Relating Processes and Events for Granularity-neutral Modeling

 

Abstract

We investigate an approach of classifying temporally extended entities (occurrents) which distinguishes events and processes by means of their inner structure and their relation to change. By assuming processes to be homogeneous up to a certain intrinsic granularity, we develop a suggestion on how to model events and processes in a way that is to a great extent neutral to granularity issues.

Author

Niels Grewe

University of Rostock, Rostock, Germany

Introduction

Biomedical reality is full of changes and processes, things that unfold in time: The citric acid cycle, an infection of the sinuses, the beating of a heart, an appendectomy, the growing of a tree: These examples of changes are affecting things on different levels of granularity and show a great deal of variation. Despite efforts in various top-level ontologies, no uniform treatment of such “unfolding”, temporal entities has emerged in biomedical ontologies. Rather, specialized accounts have sprung up to treat the needs of particular disciplines (e.g. in the fields of systems biology (cf. LeNovere 2007) or epidemiology (cf. Kawazoe et al. 2008). This is unfortunate from a data integration perspective, especially if entities on multiple layers of granularity are involved. For example, epidemiological ontologies would benefit from being capable of integrating information about the biochemical workings of antibiotics.

In this paper we take a small detour to motivate a suggestion on how a integration-friendly ontology of temporally unfolding entities should look like. This detour draws upon ideas of Glaton and Mizoguchi \cite{Galton:Mizoguchi:2009} about the traditional ontological distinction between occurrents and continuants, a simplified model that does not account for “changes” of occurrents, which are important in their own right. We then further distinguish mutable and immutable entities and use the categories of events and processes thus characterised to highlight how integration between different levels of granularity could be achieved.

Continuants and Occurents

The Standard Account

In most attempts at ontologically adequate modeling one distinction is ubiquitous: The distinction between entities that are present as a whole at every moment of their existence (called “continuants” or “endurants”), and those which are only partially present at each moment (called “occurrents” or “perdurants”, cf. Simons 1987). Hence, top-level ontologies such as DOLCE (cf. Masolo et al. 2003) or BFO (cf. Grenon and Smith, 2004) adopt this distinction as the primary means to partition the entities in the world.

At first sight, this distinction aligns nicely with everyday experience and scientific method: Continuants, both the familiar, independent variety (e.g. a DNA molecule or a scalpel) and the more outlandish dependent continuants (e.g.the weight of the DNA molecule or the colour of the scalpel) do not have tardy parts: If they are present at all, they are wholly present. Occurrents, on the other hand are fleeting, we never experience more than a single “slice” of them at once. At a given moment, we will, for example, observe exactly one phase of a mitosis, but never, say, prophase and metaphase of one and the same mitosis together.

This neat picture has another important consequence: Only continuants are entities that endure in time and hence only continuants can be the subjects of change because in order to speak of change, we need to ascribe different properties to them at different instants. For example, a scalpel used during an appendectomy can be the same scalpel at the beginning and the end of the procedure, even though it might have undergone some changes in the meantime (e.g. it was located on the table at and in the hands of the surgeon at , or it may have been quite sharp at and rather blunt at ).

The same cannot be said for occurrents. Since the parts of the appendectomy present at and are clearly distinct, claiming that the appendectomy has changed would be as absurd as claiming that the scalpel “changed”, just because the blade exhibits characteristics different from those of the handle. Consequentially, the division between continuants and occurrents lines up with the distinction of entities which allow for change and those which do not.

Mutable Occurents

Still, this standard “continuants vs. occurrents”-picture has been repeatedly challenged. Often those challenges have been put forward by ontologists who strive for extreme parsimony and try to achieve an adequate description of reality with just a minimal set of categories. Some suggest that continuants should be perceived as four-dimensional space-time worms, which then also encompass what we call “occurrents” (cf. Quine 1960). Others, in a loosely Whiteheadian tradition (cf. Whitehead 1929), advocate that continuants should be absorbed to occurrents (Seibt 1997).

Against those, at least in part reductive, proposals, the intuitive appeal of the assumption that continuants and occurrents are distinct categories that are divided because of substantial ontological differences has to be stressed. We side with the authors of the BFO (cf. Grenon and Smith 2004) in assuming that both a diachronic, occurrent-centered and a synchronic, continuant-centered description are necessary and adequate representations of biomedical reality.

Still, even if one accepts the general distinction, much can be found at fault within the confines of that framework. Most importantly, Galton (2006) and Galton and Mizoguchi (2009) have raised concerns about the nature of different classes of occurrents. They argue that specific occurrents can actually undergo changes. Our alignment of continuants as mutable entities and occurrents as immutable entities would then be incorrect.

