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Philosophical Ontology

Ontology as a branch of philosophy is the scienceof what is, of the kinds and structures of objects,properties, events, processes, and relations inevery area of reality. “Ontology” is often usedby philosophers as a synonym of “metaphysics”(a label meaning literally: “what comes after thePhysics”), a term used by early students of Aris-totle to refer to what Aristotle himself called“first philosophy.” Sometimes “ontology” is usedin a broader sense, to refer to the study of whatmight exist; “metaphysics” is then used for thestudy of which of the various alternative possibleontologies is in fact true of reality (Ingarden1964). The term “ontology” (or ontologia) wascoined in 1613, independently, by two philo-sophers, Rudolf Göckel (Goclenius) in his Lexiconphilosophicum and Jacob Lorhard (Lorhardus) inhis Theatrum philosophicum. Its first occurrencein English as recorded by the Oxford EnglishDictionary appears in Bailey’s dictionary of 1721,which defines ontology as “an Account of beingin the Abstract.”

Ontology seeks to provide a definitive andexhaustive classification of entities in all spheresof being. The classification should be definitivein the sense that it can serve as an answer tosuch questions as: What classes of entities are

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needed for a complete description and explana-tion of all the goings-on in the universe? Or:What classes of entities are needed to give anaccount of what makes true all truths? Itshould be exhaustive in the sense that all typesof entities should be included in the classifica-tion, including also the types of relations bywhich entities are tied together to form largerwholes.

Different schools of philosophy offer differentapproaches to the provision of such classifica-tions. One large division is that between whatwe might call substantialists and fluxists, whichis to say between those who conceive ontologyas a substance- or thing- (or continuant-) baseddiscipline and those who favor an ontologycentered on events or processes (or occurrents).Another large division is between what we mightcall adequatists and reductionists. Adequatistsseek a taxonomy of the entities in reality at alllevels of aggregation, from the microphysical tothe cosmological, and including also the middleworld (the mesocosmos) of human-scale entitiesin between. Reductionists see reality in terms ofsome one privileged level of existents; they seekto establish the “ultimate furniture of the uni-verse” by decomposing reality into its simplestconstituents, or they seek to “reduce” in someother way the apparent variety of types of en-tities existing in reality.

Luciano Floridi (ed.), Blackwell Guide to the Philosophy of Computing and Information. Oxford: Blackwell. pp. 155-166 (2003)

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It is the work of adequatist philosophicalontologists such as Aristotle, Ingarden (1964),and Chisholm (1996) which will be of primaryimportance for us here. Their taxonomies are inmany ways comparable to the taxonomies pro-duced by sciences such as biology or chemistry,though they are of course radically more generalthan these. Adequatists transcend the dichotomybetween substantialism and fluxism, since theyaccept categories of both continuants andoccurrents. They study the totality of thoseobjects, properties, processes, and relations thatmake up the world on different levels of focusand granularity, and whose different parts andmoments are studied by the different scientificdisciplines. Ontology, for the adequatist, is thena descriptive enterprise. It is thus distinguishedfrom the special sciences not only in its radicalgenerality but also in its goal or focus: it seeksnot predication and explanation but rathertaxonomy and description.

Methods of Ontology

The methods of ontology – henceforth in philo-sophical contexts always used in the adequatistsense – are the methods of philosophy in general.They include the development of theories ofwider or narrower scope and the testing andrefinement of such theories by measuring themup, either against difficult counter-examples oragainst the results of science. These methodswere familiar already to Aristotle himself.

In the course of the twentieth century a rangeof new formal tools became available to ontolo-gists for the development and testing of theirtheories. Ontologists nowadays have a choiceof formal frameworks (deriving from algebra,category theory, mereology, set theory, topo-logy) in terms of which their theories can beformulated. These new formal tools, along withthe language of formal logic, can in principleallow philosophers to express intuitive ideasand definitions in clear and rigorous fashion,and, through the application of the methodsof formal semantics, they can allow also for thetesting of theories for logical consistency andcompleteness.

