I started to write this post a long time ago in October; unfortunately before I finished I got hit with the start of teaching. I considered just ditching the post, as it is now so out-of-date and I am not usually a zombie poster. However, in this case, I shall post as a) it helps my mind to move back toward research after so long away and b) it will be my first of 2012, so I can check my makefiles work!
A couple of follow ups from my previous post.
Nicolas Le Novere commented via twitter on even the highest level assertion of that radioactivity is a dependent continuant.
@phillord fluorescence and radioactivity are occurrent not continuant. Freeze time to check. @phillord hence the unit of radioactivity: per second (Becquerel)
In my original post, I suggested we needed
Radioactivity; in hind-sight, perhaps I should have used
Radioactivity, which may have circumvented this issue.
However, I think it is worth considering this a little further.
I would nearly agree with Nicolas that radioactivity is a process;
actually, I would say that radioactive decay is a process, while
radioactivity is a property of this process. However, in my last post, I
was looking at a model which was “BFO-like” as OBI is based on BFO. For
BFO, that radioactivity is a rate, is measured per second does not mean
that it is an occurrent; any more than velocity which is also measure
per second is an occurrent. Actually, in BFO land,
be a quality of the atoms which are decaying and not a measurement of
the process. This is because, as Pierre Grenon says, properties of
processes do not
In fact, if we look more at this more closely still, BFO would also
claim that radioactive decay is not, as it might appear, a
because processes are continuous. This is not true for radioactive
decay, even for a bulk of radioactive material. An atom decays, then
there is a pause, then another decays. This makes radioactive decay a
processual entity, which can contain discontinuities.
I am not arguing that BFOs treatment of processes is correct — in fact, I think it is nonsensical. However, it is this line of arguing that I was using in my previous post.
David Sutherland rather takes me to task about whether realism does what I suggest.
I agree completely, but what realist principle says you need to give something the most detailed classification you can come up with?
— David Sutherland
It’s a good question, but I would turn it around. I don’t think that realism requires you do this, although this quote from Barry Smith does rather distinguish between simplifications (i.e. not the most detailed classification you can come up with) and reality.
I am beginning to suspect that for you everything is a simplification (model) — for me, functions are part of reality; they are not simplifications; I am not interested in simplifications.
— Barry Smith http://groups.google.com/group/bfo-discuss/msg/865e601864fbc2dc
The problem, though, is that realism elevates “reality” above all else. I think that this is wrong. Of course, in any scientific discipline, we should by aiming to model the experimental data that we have. But this is not all we need to do. As any statistician will tell you, models are compromises. It is very easy to build a model that perfectly represents the data that you have; you just build a model with as many variables as data points. The model will fit perfectly to the data, but ultimately the model is useless, since it lacks explanatory power. We need use cases, we need simplifications and sometimes we will need multiple representations of the same thing; there are examples galore in my paper [cite]10.1371/journal.pone.0012258[/cite]. In fact, Chris Mungall gives a good example when he talks about dispositions and their status as being real:
In fact, I have a particular problem with dispositions being “real” - BFO asks me to believe there are an infinite number of real but unrealized and perhaps wildly improbable dispositions floating around me every second
— Chris Mungall
And later he gives the solution.
taking a hard-headed pragmatic approach - e.g. avoid weirdo classes that don’t correspond to a term a normal scientist would use; introduce distinctions that give you the desired results to queries and inferences)
— Chris Mungall
In otherwords, reality is important. But we also need use cases, we need community norms, and we need applications. If ontologies do not fit with these, then can be as “real” as you like, but they are still wrong.