Leaving to one side how to avoid re-evaluating the repetitive glut of materials from any search, there is the more fundamental problem of how to you search for a subject?
This is a back-of-the-envelope sketch that I will be expanding, but here goes:
Basic Search
At its most basic, a search consists of a <term> and the search seeks to match strings that match that <term>.
Even allowing for Boolean operators, the matches against <term> are only and forever string matches.
Basic Search + Synonyms
Of course, as skilled searchers you will try not only one <term>, but several <synonym>s for the term as well.
A good example of that strategy is used at PubMed:
If you enter an entry term for a MeSH term the translation will also include an all fields search for the MeSH term associated with the entry term. For example, a search for odontalgia will translate to: “toothache”[MeSH Terms] OR “toothache”[All Fields] OR “odontalgia”[All Fields] because Odontalgia is an entry term for the MeSH term toothache. [PubMed Help]
The expansion to include the MeSH term Odontalgia is useful, but how do you maintain it?
A reader can see “toothache” and “Odontalgia” are treated as synonyms, but why remains elusive.
This is the area of owl:sameAs, the mapping of multiple subject identifiers/locators to a single topic, etc. You know that “sameness” exists, but why isn’t clear.
Subject Identity Properties
In order to maintain a PubMed or similar mapping, you need people who either “know” the basis for the mappings or you can have the mappings documented. That is you can say on what basis the mapping happened and what properties were present.
For example:
toothache
| Key | Value |
| symptom | pain |
| general-location | mouth |
| specific-location | tooth |
So if we are mapping terms to other terms and the specific location value reads “tongue,” then we know that isn’t a mapping to “toothache.”
How Far Do You Need To Go?
Of course for every term that we use as a key or value, there can be an expansion into key/value pairs, such as for tooth:
tooth
| Key | Value |
| general-location | mouth |
| composition | enamel coated bone |
| use | biting, chewing |
Observations:
Each step towards more precise gathering of information increases your pre-search costs but decreases your post-search cost of casting out irrelevant material.
Moreover, precise gathering of information will help you avoid missing data simply due to data glut returns.
If maintenance of your mapping across generations is a concern, doing more than mapping of synonyms for reason or reasons unknown may be in order.
The point being that your current retrieval or lack thereof of current and correct information has a cost. As does improving your current retrieval.
The question of improved retrieval isn’t ideological but an ROI driven one.
- If you have better mappings will that give you an advantage over N department/agency?
- Will better retrieval slow down (never stop) the time wasted by staff on voluminous search results?
- Will more precision focus your limited resources (always limited) on highly relevant materials?
Formulate your own ROI questions and means of measuring them. Then reach out to topic maps to see how they improve (or not) your ROI.
Properly used, I think you are in for a pleasant surprise with topic maps.