The primary justification for this is that there are many propositions that ascribe changes to occurrents. Some of these appear quite natural in everyday language. For example, someone might be tempted to say that “the snowing got more intense during the night.” Here different intensity qualities are assigned to a perduring episode of snowing at two different points of time. Likewise, many properties of physical systems, which can be described by differential equations, can often readily be explained by appealing to changes of an occurrent. Key examples would be the concepts of damping or acceleration. Damping describes the change of amplitude in an oscillation process and acceleration the change of velocity in a motion process.

The fact that one usually ascribes the corresponding property to a participant of the process (for example, “acceleration of a body” or, to take a simpler example, “velocity of a body”) is only a superficial counterargument. Such descriptions rather serve to illustrate a peculiar feature of scientific parlance: The (in this case: physical) models are usually reduced to their bare minimum in order to capture only those factors that are essential for the system under study. Hence the phrase “velocity of a body” arises as a convenient shorthand for “velocity of a body participating in motion process p relative to an inertial system s“. But this shorthand is only unambiguous for simple models. One can easily see this when asked to determine the velocity of the earth: What is meant by “velocity of the earth”? The velocity that characterises the motion around the earth’s axis or to the velocity that characterises the motion of the earth around the sun? In this case, one cannot do away with the reference to the motion process and “short-circuit” to ascribing the velocity to the object alone. Hence, if the velocity changes, we might be compelled to ascribe the change (at least partially) to the motion process (One is not, however, compelled to claim that the change is effected by the process. I take the conservative but very plausible stance that there are no free-floating changes of processes: Every change to a process is due to an underlying change in the participating continuants)

This observation is clearly at odds with the intuition that occurrents do not undergo change. One is thus obligated to either provide some rationale for overriding the intuition or to provide a analysis that avoids the conclusion that occurrents do change.

Events and Processes

The solution that Galton and provide for this conundrum rests on the distinction between events and processes. (Caveat lector: The terminological confusion about the terms “event” and “process” is Babylonian in extent. I will use them here to denote two sibling-classes under the parent Occurrent. Their specific differences will become clear in what follows.) This distinction is, in turn, modeled in analogy to the distinction of objects and matter on the continuant side.

Events are said to be analogous to objects in as far as both “are discrete individuals which may be referred to using count nouns.” (Galton and Mizoguchi, 2009, 74) This is certainly true: Just as the surgeon can count the scalpels and hemostats on the operating table, he can count the appendectomies and colonoscopies he has performed. Each of them will be a single, clearly delineated individual.

Closely related to this feature of “discreteness” is that of “definite extension”: Just as each object takes up a fixed amount of space, each event occupies a fixed time interval. (The extension of either events or objects might, however, exhibit some degree of fuzzyness.)

Additionally both categories share certain constraints on their internal structure: Both are “non-dissective”, or heteromerous. This means that no part of the original whole is still of the same kind as the whole. The blade of a scalpel is a blade, not a scalpel, and the initial incision during the appendectomy is an incision, not an appendectomy.

On the other side of the spectrum, an equivalent analogy is drawn between matter and processes, which are characterised by the inverse set of characteristics: Matter is not discrete in the sense that it constitutes a cleanly delineated individual, it is rather “the ‘stuff’ from which those individuals are made” (Galton and Mizoguchi 2009, 74). Hence, the hemostat will be made of steel, and steel alone does not yet carry any clear criterion of individuation since we can never say that there is complete “steel”, only complete chunks of steel.

The same is said to be true for processes with regard to events: The incision event that is the first part of the appendectomy is made up from a cutting process. The cutting process, as such, does not have a definite criterion of what makes a “complete” cutting. The incision event in the appendectomy, on the other hand, has one: It is complete once the intended endpoint (e.g. McBurney’s point) has been reached by the scalpel. Again, this also means that there is no definite extension for either matter or processes.

Table 1. Analogous features of objects, events, matter, and processes according to Galton and Mizoguchi (2009).

 

Spatial/Temporal

Discreteness

Definite

extension

Dissectivity

Object

+

+

Event

+

+

Matter

+

Process

+

But the most important analogy between matter and processes is their dissectivity: Save for granularity issues that we will have to deal with later on, a certain kind of matter can be arbitrarily divided into smaller portions and still be of the same kind. The same is arguably true for processes: If cutting is going on from until , cutting is also going on from until .

