I once had cause to refer, somewhat mischievously, to “a kind of pasta from Tuscany, which is almost identical to spaghetti, but slightly different”; this was on a mailing list that was used by many Italians. It provoked the expected response; an offended Tuscan responded “I don’t know what you are talking about; but if you mean pici”, which I did, “it’s nothing like spaghetti”.

Recently, on the OBI mailing list, there has been much discussion about labels, markers or tracers. What ever you wish to call it, the basic idea is the same; a molecule which is easily detectable, is used to trace something else. This can involve adding a small amount of a radioactive isotope (P32). This makes it possible to follow the molecule (which is otherwise hard) by tracing the radiation (which is generally easy).

So, how do we model this? As with many parts of ontology building, it turns out to be not straight-forward; during this discussion, an email from Philipee Rocca-Serra which left me asking the question, are we being too specific? I will work through an example to show what I mean. Feel free to skip to the punchline if you choose.

Consider, for example, the following models; these are not directly taken from OBI, as I want to reduce the complexity for this article; rather they are in the general spirit of the models which raised these questions.

A label, or something that has been labelled is clearly part of an experimental design. It is not intrinsic to this entity, rather it appears to be a role that the entity is playing in the experiment. So:

Class: Label
       SubClassOf:
          Role

There are, of course, labels of many sorts. The main types that I can think of are radioactive, fluorescent and what I call adherent. So, we might add the following, with a few subclasses of adherent as explanation.

Class: RadioactiveLabel
       SubClassOf:
          Label

Class: FluorescentLabel
       SubClassOf:
          Label

Class: AdherentLabel
       SubClassOf:
          Label

Class: BiotinilaytedLabel
       SubClassOf:
           AdherentLabel

Class: AntigenicLabel
       SubClassOf:
           AdherentLabel

So far so good. However, for a label to be useful, it needs to be manufactured (often in a bespoke fashion, depending on the experiment being performed) and it needs to be detectable. So, we might add classes like so:

Class: LabellingProcess
       SubClassOf:
           Process
           has_output some Label

Class: LabellingDetectionProcess
       SubClassOf:
           Process
           has_input some
                  Sample contains some Label

Now we have three classes for every label type. We can deal with this by generating a cross-product, either at development time, or at the time of use if we are using OWL. However, we need something to tie together these classes. We need a concept to know that we need a RadioLabellingProcess to produce a RadioLabel which we detect in a RadioLabellingDetectionProcess. In short, we need a concept of Radiation, Radioactive or Radioactivity.

Class: RadioactiveEntity
    SubClassOf:
        IndependentContinuant,
        bears some Radioactivity

Class: RadioactiveLabel
    SubClassOf:
        Role,
        RadioactiveEntity

Class: RadiationDetector
    SubClassOf:
       detects some Radioactivity

Class: RadioactiveLabelProductionProcess
    SubClassOf:
       has_input some RadioactiveEntity

This is where the situation gets difficult. What kind of thing is Radioactivity? Taking the realist approach, we need to consider this carefully, determining what this universal is. So, starting from the top, it is fairly obvious that we have a Continuant. Next question, do we have a Dependent or IndependentContinuant. Again, this is fairly clear: radioactivity cannot exist without something to be radioactive, hence Radioactivity is a DependentContinuant.

We have a set of DependentContinuant‘s that Radioactivity could be. The concept Role does not fill well; this is usually ascribed by socially or, in this case, experimentally determined behaviour. Perhaps, Disposition would be better. However, this does not really fit either, as a Disposition is realised “under specific circumstances”. Now this is not true of radioactivity. Either something is radioactive or it is not, and if it is, then it is, to the best of our knowledge, radioactive under all circumstances. It appears, then, that Radioactivity is a Quality, because “it is exhibited if it inheres in an entity at all”.

If we follow the same logic with our other label types, initially, we come to the same conclusions. However, Fluorescence is not exhibited under all circumstances. It only happens when the label is illuminated with the right kind of light. So, Fluorescence appears to be a Disposition. Following a similar logic, this is also true of Adherent. So the best we can say about the property of the substance that makes it usable in labelling is that it is a RealizableEntity.

