Too Few … or "Just Right"

October 31, 2013 Mark Childress

As terminology database administrators we in the Terminology@SAP team are sometimes asked to add – or remove – a data category or other aspect of the term entries. When this happens our primary question has to be: What would this do to the value of our terminology?


Some requests sail through easily. They’re obvious. It's Win-Win for everybody. The new categories add value to the entire database by filling a gap we didn't realize needed filling, or by supporting a strategic project. Merging the term database of an acquired company is often the impetus for this: When we map the data categories onto each other prior to import we realize we’re missing a slot for something useful that’s in the acquired organization’s database but not (yet!) in our own.


Other requests are too specialized. We can’t invest administration effort and software development time in a category that only one person will use for a handful of terms. Our database doesn't need to distinguish between antonyms, for example, because there are so few in our line of business. We've removed several categories in the past after we realized no one was using them.


The requests at which we truly balk are ones which would degrade the value of the term database. One which reappears repeatedly is the wish to delete all the synonyms and remove that category forever, on the grounds that we should never have synonyms in our products. But we can’t ignore reality: Some synonyms are legal requirements; others are de facto standards along with the preferred terms in their subject areas. We cannot eliminate the existence of synonyms by eliminating the category. A synonym is an unavoidable terminological element which needs to be dealt with in the terminology strategy just like the other elements.


To sum up, some colleagues may pout that they can’t mark their terms as neologisms, while others are annoyed because their nouns must include grammatical genders. But our job is to look at the big picture and use the return on investment as one of the primary arguments for changing the data categories in the term database.

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