This notion of dissectivity (also called homogenity or homoeomericity) is one key ingredient to solving the change conundrum: In as far as occurrents are non-dissective (i.e. events), they cannot change because the selfsame event is only completely present over the whole time interval it occupies and there is no point in claiming that a change took place from until because there would not be the same entity present at both points in time. (cf. Galton and Mizoguchi 2009, 78)

As far as occurrents are dissective (i.e. processes), it seems to be possible to speak of change. The reasons are as follows: If one assumes that a process p is going on between and , the same process is also going on at every such that due to its dissectivity. Thus one can identify the process p at multiple points in time and ascribe different qualities to it at those timepoints. The transition between them amounts to something that is at least analogous to the change of a continuant. It needs to be stressed that this is only possible because a process is dissective: There is at least one (non-contingent) aspect about it that stays the same while the process is going on.

This position is thus on the one hand different from views that merely use dissectivity as a classification criterion for distinguishing occurrents that effect changes from those that merely describe the continued existence of a state, which is how DOLCE introduces the categories of “stative” and “eventive” occurrents. (cf. Masolo et al. 2003, 17)

On the other hand there is a marked difference to views such as that of Rowland Stout, who makes similar claims to continuant-like characteristics of processes but does not require them to be dissective. He instead appeals to an allegedly primitive human capacity of “tracking” things (i.e. objects or processes) through time to account for the reidentification of a process through time. (cf. Stout 2003, 148) Since there is no explanation on offer for this capacity, it has a certain air of obscurum per obscurius, which makes it less useful for the purpose at hand.

Galton and Mizoguchi conclude that a process seems to be “more ike an object than an event, calling into question the neat division into continuants and occurrents.” (Galton and Mizoguchi 2009, 79) Their complete solution is more sophisticated and quite revisionary in that it describes objects as “interfaces” between processes (Galton and Mizoguchi 2009, 92). Since scientific ontologies should be founded on well-understood and uncontroversial principles I will not discuss it here but instead restrict the discussion to the granularity issues that are crucial in this context.

Process/Event Relations and Intrinsic Granularity

Temporal Windows

Assuming matter and processes to be homogeneous is a fitting abstraction if one tries to expound the conceptual similarities between the two categories. It is not, however, an adequate principle for concrete modeling. Matter may be

dissective on the macro- or mesoscale but on the microscale, there are limits to dissectivity.

When one start dividing a given portion of water, one will at first obtain different portions of the same kind: But that is no longer true once one has divided the portion that only consists of two water molecules. Any further division will produce entities that are no longer of the same kind, for example a hydroxide anion and a proton. Hence, the molecule is the natural grain of the divisible water-stuff (cf. Jansen and Schulz, 2010).

Such intrinsic levels of granularity play an important role in the definition of processes as well. For example, an episode of walking can only be divided into further episodes of walking until the granularity of a single step has been reached. The same is already true for very basic physical processes, like the emission of a sound at a certain frequency f, which can only be subdivided into intervals that last at least seconds.

According to Galton and Mizoguchi, these intrinsic granularities can be used to define “temporal windows” for processes (Galton and Mizoguchi 2009, 83–85). These windows are time slots which are just long enough so that the characteristics of the process kind in question can be realised. Hence, for a walking process, the temporal window will have the duration of a single step and for a process of a bacterial infection spreading, the temporal window will accommodate individual cell divisions.

When a process is going on, the temporal window moves along with the present temporal extension of the process and might even shrink or grow as needed, for example if the person walking slows its pace or if the rate of cell division in a bacteria colony increases. Since for each temporal window the qualities of the process can be determined, the succession of different qualities amounts to the changes a process undergoes.

But the temporal window of a process is different from its temporal parts: The temporal parts of a walking process are the individual movements of the left and the right leg, and those of the spreading process of a bacterial infection are the various phases of the single cell divisions. Neither of these constitutes the complete processes they are temporal parts of.

Temporal windows are more like “temporary parts” (I am borrowing this term from Stout (2003, 153), who uses it in a similar manner) of the process: At every temporal window, the same process is wholly present, but each temporal window is only present during a small duration of the time that the process is going on. Just like, for example, most (or probably all) of my epithelial cells are only part of my body for a short period of time, but my body is still present as a whole during each of those periods.

Unfortunately, the “temporary part of”-relation seems rather arcane. With continuants, it clearly corresponds to temporally indexed spatial parthood (“x is (spatial) part of y at t“, but this is clearly not an option for processes, because what is needed is a relation between two occurrents. One potential candidate is a constitution relation between occurrents. We would then read “y (temporally) constitutes x“, as saying that a process x is constituted by an occurrent y during the duration of y. I will use this as a rough approximation of what is needed here.