Ontological Commitment

To create effective representations it is an advant-age if one knows something about the thingsand processes one is trying to represent. (Wemight call this the Ontologist’s Credo.) The at-tempt to satisfy this credo has led philosophersto be maximally opportunistic in the sources theyhave drawn upon in their ontological explorationsof reality and in their ontological theorizing.These have ranged all the way from the prepara-tion of commentaries on ancient texts to reflec-tion on our linguistic usages when talking aboutentities in domains of different types. Increasingly,however, philosophers have turned to science,embracing the assumption that one (perhaps theonly) generally reliable way to find out some-thing about the things and processes within agiven domain is to see what scientists say. Somephilosophers have indeed thought that the wayto do ontology is exclusively through the invest-igation of scientific theories.

With the work of Quine (1953) there arose inthis connection a new conception of the propermethod of ontology, according to which theontologist’s task is to establish what kinds ofentities scientists are committed to in theirtheorizing. The ontologist studies the world bydrawing conclusions from the theories of thenatural sciences, which Quine takes to be ourbest sources of knowledge as to what the worldis like. Such theories are extensions of the theor-ies we develop and use informally in everydaylife, but they are developed with closer attentionto those special kinds of evidence that confer ahigher degree of probability on the claims made.Quine – or at least the Quine of 1953 (I amhere leaving aside Quine’s views on such mattersas ontological relativity and the indeterminacyof translation) – still takes ontology seriously.His aim is to use science for ontological pur-poses, which means: to find the ontology inscientific theories. Ontology is then a networkof claims, derived from the natural sciences, aboutwhat exists, coupled with the attempt to establishwhat types of entities are most basic. Each nat-ural science has, Quine holds, its own preferredrepertoire of types of objects to the existenceof which it is committed. Each such science

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embodies only a partial ontology. This is definedby the vocabulary of the corresponding theoryand (most importantly for Quine) by its canon-ical formalization in the language of first-orderlogic. Note that ontology is for Quine himselfnot the metalevel study of the ontological com-mitments or presuppositions embodied in thedifferent natural-scientific theories. Ontology israther these commitments themselves. Quinemoves to the metalevel, making a semantic as-cent to consider the statements in a theory, onlyin setting out to establish those expressions whichdefinitively carry its commitments. Quine fixesupon the language of first-order logic as themedium of canonical representation not out ofdogmatic devotion to this particular form, butrather because he holds that this is the onlyreally clear form of language. First-order logic isitself just a regimentation of corresponding partsof ordinary language, a regimentation fromwhich, in Quine’s eyes, logically problematicfeatures have been excised. It is then, Quineargues, only the bound variables of a theory thatcarry its definitive commitment to existence. Itis sentences like “There are horses,” “There arenumbers,” “There are electrons,” that do thisjob. His so-called “criterion of ontological com-mitment” is captured in the slogan: To be is to bethe value of a bound variable. This should notbe understood as signifying some reductivisticconception of existence itself as a merely logico-linguistic matter. Rather it is to be interpreted inpractical terms: to determine what the ontologicalcommitments of a scientific theory are, it is neces-sary to determine the values of the quantifiedvariables used in its canonical formalization.

Quine’s approach is thus most properlyconceived not as a reduction of ontology to thestudy of scientific language, but rather as acontinuation of ontology in the traditional sense.When viewed in this light, however, it can beseen to be in need of vital supplementation. Forthe objects of scientific theories are discipline-specific. This means that the relations betweenobjects belonging to different disciplinary do-mains fall out of bounds for Quinean ontology.Only something like a philosophical theory of howdifferent scientific theories (or their objects)relate to each other can fulfill the task of provid-ing an inventory of all the types of entities in

reality. Quine himself would resist this latterconclusion. For him the best we can achieve inontology lies in the quantified statements of par-ticular theories, theories supported by the bestevidence we can muster. We have no way to riseabove the particular theories we have; no way toharmonize and unify their respective claims.