Having Radioactivity stand out in this way is a little unsatisfying. Let’s consider the logic again. One classic experimental form is the pulse-decay experiment. I can, for example, feed a rat with, say, radioactive phosphorus briefly. After this, you can trace the course of phosphorus. Now during the course of this experiment, the rat becomes radioactive and then ceases to be radioactive again. But, it is notably, the same rat. So, perhaps, the statement that things are either radioactive or not is wrong. Perhaps, it is not a Quality at all. The flaw in the logic is the assumption that because an atom is either radioactive or is not, therefore anything made up from atoms must be so. But an entity can have its atoms totally replaced and still be the same entity. In this case, what is true of a rat, is also true of its DNA. We can replace the atoms in a sample of DNA with other ones and still, have the same DNA. So, maybe, Radioactivity is a Quality at an atomic level of granularity, but is, after all, a Disposition at others.

Thinking further, however, maybe it is not a Quality at all. A mass of P32 is always radioactive, but a single atom? Perhaps not, since it only displays this when it decays. So, perhaps, it is a Disposition after all. However, this makes no sense, because dispositions are displayed under “specific circumstances”. Now, to the best of our knowledge, radioactive decay is stochastic — it is so random, that radioactivity is often used to generate randomness. We cannot specify the circumstances under which it happens, it just does. More over, after it displays the radioactivity, what has happened to the atom? Using the same argument as before, we could say that, like the rat, the atom still exists, it’s just that (some of) the elementary particles that make it up have changed. But this way, surely, madness lies, as “being phosophorus” would become some sort of dependent continuant, which the atom displays during its decay, while it happens to have the right number of protons. So, probably it makes more sense to say that, the decay process represents the end of the existence of the phosophorus atom and the beginning of a new atom (and a radioactive particle). In which case, even our original decision that Radioactivity is DependentContinuant is wrong. It’s not a DependentContinuant at all, it’s only a process which over as soon as it begins.

So, what have we achieved? Well, I would argue, not a great deal, except for a lot of discussion. More over, we have ended discussing very detailed issues about the physical properties of matter, when we started discussing an ontology of biomedical investigations. This might be entertaining, or it might be very dull, depending on your point-of-view. But, what we have failed to produce is a specific conclusion.

The problem here is realism. A realist ontology represents portions of reality, that is classes of things that really have instances. We have to ask these questions to try and determine whether Radioactivity exists and what kind of thing that it is. We can set realism against pragmatism. Previously, Robert Stevens has described the problems that this causes by preventing the ontologist from modelling “unicorns“, such as Newtonian mechanics, or canonical anatomies. The unicorn principle says, if it is useful to model a concept in an ontology, then often we should. Here, I introduce what I call the “Pici principle” — if it is not useful to model a concept then we should not. As a British native, pasta is pasta; it all tastes much the same to me. Generally, I do not need the ability to be able to distinguish pici and spaghetti, unless I want to provoke a response from an over-excitable Tuscan. The sensible course is not to get involved in the discussion in the first place.

The same applies in this instance. There is a clear use case for the concept of Radioactivity; without it, we cannot say that a radio-label is radioactive, or that a fluorescence detector is not going to work detecting it. But to achieve this use case, we do not need to understand very deeply what Radioactivity is. Describing it as a DependentContinuant is enough, and it will fulfil the use cases. It will not enable us to ask questions about which kind of labels detect qualities and which detect dispositions. But in the absence of a use case, this is not an issue.

A chemist may care, and may want to classify radioactivity further. This is fine; as with pasta, we can safely leave these issues to someone else, in the knowledge that they are probably better qualified to give an answer anyway. So long as they decide that Radioactivity is a DependentContinuant, it does not matter to us what kind of DependentContinuant; we have said nothing incorrect. So, our ontology will integrate with theirs, without change to either. By being as vague as our use cases allow us, we have actually increased the ability of our ontology to integrate with others.

In short, the pici principle encapsulates the idea that deciding what we should not model in an ontology is as important as what we should model. And this decision comes from use cases, not reality.

3 Comments

  1. Chris Mungall says:

    Interesting article, many good points.