Interrelation between Processes and Events

Events as Process-ChunksWith these clarifications we can turn our attention to the interrelations between processes and events Fortunately the model just developed for dealing with change ascriptions to processes also proves to be very useful to clarify those interrelations To do this it is useful to consider the analogy from the continuant categories of matter and object again Considered carefully matter is a rather abstract category. In the reality we experience there is no such thing as “raw” matter: We never see steel or water by themselves but instead chunks of steel and portions of water Water and steel are still the stuff that the chunks and portions are made of but we always need to assign a definite extension to them

With processes, things are rather similar. We never come across entities which are just walking or cutting. What we experience and talk about are rather concrete episodes of walking or cutting. In this case, by adding temporal extension as a delimiting factor, we create an event from the process. For example “the episode of walking from 5:00pm to 5:30pm” would describe an event that delimits, and hence is made of or constituted by, a walking process. Events are thus “chunks” of processes, (Galton and Mizoguchi 2009, 82) which is unsurprising given the fact that the distinction between processes and events was motivated by looking the way matter and objects relate.

Processes as Event-Masses But there is an additional type of relation between processes and events. This can be seen when one tries to answer the following question: What kind of thing fits into temporal windows? It is clear that we are dealing with an occurrent here, but are we dealing with a mutable or immutable entity? Since temporal windows are aligned to the intrinsic granularity of the process they are temporal windows of, they seem to require a specific time interval to be specified. But if that is the case, the entity contained in each window is already fixed by the boundaries of the window which would forbid it from changing. It thus needs to be an event.

The temporal windows of a process contain events that are atomic with regard to the process: A walking process is (temporally) constituted by a series of step events. But since events are only complete when they are already gone by, this introduces a neat little puzzle: Suppose I am walking across the street and in the middle of a step somebody pushes me so that I do not get hit by an approaching bus: Would I be right to say “I was walking across the street when I was pushed.”? On the face of it, and quite counter-intuitively, it seems that this is not the case: If the temporal windows of a walking process can only be filled by (complete) step events, I was only walking until I set out to make the last step before being pushed.

One might try to remedy this by allowing the last temporal window of a process to be filled by the initial segment of the usual process-grain event as well. But there are other cases where this does not seem plausible. For example, the process of flashing a light twice a second would have temporal windows with a duration of 1s. In each window, the process would be constituted by an event of two flashes, which decomposes into two temporal parts with one flash each. If after some time, I switch to flashing the light only once per second, I would be compelled to include the first flash of the new sequence as belonging to the previous process.

The semantics of such interruptions and process replacements seem to be rather subtle and I am inclined to assume that the question is a material one that needs to be answered on a case by case basis.

Still, the assumption that the temporal windows of a process are filled by events is a very useful one when combined with the assumption that some events are made up from processes. (Since events can be specified by supplying completely arbitrary fiat-boundaries, not all events can be constituted by processes (cf. Stout 2003, 154)). We can then have processes, which constitute events, which constitute processes (because they form temporal windows). And since this structure can be nested, it opens an avenue for integrating different levels of granularity.

Let us take the growth of an cancerous ulcer as an example. The intrinsic granularity of this growth process is the single cell division and at each point in time the growth process will be temporally constituted by at least one and potentially a large number of cell division events. A cell sdivision in turn is an event with multiple parts (in this case know as phases). If we look at, for example, the anaphase, we can see that it, again, has two parts: The separation of the sister chromosomes and their movement of the respective centrosomes. The event of the chromosomes moving to the centrosomes is in turn constituted by a movement process which can be analysed further into the events it is made up from.

This way, multiple levels of granularity can be combined into a consistent picture without introducing any tight coupling: If we are not interested in the specifics of how chromosomes move to the centrosomes, we can just leave it at describing their movement as an event that is atomic with regard to the process on the higher level. This kind of modeling can be regarded as granularity-neutral. It allows for integration with upper and lower levels where needed, but it does not force modellers to adopt those levels if they have no use for them.

Conclusion

The problem of whether occurrents can be the subjects of change is a particularly difficult one since one is always at risk of mistaking linguistic artifacts or mere colloquialisms for proper ontological facts. It is thus useful to show that this kind of scheme has additional merit apart from a proper treatment of mutability. As it turns out, the consideration of this problem does indeed lead to a new perspective on granularity issues that pertain to the ontology of events. Differentiating between processes and events and encapsulating them in one-another can reduce the need for a fixed base-granularity in event descriptions, which seems to be useful for projects that need to integrate information from various levels of reality.

Designing an concrete ontology that implements the suggestions made in this paper would, however, require quite some work to achieve a working formal definition of process and event mereology as well as of the constitution relation that seems to be required to properly talk about processes and the atomic events they are made up from.

Acknowledgements

This work is supported by the German Science Foundation (DFG) as part of the research project “Good Ontology Design” (GoodOD). Many thanks go to Ludger Jansen and Johannes Röhl (Rostock) for challenging and fruitful discussions on the topic of this paper and to four anonymous reviewers for their insightful comments.

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