Internal vs. External Metaphysics

Quine is a realist philosopher. He believes in aworld beyond language and beliefs, a world whichthe theories of natural science give us the powerto illuminate. There is, however, another tend-ency in twentieth-century analytic philosophy, atendency often associated with Quine but in-spired much rather by Kant and promulgated bythinkers such as Carnap and Putnam. Accordingto these thinkers ontology is a metalevel dis-cipline which concerns itself not with the worlditself but rather only with theories or languagesor systems of beliefs. Ontology as a first-levelscience of reality – ontology as what thesephilosophers call “external metaphysics” – isimpossible. The best we can achieve, they hold,is internal metaphysics, which means precisely thestudy of the ontological commitments of spe-cific theories or systems of beliefs. Strawsoniandescriptive metaphysics is one example of suchinternal metaphysics. Model-theoretic semantics,too, is often implicitly understood in internal-metaphysical terms – the idea being that we can-not understand what a given language or theoryis really about, but we can build models withmore or less nice properties. What we can neverdo is compare these models to some reality bey-ond. Ontology in the traditional philosophicalsense thus comes to be replaced by the study ofhow a given language or science conceptualizesa given domain. It becomes a theory of theontological content of certain representations.Traditional ontologists are seeking principles thatare true of reality. The practitioners of internalmetaphysics, in contrast, are seeking to elicit prin-ciples from subjects or theories. The elicited prin-ciples may or may not be true, but this, to thepractitioner of internal metaphysics, is of no con-cern, since the significance of these principles

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lies elsewhere – for instance in yielding a cor-rect account of the taxonomical system used byspeakers of a given language or by the scientistsworking in a given discipline.

In a development that has hardly been notedby philosophers, a conception of the job of theontologist close to that of Carnap and Putnamhas been advanced in recent years also in certainextraphilosophical disciplines, as linguists, psy-chologists, and anthropologists have sought toelicit the ontological commitments (“ontologies,”in the plural) of different cultures and groups.Thus, they have sought to establish the ontologyunderlying common-sense or folk theories ofvarious sorts by using the standard empiricalmethods of the cognitive sciences (see forexample Keil 1979, Spelke 1990). Researchersin psychology and anthropology have soughtto establish what individual human subjects, orentire human cultures, are committed to, ontolo-gically, in their everyday cognition, in much thesame way in which Quine-inspired philosophersof science had attempted to elicit the ontolo-gical commitments of the natural sciences.

It was still reasonable for Quine to identifythe study of ontology – the search for answersto the question: what exists? – with the study ofthe ontological commitments of natural scient-ists. This is because it is a reasonable hypothesisthat all natural sciences are in large degree con-sistent with each other. Moreover, the identifica-tion of ontology with ontological commitmentscontinues to seem reasonable when one takesinto account not only the natural sciences butalso certain commonly shared commitments ofcommon sense – for example that tables andchairs and people exist. For the common-sensetaxonomies of objects such as these are compat-ible with those of scientific theory if only we arecareful to take into account the different granu-larities at which each operates (Forguson 1989,Omnès 1999, Smith & Brogaard 2001).

Crucially, however, the running together ofontology and ontological commitments becomesstrikingly less defensible when the ontologicalcommitments of various specialist groups ofnonscientists are allowed into the mix. How, onto-logically, are we to treat the commitments ofastrologists, or clairvoyants, or believers in lepre-chauns? We shall return to this question below.

Ontology and Information Science

In a related development, also hardly noticed byphilosophers, the term “ontology” has gainedcurrency in recent years in the field of computerand information science (Welty & Smith 2001).

The big task for the new “ontology” derivesfrom what we might call the Tower of Babel prob-lem. Different groups of data- and knowledge-base system designers have their own idiosyncraticterms and concepts by means of which they buildframeworks for information representation. Dif-ferent databases may use identical labels but withdifferent meanings; alternatively the same mean-ing may be expressed via different names. Asever more diverse groups are involved in sharingand translating ever more diverse varieties ofinformation, the problems standing in the wayof putting this information together within asingle system increase geometrically. Methodsmust be found to resolve the terminological andconceptual incompatibilities which then inevit-ably arise.

