How does one do an ontological investigation?

It’s a question I’ve been asked several times. Students see ontology papers in venues such as FOIS, EKAW, KR, AAAI, Applied Ontology, or the FOUST workshops and it seems as if all that stuff just fell from the sky neatly into the paper, or that the authors perhaps played with mud and somehow got the paper’s contents to emerge neatly from it. Not quite. It’s just that none of the authors bothered to write a “methods and methodologies” or “procedure” section. That it’s not written doesn’t mean it didn’t happen.

To figure out how to go about doing such an ontological investigation, there are a few options available to you:

• Read many such papers and try to distill commonalities with which one could  reverse engineer a possible process that could have led to those documented outcomes.
• Guess the processes and do something, submit the manuscript, swallow the critical reviews and act upon those suggestions; repeat this process until it makes it through the review system. Then try again with another topic to see if you can do it now by yourself in fewer iterations.
• Try to get a supervisor or a mentor who has published such papers and be their apprentice or protégé formally or informally.
• Enrol in an applied ontology course, where they should be introducing you to the mores of the field, including the process of doing ontological investigations. Or take up a major/minor in philosophy.

Pursuing all options likely will get you the best results. In a time of publish-or-perish, shortcuts may be welcome since the ever greater pressures are less forgiving to learning things the hard way.

Every discipline has its own ways for how to investigate something. At a very high level, it still will look the same: you arrive at a question, a hypothesis, or a problem that no one has answered/falsified/solved before, you do your thing and obtain results, discuss them, and conclude. For ontology, what hopefully rolls out of such an investigation is what the nature of the entity under investigation is. For instance, what dispositions are, a new insight on the transitivity of parthood, the nature of the relation between portions of stuff, or what a particular domain entity (e.g., money, peace, pandemic) means.

I haven’t seen cookbook instructions for how to go about doing this for applied ontology. I did do most of the options listed above: I read (and still read) a lot of articles, conducted a number of such investigations myself and managed to get them published, and even did a (small) dissertation in applied philosophy (mentorships are hard to come by for women in academia, let alone the next stage of being someone’s protégé). I think it is possible to distill some procedure from all of that, for applied ontology at least. While it’s still only a rough outline, it may be of interest to put it out there to get feedback on it to see whether this can be collectively refined or extended.

With X the subject of investigation, which could be anything—a feature such as the colour of objects, the nature of a relation, the roles people fulfill, causality, stuff, collectives, events, money, secrets—the following steps will get you at least closer to an answer, if not finding the answer outright:

1. (optional) Consult dictionaries and the like for what they say about X;
2. Do a scientific literature review on X and, if needed when there’s little on X, also look up attendant topics for possible ideas;
3. Criticise the related work for where they fall short and how, and narrow down the problem/question regarding X;
4. Put forth your view on the matter, by building up the argument step by step; e.g., as follows:
   1. From informal explanation to a possible intermediate stage with sketching a solution (in ad hoc notation for illustration or by abusing ORM or UML class diagram notation) to a formal characterisation of X, or the aspect of X if the scope was narrowed down.
   2. From each piece of informal explanation, create the theory one axiom or definition at a time.
   Either of the two may involve proofs for logical consequences and will have some iterations of looking up more scientific literature to finalise an axiom or definition.

5. (optional) Evaluate and implement.
6. Discuss where it gave new insight, note any shortcomings, and mention new questions it may generate or problem it doesn’t solve yet, and conclude.

For step 3, and as compared to scientific literature I’ve read in other disciplines, the ontologists are a rather blunt critical lot. The formalisation stage in step 4 is more flexible than indicated. For instance, you can choose your logic or make one up [1], but you do need at least something of that (more about that below). Few use tools, such as Isabelle, Prover9, and HeTS, to assist with the logic aspects, but I would recommend you do. Also within that grand step 4, is that philosophers typically would not use UML or ORM or the like, but use total freedom in drawing something, if there’s a drawing at all (and a good number would recoil at the very word ‘conceptual data modeling language’, but that’s for another time), and likewise for many a logician. Here are two sample sequences for that step 4:

A visualization of the ‘one definition or axiom at a time’ option (4b)

A visualization of the ‘iterating over a diagram first’ option (4a)

As an aside, the philosophical investigations are lonesome endeavours resulting in disproportionately more single-author articles and books. This is in stark contrast with ontologies, those artefacts in computing and IT: many of them are developed in teams or even in large consortia, ranging from a few modellers to hundreds of contributors. Possibly because there are more tasks and the scope often may be larger.

Is that all there is to it? Sort of, yes, but for different reasons, there may be different emphases on different components (and so it still may not get you through the publication process to tell the world about your awesome results). Different venues have different scopes, even if they use the same terminology in their respective CFPs. Venues such as KR and AAAI are very much logic oriented, so there must be a formalization and proving interesting properties will substantially increase the (very small) chance of getting the paper accepted. Toning down the philosophical musings and deliberations is unlikely to be detrimental. For instance, our paper on essential vs immutable part-whole relations [2]. I wouldn’t expect the earlier papers, such as on social roles by Masolo et al [3] or temporal mereology by Donnelly and Bittner [4], to be able to make it through in the KR/AAAI/IJCAI venues nowadays (none of the IJCAI’22 papers sound even remotely like an ontology paper). But feel free to try. IJCAI 2023 will be in Cape Town, in case that information would help to motivate trying.

