The ontology engineering course starting this Monday at the Knowledge Representation and Reasoning group at Meraka commences with the question What is an ontology? In addition to assessing definitions, it touches upon long-standing disagreements concerning if ontologies are about representing reality, our conceptualization of entities in reality, or some conceptualization that does not necessarily ascribe to existence of reality. The “representation of reality school” is advocated in ontology engineering most prominently by Barry Smith and cs. and their foundational ontology BFO, the “conceptualization of entities in reality school” by various people and research groups, such as the LOA headed by Nicola Guarino and their DOLCE foundational ontology, whereas the “conceptualization irrespective regardless reality school” can be (but not necessarily is) encountered in organisations developing, e.g., medical ontologies that do not ascribe to evidence-based medicine to decide what goes in the ontology and how (but instead base it on, say, the outcome of power plays between big pharma and health insurance companies).
Due to the limited time and scope of this and previous courses on ontology engineering I taught, I mention[ed] only succinctly that those differences exist (e.g., pp10-11 of the UH slides), and briefly illustrate some of the aspects of the debate and their possible consequences in practical aspects of ontology engineering. This information is largely based on a few papers and extracting consequences from that, the examples they describe and that I encountered, and the discussions that took place at the various meetings, workshops, conferences, and summer schools that I participated in. But there was no nice, accessible, paper that describes de debate—or even part of it—more precisely and is readable also by ontologists who are not philosophers. Until last week, that is. The Applied Ontology journal published a paper by Gary Merrill, entitled Ontological realism: Methodology or misdirection? , that assess critically the ontological realism advocated by Barry Smith and his colleague Werner Ceusters. Considering its relevance in ontology engineering, the article has been made freely available, and in the announcement of the journal issue, its editors in chief (Nicola Guarino and Mark Musen) mentioned that Smith and Ceusters are busy preparing a response on Merrill’s paper, which will be published in a subsequent issue of Applied Ontology. Merrill, in turn, promised to respond to this rebuttal.
But for now, there are 30 pages of assessment on the merits of, and problems with, the philosophical underpinnings of the “realism-based approach” that is used in particular in the realm of ontology engineering within the OBO Foundry project and its large set of ontologies, BFO, and the Relation Ontology. The abstract gives an idea of the answer to the question in the paper’s title:
… The conclusion reached is that while Smith’s and Ceusters’ criticisms of prior practice in the treatment of ontologies and terminologies in medical informatics are often both perceptive and well founded, and while at least some of their own proposals demonstrate obvious merit and promise, none of this either follows from or requires the brand of realism that they propose.
The paper’s contents backs this up with analysis, arguments, examples, and bolder statements than the abstracts suggests.
For anyone involved in ontology development and interested in the debate—even if you think you’re tired of it—I recommend reading the paper, and to at least follow how the debate will unfold with responses and rebuttals.
My opinion? Well, I have one, of course, but this post is an addendum to the general course page of MOWS’10, hence I try to refrain from adding too much bias to the course material.
UPDATE (27-7-2010): On whales and apples, and on ontology and reality: you might enjoy also “Moby Dick: an exercise in ontology”, written by Lorne A. Smith.
 Gary H. Merrill. Ontological realism: Methodology or misdirection? Applied Ontology, 5 (2010) 79–108.
If you agree that “ontology” is the new “conceptual data model” (many ontologies are not even this) then have a look at “Data Modeling: Theory and Practice” by Graeme Simsion. He wrote a whole PhD about the question whether (conceptual) data modeling is a descriptive process or a design process and his results are well-founded. My all-time favorite is William Kent’s “Data and Reality” from 1978. The essay The Many Forms of a Single Fact should answer all questions. But ontology advocates don’t think that they can learn from publications dating back in the last millenium, do they? 😉
No, I do not agree that ontologies are the new incarnation of conceptual data models, even though at times they are used like that [*] and, as you say, some are not even that. I describe the differences during the ontology engineering courses and still intend to write down all the arguments, so your pointer to Graeme Simsion’s PhD (that I was not aware of) is well-received.
[*] As you’re pointing to the ORM foundation site, you might also want to have a look at the slides of least year’s workshop, where I gave a sneak preview of the Wonder system (with a genomics database as case study), which is an extension to the “Ontology-Based Data Access” (OBDA) approach using web-based graphical querying, and where I mentioned that COnceptual MOdel-based Data Access (COMODA) is a more appropriate term for this approach.
It strongly depends on how you define “ontology” but in its general form as “formal, explicit specification of a shared conceptualisation” (Gruber 1993) it is more located at the conceptual level (I read “shared conceptualisation” as synonym of “universe of discourse”). If you refer to ontologies as concrete implementations, for instance an OWL instance, then they are located on the logical level. In practice both is mixed anyway. I bet that most RDF-based ontologies have not been created based on any conceptual modeling language but on paper and pencil sketches which are directly implemented in code. Simsion concludes (p 345) that “the impact of the very substantial amount of academic work on modeling languages appears to be minimal, with modelers apparently preferring to work directly with the DBMS language”.
You might want to have a look at slides 6-18 of the introduction to ontology engineering course regarding definitions of an ontology and later on at the start of part II, the limitations of RDF(S) as an ontology language (OWL is an ontology language that aimed to address limitations of what you seem to call ‘RDF ontologies’). Regarding the former, and to put it mildly: Gruber’s phrase is fairly outdated, it’s limitations discussed extensively, and much more precise definitions provided. In case you are interested, I’d recommend you having a look at:
 Guarino, N. Formal Ontology in Information Systems. Proceedings of FOIS’98, Trento, Italy, June 6-8, 1998. IOS Press, Amsterdam, pp. 3-15
 Nicola Guarino. The Ontological Level: Revisiting 30 Years of Knowledge Representation. In: A.T. Borgida et al. (Eds.), Mylopoulos Festschrift. Springer LNCS 5600, 52–67. 2009.
 Nicola Guarino, Daniel Oberle, and Steffen Staab. What Is An Ontology? In: S. Staab and R. Studer, Handbook on Ontologies, Chapter 6. Springer. 2009. pp1-17.
Concerning “RDF-based ontologies … are directly implemented in code”: I find it hard to imagine that people find RDF readable, let alone manually “code” in it. If they do, I feel sorry for them wasting excessive time on it, because for ontology development, there is no need to bother oneself with such lower level issues (cf. the Semantic Web layer cake).
Further, I strongly doubt the “modelers apparently preferring to work directly with the DBMS language”: implementers, sure, but analysts and modellers, no. Or, to tease a bit (as mentioned before, I have not read Simsion’s book): perhaps there is an older generation of ‘modellers’ who did not entertain themselves with sufficient education on the progress that has been made in conceptual data modelling and operate on the it-didn’t-work-well-15-years-ago-so-I-won’t-have-a-go-at-it-now assumption. In addition, there is plenty of modelling software around; if no-one would use it, these companies would have been bankrupt–but they are not.