Initially, such incompatibilities were resolvedon a case-by-case basis. Gradually, however, itwas recognized that the provision, once and forall, of a common reference ontology – a sharedtaxonomy of entities – might provide significantadvantages over such case-by-case resolution, andthe term “ontology” came to be used by informa-tion scientists to describe the construction of acanonical description of this sort. An ontologyis in this context a dictionary of terms formu-lated in a canonical syntax and with commonlyaccepted definitions designed to yield a lexicalor taxonomical framework for knowledge rep-resentation which can be shared by differentinformation-systems communities. More ambi-tiously, an ontology is a formal theory withinwhich not only definitions but also a supportingframework of axioms is included (perhaps theaxioms themselves provide implicit definitions ofthe terms involved).

The methods used in the construction ofontologies thus conceived are derived on theone hand from earlier initiatives in databasemanagement systems. But they also includemethods similar to those employed in philosophy(as described in Hayes 1985), including the

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methods used by logicians when developingformal semantic theories.

Upper-level Ontologies

The potential advantages of ontology thus con-ceived for the purposes of information manage-ment are obvious. Each group of data analystswould need to perform the task of making itsterms and concepts compatible with those ofother such groups only once – by calibrating itsresults in the terms of the single canonical back-bone language. If all databases were calibratedin terms of just one common ontology (a singleconsistent, stable, and highly expressive set ofcategory labels), then the prospect would ariseof leveraging the thousands of person-years ofeffort that have been invested in creating separatedatabase resources in such a way as to create, inmore or less automatic fashion, a single integratedknowledge base of a scale hitherto unimagined,thus fulfilling an ancient philosophical dream ofa Great Encyclopedia comprehending all know-ledge within a single system.

The obstacles standing in the way of the con-struction of a single shared ontology in the sensedescribed are unfortunately prodigious. Considerthe task of establishing a common ontology ofworld history. This would require a neutral andcommon framework for all descriptions of his-torical facts, which would require in turn that alllegal and political systems, rights, beliefs, powers,and so forth, be comprehended within a single,perspicuous list of categories.

Added to this are the difficulties which ariseat the point of adoption. To be widely acceptedan ontology must be neutral as between differentdata communities, and there is, as experiencehas shown, a formidable trade-off between thisconstraint of neutrality and the requirement thatan ontology be maximally wide-ranging andexpressively powerful – that it should containcanonical definitions for the largest possiblenumber of terms. One solution to this trade-offproblem is the idea of a top-level ontology, whichwould confine itself to the specification of suchhighly general (domain-independent) categoriesas: time, space, inherence, instantiation, identity,

measure, quantity, functional dependence, pro-cess, event, attribute, boundary, and so on. (Seefor example <http://suo.ieee.org>.) The top-levelontology would then be designed to serve ascommon neutral backbone, which would be sup-plemented by the work of ontologists workingin more specialized domains on, for example,ontologies of geography, or medicine, or ecology,or law, or, still more specifically, ontologies ofbuilt environments (Bittner 2001), or of surgicaldeeds (Rossi Mori et al. 1997).

Uses of Ontology

The initial project of building one single onto-logy, even one single top-level ontology, whichwould be at the same time nontrivial and alsoreadily adopted by a broad population of differ-ent information-systems communities, has how-ever largely been abandoned. The reasons forthis can be summarized as follows. The task ofontology-building proved much more difficultthan had initially been anticipated (the difficult-ies being at least in part identical to those withwhich philosophical ontologists have grappledfor some 2000 years). The information-systemsworld itself, on the other hand, is very oftensubject to the short time horizons of the com-mercial environment. This means that the require-ments placed on information systems changeat a rapid rate, so that already for this reasonwork on the construction of correspondingontological translation modules has been unableto keep pace.

Yet work in ontology in the information-systems world continues to flourish, and the prin-cipal reason for this lies in the fact that its focuson classification (on analysis of object types) andon constraints on allowable taxonomies hasproved useful in ways not foreseen by its initialprogenitors. The attempt to develop termino-logical standards, which means the provision ofexplicit specifications of the meanings of the termsused in application domains such as medicine orair-traffic control, loses nothing of its urgencyeven when it is known in advance that the moreambitious goal of a common universal ontologyis unlikely to be realized.

