Notion of the "Semantic Hive" or "Hive Plot"

Someone was explaining something to me and they used the term "semantic hive".  This blog post explains what I think a semantic hive is.  It could be the case that they are using that term "semantic hive" to describe something different; but I believing that what I am describing is necessary. Another term for what I am trying to describe is "hive plot".

To create a problem solving system you need to be sure to include all of the pieces of that system.  One of those pieces is the knowledge from some area of knowledge.  Users of that knowledge need to be committed to that knowledge in order for the system to work the way they want/need the problem solving system to work. But reality can get very messy.  The Cnyfin Framework, which is a sensemaking tool, helps one organize an area of knowledge into categories.  Those categories are:

  • Best practices: things that tend to be obvious even to people outside an area of knowledge. There tends to be only one way to do something which makes sense.
  • Good practices: things that are a bit more complicated but the subject matter experts within an area of knowledge that have skills and experience tend to agree on these practices.  Different groups can use different good practices as a matter of policies.
  • Emergent practices: things that are even more complex and subject matter experts within an area of knowledge tend to disagree with one another as to what the good practices are which leads to multiple different views, each which is reasonable based on the principles of an area of knowledge and the logical patterns of the situation. There tends to be tight, identifiable clusters of answers.  (For example, if accounting standards have ambiguity and accountants apply fundamental principles to figuring out a situation and say each of the Big 4 CPA firms; PWC, Deloitte, EY, KPMG; each come up with a view on how to handle that situation; each view could be correct)
  • Novel practice: this is similar to emergent practices except that there are no identifiable logical patterns of the situation and no identifiable principles that can be applied; but logical answers can be figured out but the clustering of answers is more spread out, not as tight.
A "semantic hive" or a "hive plot" is a group that has a similar view and have similar "ontological commitment" or "knowledge commitment". Effectively, each "semantic hive" or "hive plot" is mutually exclusive: you belong to one semantic hive or another semantic hive, you cannot belong to both because that would be illogical.

Here is an example.  Say you wanted to create a knowledge graph of the semantics of the U.S. Constitution.  If you tried to get everyone to agree with one single knowledge graph, this could be quite a challenge.  But, if you broke up the group of people trying to do this into "semantic hives" or "hive plots" such as "democrat" and "republican" and/or "conservative" and "liberal" figuring out what goes into that knowledge graph becomes significantly easier.  Then, you could use the semantic hive or hive plot created by the group you subscribe to most to perform reasoning.

A similar example related to financial reporting might be two areas of significant variability that I have notices in financial reports.  One is where the line item "Income (Loss) on Equity Method Investments" belongs on the income statement.  Another is the classification of equity as "Equity" or as "Temporary Equity" on the balance sheet.

What a "semantic hive" or "hive plot" offers is flexibility in the representation of knowledge in a knowledge graph. It also offers clarity as to which knowledge graph you subscribe to.  Perhaps there is a better or different term; this is more about the idea than the exact term.



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