    I consider myself a pragmatic realist (I was recently taken to task by a realist for being a pragmatist, if I was forced to choose sides I would be on the side of the pragmatists).

    I would say the problem here is “realist overreach” into the murky world of properties. Unlike with physical entities (isotopes, rats, pasta) or processes (radiation, fluorescence) we have a harder time pointing to things in order to resolve debates about what should go in our ontology or which distinctions to make. This leads to non-useful debates and analysis paralysis.

    It’s particularly hard to point to a disposition (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: my disposition to raise my right eyebrow in the manner of Roger Moore, rub my tummy, fart if you pull my left pinkie, quit my job and join the circus, sing an ABBA song in a comedy Slovenian accent, throw custard pies at presenters during the next ICBO).

    Trying to assert dubious sub-categories of DependentContinuant in advance is not useful and a recipe for pointless discussion, because it’s harder to use objective reality as a guide. A pragmatic approach would be to always model the physical entities and processes as named classes (taking a hardheaded ultra-realist approach – unicorns? NOT ON YOUR LIFE MATE; hallucinations/cheesy Athena posters of unicorns? SURE, KNOCK YOURSELF OUT, I DON’T CARE. Sorry Robert & Rob), and then to introduce properties where they are needed for modeling purposes (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).

    If distinctions such as disposition vs quality turn out to be important in the long run, then we infer them. For example, if this particular entity is always radiating then we can infer there’s a “quality” there. If this particular entity periodically radiates contingent on presence of some input, then we infer there’s a “disposition” lurking around. If I am singing an ABBA song right now, then I have the quality of singing an ABBA song (perhaps other qualities, such as being a terrible singer, and looking like a bit of an arse). If you always sing ABBA songs after drinking three pints of lager, then we can model this precisely as such (e.g. “P(Phill-sings-ABBA|>=3 pints)=1”), and, if we so choose, infer that this is a “disposition” (based on the “if” or “P(X|Y)”). No need to argue about the category in advance. Focus on the important things (e.g. building a useful probabilistic model that predicts ontologists singing ABBA, so we are forewarned and can get out the pub).

    Nothing could be more realist than this (at least according to my simplistic boneheaded sub-Newtonian can-you-point-at-it flavour of realism).

    I would perhaps go further and relabel the ugly “dependent continuant” as “abstract”, “property” or “reified relationship”, but that’s enough heresy for one day..

    TL;DR – realism works in general but “dependent continuant”s are dubious with regards to their claims to carve reality at the joints.

    Cheers
    Chris

  2. dosumis says:

    “In short, the pici principle encapsulates the idea that deciding what we should not model in an ontology is as important as what we should model. And this decision comes from use cases, not reality.”

    I agree completely, but what realist principle says you need to give something the most detailed classification you can come up with? It’s not unheard of for conceptualists to get tied up in arguments about dependent continuants and their various flavours. Whether you are a conceptualist or a realist, you’re not using your time well if you spend most of it worrying about abstruse classification issues that are neither of interest to scientists nor useful for basic sanity checking.

  3. Phil Lord says:

    “Realism” moves backward and forward in its principles. It is often very hard to determine what those principles are, because they change rapidly over time, often without being explicit. So you will excuse me, if I turn the question around and ask instead what realist principle is it that you can use to say “well, even though the experimental data says this, we are going to choose NOT to model it, because it is too complex”? Realism elevates “reality” above all else, and this is not a sensible way of operating. As my post says, we need use cases also.

    The general antipathy toward using an appropriate level of simplification can be seen here however, in this quote from Barry Smith. As you know, I do not have a philosophical issue with “realism” in general — I just don’t care — but with the particular strand of it that is inherent in BFO, which Barry pushes.

    “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. ”

    http://groups.google.com/group/bfo-discuss/msg/865e601864fbc2dc

    I agree with you,though. Anyone can get tied up in overly complicated arguments about some minor point (I hold my hand up here). We need to work on strategies to get around this; I think many of these do and will come from software engineering, and in particular from the agile and decoupled methodologies, rather than the waterfall approach that realism suggests.

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