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Consider the following example, due toGuarino. Financial statements may be preparedunder either the US GAAP or the IASC stand-ards (the latter being applied in Europe and manyother countries). Cost items are often allocatedto different revenue and expenditure categoriesunder the two standards, depending on the taxlaws and accounting rules of the countriesinvolved. So far it has not been possible to de-velop an algorithm for the automatic conversionof income statements and balance sheets betweenthe two systems, since so much depends on highlyvolatile case law and on the subjective inter-pretation of accountants. Not even this relativelysimple problem has been satisfactorily resolved,though this is prima facie precisely the sort oftopic where ontology could contribute some-thing of great commercial impact.

If Ontek did not Exist, it wouldbe Necessary to Invent It

Perhaps the most impressive attempt to developan ontology – at least in terms of sheer size – isthe CYC project (http://www.cyc.com), whichgrew out of an effort initiated by Doug Lenatin the early 1980s to formalize common-senseknowledge in the form of a massive database ofaxioms covering all things, from governments tomothers. The resultant ontology has been criti-cized for what seems to be its lack of principlein the ways in which new terms and theoriescome to be added to the edifice of the theory.CYC takes the form of a tangled hierarchy, witha topmost node labeled Thing, beneath whichare a series of cross-cutting total partitions,including: Represented Thing vs. Internal MachineThing, Individual Object vs. Collection, Intan-gible vs. Tangible Object vs. Composite Tangibleand Intangible Object. Examples of IntangibleObjects (Intangible means: has no mass) are setsand numbers. A person, in the CYC ontology, isa Composite Object made up of a Tangible bodyand an Intangible mind.

More important for our purposes here is thework of the firm Ontek – short for “ontologicaltechnology” – which since 1981 has been devel-oping database programming and knowledge

representation technologies necessary to createdecision automation systems – “white collarrobots” – for large-scale industrial enterprises infields such as aerospace and defense. Realizingthat the ontology required to build such systemswould need to embrace in a principled way theentire gamut of entities encompassed by thesebusinesses in a single, unified framework, Ontekapproached this problem by systematically ex-ploiting the resources of ontology in the tradi-tional (adequatist) philosophical sense. A teamof philosophers (including David W. Smith andPeter Simons) collaborated with software engin-eers in constructing the system PACIS (forPlatform for the Automated Construction ofIntelligent Systems), which is designed toimplement a comprehensive theory of entities,ranging from the very concrete (aircraft, theirstructures, and the processes involved in design-ing and developing them), to the somewhatabstract (business processes and organizations,their structures, and the strategies involved increating them), to the exceedingly abstract for-mal structures which bring all of these diversecomponents together.

Ontek has thus realized in large degree theproject sketched by Hayes in his “Naïve PhysicsManifesto,” of building a massive formal theoryof (in Hayes’s case) common-sense physical real-ity (in Ontek’s case this is extended to includenot only airplane wings and factories but alsoassociated planning and accounting procedures).As Hayes insisted, if long-term progress in artifi-cial intelligence is to be achieved it is necessaryto put away the toy worlds of classical AI re-search and to concentrate instead on the task offormalizing the ontological features of the worlditself, as this is encountered by adults engagedin the serious business of living.

The Leipzig project in medical ontology (see <http://ifomis.org>), too, is based on a realist methodology close to that of Ontek, and some-thing similar applies also to the work of Guarino and his colleagues in Italy. Most prominent information-systems ontologists in recent years, however, have abandoned the Ontologist’s Credo and have embraced instead a view of ontology as an inwardly directed discipline (so that they have in a sense adopted an epistemologized reading of ontology analogous to that of Carnap and

