I appreciate the sentiment but I find something odd about expecting ontology to be backwards compatible. Sometimes there are big, insightful updates that reshape ontology. Those are sometimes not compatible with the old ontology, except insofar as both were attempting to model approximately the same reality. As an example, at some point in the past I thought of people has having character traits, now I think of character traits as patters I extract from observed behavior and not something the person has. The new ontology doesn’t seem backwards compatible to me, except that it’s describing the same reality.
There’s a LOT of detail that the word “compatible” obscures. Obviously, they’re not identical, so they must differ in some ways. This will always and intentionally make them incompatible on some dimensions. “compatible for what purpose” is the key question here.
I’d argue that your character-traits example is very illustrative of this. To the extent that you use the same clustering of trait definitions, that’s very compatible for many predictions of someone’s behavior. Because the traits are attached differently in your model, that’s probably NOT compatible for how traits change over time. There are probably semi-compatible elements in there, as well, such as how you picture uncertainty about or correlation among different trait-clusters.
I appreciate the sentiment but I find something odd about expecting ontology to be backwards compatible. Sometimes there are big, insightful updates that reshape ontology. Those are sometimes not compatible with the old ontology, except insofar as both were attempting to model approximately the same reality. As an example, at some point in the past I thought of people has having character traits, now I think of character traits as patters I extract from observed behavior and not something the person has. The new ontology doesn’t seem backwards compatible to me, except that it’s describing the same reality.
There’s a LOT of detail that the word “compatible” obscures. Obviously, they’re not identical, so they must differ in some ways. This will always and intentionally make them incompatible on some dimensions. “compatible for what purpose” is the key question here.
I’d argue that your character-traits example is very illustrative of this. To the extent that you use the same clustering of trait definitions, that’s very compatible for many predictions of someone’s behavior. Because the traits are attached differently in your model, that’s probably NOT compatible for how traits change over time. There are probably semi-compatible elements in there, as well, such as how you picture uncertainty about or correlation among different trait-clusters.