Venues such as EKAW and KCAP like some theory, but there’s got to be some implementation, (plausible) use, and/or evaluation to it for it to have a chance to make it through the review process. For instance, my theory on relations was evaluated on a few ontologies [5] and the stuff paper had the ontology also in OWL, modelling guidance for use, and notes on interoperability [6]. All those topics, which reside in the “step 5” above, come at the ‘cost’ of less logic and less detailed philosophical deliberations—research time and a paper’s page limits do have hard boundaries.

Ontology papers in FOIS and the like prefer to see more emphasis on the theory and what can be dragged in and used or adapted from advances in analytic philosophy, cognitive science, and attendant disciplines. Evaluation is not asked for as a separate item but assumed to be evident from the argumentation. I admit that sometimes I skip that as well when I write for such venues, e.g., in [7], but typically do put some evaluation in there nonetheless (recall [1]). And there still tends to be the assumption that one can write axioms flawlessly and oversee consequences without the assistance of automated model checkers and provers. For instance, have a look at the FOIS 2020 best paper award paper on a theory of secrets [8], which went through the steps mentioned above with the 4b route, and the one about the ontology of competition [9], which took the 4a route with OntoUML diagrams (with the logic implied by its use), and one more on mereology that first had other diagrams as part of the domain analysis to then go to the formalization with definitions and theorems and a version in CLIF [10]. That’s not to say you shouldn’t do an evaluation of sorts (of the variety use cases, checking against requirements, proving consistency, etc.), but just that you may be able to get away with not doing so (provided your argumentation is good enough and there’s enough novelty to it).

Finally, note that this is a blog post and it was not easy to keep it short. Alleys and more explanations and illustrations and details are quite possible. If you have comments on the high-level procedure, please don’t hesitate to leave a comment on the blog or contact me directly!

References

[1] Fillottrani, P.R., Keet, C.M.. An analysis of commitments in ontology language design. Proceedings of the 11th International Conference on Formal Ontology in Information Systems 2020 (FOIS’20). Brodaric, B and Neuhaus, F. (Eds.). IOS Press, FAIA vol. 330, 46-60.

[2] Artale, A., Guarino, N., and Keet, C.M. Formalising temporal constraints on part-whole relations. Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR’08). Gerhard Brewka, Jerome Lang (Eds.) AAAI Press, pp 673-683.

[3] Masolo, C., Vieu, L., Bottazzi, E., Catenacci, C., Ferrario, R., Gangemi, A., & Guarino, N. Social Roles and their Descriptions. Proceedings of the 9th International Conference on Principles of Knowledge Representation and Reasoning (KR’04). AAAI press. pp 267-277.

[4] Bittner, T., & Donnelly, M. A temporal mereology for distinguishing between integral objects and portions of stuff. Proceedings of Association for the Advancement of Artificial Intelligence conference 2007 (AAAI’07). AAAI press. pp 287-292.

 [5] Keet, C.M. Detecting and Revising Flaws in OWL Object Property Expressions. 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW’12), A. ten Teije et al. (Eds.). Springer, LNAI 7603, 252-266.

[6] Keet, C.M. A core ontology of macroscopic stuff. 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW’14). K. Janowicz et al. (Eds.). Springer LNAI vol. 8876, 209-224.

[7] Keet, C.M. The computer program as a functional whole. Proceedings of the 11th International Conference on Formal Ontology in Information Systems 2020 (FOIS’20). Brodaric, B and Neuhaus, F. (Eds.). IOS Press, FAIA vol. 330, 216-230.

[8] Haythem O. Ismail, Merna Shafie. A commonsense theory of secrets. Proceedings of the 11th International Conference on Formal Ontology in Information Systems 2020 (FOIS’20). Brodaric, B and Neuhaus, F. (Eds.). IOS Press, FAIA vol. 330, 77-91.

[9] Tiago Prince Sales, Daniele Porello, Nicola Guarino, Giancarlo Guizzardi, John Mylopoulos. Ontological foundations of competition. Proceedings of the 10th International Conference on Formal Ontology in Information Systems 2020 (FOIS’18). Stefano Borgo, Pascal Hitzler, Oliver Kutz (eds.). IOS Press, FAIA vol. 306, 96-109.

[10] Michael Grüninger, Carmen Chui, Yi Ru, Jona Thai. A mereology for connected structures. Proceedings of the 11th International Conference on Formal Ontology in Information Systems 2020 (FOIS’20). Brodaric, B and Neuhaus, F. (Eds.). IOS Press, FAIA vol. 330, 171-185.