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Putnam). They have come to hold that onto-logy deals not with reality itself but rather with“alternative possible worlds,” worlds which areindeed defined by the information systems them-selves. This means not only that only those en-tities exist which are represented in the system(Gruber 1995), but also that the entities in ques-tion are allowed to possess only those propertieswhich the system itself can recognize. It is as ifHamlet, whose hair (we shall suppose) is notmentioned in Shakespeare’s play, would be notmerely neither bald nor nonbald, but wouldsomehow have no properties at all as far as hair isconcerned. (Compare Ingarden 1973 on the “lociof indeterminacy” within the stratum of rep-resented objects of a literary work.) What thismeans, however, is that the objects representedin the system (for example, people in a database)are not real objects – the objects of flesh andblood we find all around us. Rather, they aredenatured surrogates, possessing only a finitenumber of properties (sex, date of birth, socialsecurity number, marital status, employmentstatus, and the like), and being otherwise entirelyindeterminate with regard to those sorts of prop-erties with which the system is not concerned.

Information-systems ontologies in the senseof Gruber are, we see, not oriented around theworld of objects at all. Rather, they are focusedon our concepts or languages or mental models(or, on a less charitable interpretation, the tworealms of objects and concepts are simply con-fused). It is in this light that we are to interpretpassages such as the following:

an ontology is a description (like a formalspecification of a program) of the conceptsand relationships that can exist for an agent ora community of agents. This definition is con-sistent with the usage of ontology as set-of-concept-definitions, but more general. And itis certainly a different sense of the word thanits use in philosophy. (Gruber, n.d.)

Conceptualizations

The newly fashionable usage of “ontology” asmeaning just “conceptual model” is by now

firmly entrenched in many information-systemscircles. Gruber is to be given credit for havingcrystallized the new sense of the term by relatingit to the technical definition of “conceptualiza-tion” introduced by Genesereth and Nilsson intheir Logical Foundation of Artificial Intelligence(1987). In his 1993 article Gruber defines anontology as “the specification of a conceptual-ization.” Genesereth and Nilsson conceive con-ceptualizations as extensional entities (they aredefined in terms of sets of relations), and theirwork has been criticized on the grounds thatthis extensional understanding makes concep-tualizations too remote from natural language,where intensional contexts predominate (seeGuarino, Introduction to 1998). For presentpurposes, however, we can ignore these issues,since we shall gain a sufficiently precise under-standing of the nature of “ontology,” as Gruberconceives it, if we rely simply on the accountof conceptualizations which he himself gives inpassages such as the following:

A conceptualization is an abstract, simplifiedview of the world that we wish to representfor some purpose. Every knowledge base,knowledge-based system, or knowledge-levelagent is committed to some conceptualization,explicitly or implicitly. (Gruber 1995)

The idea is as follows. As we engage with theworld from day to day we participate in ritualsand we tell stories. We use information systems,databases, specialized languages, and scientificinstruments. We buy insurance, negotiate traffic,invest in bond derivatives, make supplications tothe gods of our ancestors. Each of these ways ofbehaving involves, we can say, a certain concep-tualization. What this means is that it involves asystem of concepts in terms of which the corres-ponding universe of discourse is divided up intoobjects, processes, and relations in different sortsof ways. Thus in a religious ritual setting we mightuse concepts such as salvation and purification;in a scientific setting we might use concepts suchas virus and nitrous oxide; in a story-telling set-ting we might use concepts such as leprechaunand dragon. Such conceptualizations are oftentacit; that is, they are often not thematized inany systematic way. But tools can be developed

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to specify and to clarify the concepts involved andto establish their logical structure, and in thisway we are able to render explicit the underlyingtaxonomy. We get very close to the use of theterm “ontology” in Gruber’s sense if we definean ontology as the result of such clarification –as, precisely, the specification of a conceptualiza-tion in the intuitive sense described in the above.

Ontology now concerns itself not with thequestion of ontological realism, that is with thequestion whether its conceptualizations are trueof some independently existing reality. Rather, itis a strictly pragmatic enterprise. It starts withconceptualizations, and goes from there to thedescription of corresponding domains of objects(also called “concepts” or “classes”), the latterbeing conceived as nothing more than nodes inor elements of data models devised with specificpractical purposes in mind.

In very many cases the domains addressed byontological engineers are themselves the pro-ducts of administrative fiat. The neglect of truthto independent reality as a measure of the cor-rectness of an ontology is then of little import.In such cases the ontologist is called upon merelyto achieve a certain degree of adequacy to thespecifications laid down by the client, striving asbest he can to do justice to the fact that whatthe client says may fall short, for example, whenmeasured in terms of logical coherence. Truth(or the lack of truth) can be a problem also innon-administrative domains. Bad conceptualiza-tions abound (rooted in error, myth-making,hype, bad linguistics, or in the confusions ofill-informed “experts” who are the targets ofknowledge-mining). Conceptualizations such asthese may deal only with created (pseudo-)domains, and not with any transcendent realitybeyond. They call for a quite different approachthan is required in those areas – above all in theareas addressed by the natural sciences – wherethe striving for truth to independent reality is aparamount constraint. Yet this difference in ques-tion has hardly been noted by those working oninformation-systems ontology – and this givesus one clue as to why the project of a commonreference ontology applicable in domains of manydifferent types should thus far have failed.

Considered against this background the projectof developing a top-level ontology begins to seem

rather like the attempt to find some highestcommon denominator that would be shared incommon by a plurality of true and false theories.Attempts to construct such an ontology mustfail if they are made on the basis of a methodo-logy which treats all application domains on anequal footing. Instead, we must find ways to dojustice to the fact that the different conceptual-izations which serve as inputs to ontology arelikely to be not only of wildly differing qualitybut also mutually inconsistent.

What can Information ScientistsLearn from Philosophical

Ontologists?

As we have seen, some ontological engineers haverecognized that they can improve their modelsby drawing on the results of the philosophicalwork in ontology carried out over the last 2000years. This does not in every case mean thatthey are ready to abandon their pragmatic per-spective. Rather, they see it as useful to employa wider repertoire of ontological theories andframeworks and, like philosophers themselves,they are willing to be maximally opportunisticin their selection of resources for purposes ofontology-construction. Guarino and Welty(2000), for example, use standard philosophicalanalyses of notions such as identity, part, set-membership, and the like in order to exposeinconsistencies in standard upper-level ontologiessuch as CYC, and they go on from there toderive metalevel constraints which all ontologiesmust satisfy if they are to avoid inconsistenciesof the sorts exposed.

Given what was said above, it appears fur-ther that information ontologists may havesound pragmatic reasons to take the philo-sopher ontologist’s traditional concern for truthmore seriously still. For the very abandonmentof the focus on mere conceptualizations andon conceptualization-generated object-surrogatesmay itself have positive pragmatic consequences.

This applies even in the world of admin-istrative systems, for example in relation to theGAAP/IASC integration problem referred toabove. For ontologists are here working in a

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type of theoretical context where they must moveback and forth between distinct conceptualiza-tions, and where they can find the means tolink the two together only by looking at theircommon objects of reference in the real, flesh-and-blood world of human agents and financialtransactions.

Where ontology is directed in this fashion,not towards a variety of more or less coherentsurrogate models, but rather towards the realworld of flesh-and-blood objects in which we alllive, then this itself reduces the likelihood ofinconsistency and systematic error in the theor-ies which result; and, conversely, it increases thelikelihood of our being able to build a singleworkable system of ontology that will be atthe same time nontrivial. On the other hand,however, the ontological project thus conceivedwill take much longer to complete and it willface considerable internal difficulties along theway. Traditional ontology is a difficult busi-ness. At the same time, however, it has thepotential to reap considerable rewards – not leastin terms of a greater stability and conceptualcoherence of the software artifacts constructedon its basis.

To put the point another way: it is preciselybecause good conceptualizations are transparentto reality that they have a reasonable chance ofbeing integrated together in robust fashion intoa single unitary ontological system. If, however,we are to allow the real world to play a significantrole in ensuring the unifiability of our separateontologies, then this will imply that those whoaccept a conceptualization-based methodologyas a stepping stone towards the construction ofadequate ontologies must abandon the attitudeof tolerance towards both good and bad con-ceptualizations. It is this very tolerance whichis fated to undermine the project of ontologyitself.

Of course to zero-in on good conceptualiza-tions is no easy matter. There is no Geiger-counter-like device which can be used forautomatically detecting truth. Rather, we haveto rely at any give stage on our best endeavors –which means concentrating above all on the workof natural scientists – and proceed in careful,critical, and fallibilistic fashion from there, hop-ing to move gradually closer to the truth via

an incremental process of theory construction,criticism, testing, and amendment. As suggestedin Smith and Mark (2001), there may be reasonsto look beyond natural science, above all wherewe are dealing with objects (such as societies,institutions, and concrete and abstract artifacts)existing at levels of granularity distinct from thosewhich readily lend themselves to natural-scientificinquiry. Our best candidates for good conceptu-alizations will, however, remain those of the nat-ural sciences – so that we are, in a sense, broughtback to Quine, for whom the job of the ontolo-gist coincides with the task of establishing theontological commitments of scientists, and ofscientists alone.

What Can Philosophers Learnfrom Information-systems

Ontologists?

Developments in modal, temporal, and dynamiclogics as also in linear, substructural, and paracon-sistent logics have demonstrated the degree towhich advances in computer science can yieldbenefits in logic – benefits not only of a strictlytechnical nature, but also sometimes of widerphilosophical significance. Something similarcan be true, I suggest, in relation to the devel-opments in ontological engineering referred toabove. These developments can first of all helpto encourage existing tendencies in philosoph-ical ontology (nowadays often grouped under theheading “analytic metaphysics”) towards open-ing up new domains of investigation, for examplethe domain of social institutions (Mulligan 1987,Searle 1995, Smith 2002), of patterns (Johansson1998), of artifacts (Dipert 1993, Simons &Dement 1996), of boundaries (Smith 2001), ofdependence and instantiation (Mertz 1996), ofholes (Casati & Varzi 1994), and parts (Simons1987). Secondly, it can shed new light on themany existing contributions to ontology, fromAristotle to Goclenius and beyond (Burkhardt& Smith 1991), whose significance was for a longtime neglected by philosophers in the shadow ofKant and other enemies of metaphysics. Thirdly,if philosophical ontology can properly be con-ceived as a kind of generalized chemistry, then

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information systems can help to fill one importantgap in ontology as it has been practiced thus far,which lies in the absence of any analog of chem-ical experimentation. For one can, as C. S. Peirceremarked (1933: 4.530), “make exact experi-ments upon uniform diagrams.” The new toolsof ontological engineering might help us to real-ize Peirce’s vision of a time when operationsupon diagrams will “take the place of the experi-ments upon real things that one performs inchemical and physical research.”

Finally, the lessons drawn from information-systems ontology can support the efforts of thosephilosophers who have concerned themselvesnot only with the development of ontologicaltheories, but also – in a field sometimes called“applied ontology” (Koepsell 1999, 2000) – withthe application of such theories in domains suchas law, or commerce, or medicine. The tools ofphilosophical ontology have been applied to solvepractical problems, for example concerning thenature of intellectual property or concerningthe classification of the human fetus at differentstages of its development. Collaboration withinformation-systems ontologists can support suchventures in a variety of ways, first of all becausethe results achieved in specific application do-mains can provide stimulation for philosophers,but also – and not least importantly – becauseinformation-systems ontology is itself an enorm-ous new field of practical application that iscrying out to be explored by the methods ofrigorous philosophy.

Acknowledgments

This chapter is based upon work supported bythe National Science Foundation under GrantNo. BCS-9975557 (“Ontology and GeographicCategories”) and by the Alexander vonHumboldt Foundation under the auspices of itsWolfgang Paul Program. Thanks go in additionto Thomas Bittner, Charles Dement, AndrewFrank, Angelika Franzke, Wolfgang Grassl, NicolaGuarino, Kathleen Hornsby, Ingvar Johansson,Kevin Mulligan, David W. Smith, WilliamRapaport, Chris Welty, and Graham White forhelpful comments. They are not responsible forany errors which remain.

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