RDF Schema Definition Language">Toward a Structuralist RDF Schema Definition Language

June 7th, 2009 admin RDF Schema Definition Language&rft.aulast=&rft.aufirst=&rft.subject=Comparative Ontology&rft.subject=theory&rft.source=The Transducer&rft.date=2009-06-07&rft.type=&rft.format=text&rft.identifier=http://transducer.ontoligent.com/?p=534&rft.language=English">

When I get the time, I’m going to write a vocab­u­lary cre­ation lan­guage to sup­port struc­tural­ist text inter­pre­ta­tion.  It will con­sist of two specs: one to han­dle the mark­ing up the sur­face fea­tures of text, such as rhetor­i­cal fig­ures and tropes.  This will be based on my work with the Prince­ton Char­rette Project and it will likely incor­po­rate some ideas from Steven Bird’s work on anno­ta­tion graphs.  The sec­ond will be either an exten­sion of or a vari­ant of SKOS and|or OWL designed to rep­re­sent extracted sym­bolic struc­tures.  It will incor­po­rate pred­i­cates to han­dle rela­tions of sig­ni­fi­ca­tion, such as has_part, has_analogy, and has_metonym, between the ele­ments rep­re­sented in the first lan­guage.   At a larger level, I want to rep­re­sent holis­tic dimen­sions such as con­text and level, as well as nar­ra­to­log­i­cal things like encom­pass­ment, trans­for­ma­tion, inver­sion, and liminality.

One of the big prob­lems I see in this project is an appar­ent lim­i­ta­tion in RDF to sup­port triples about triples.  For exam­ple, an anal­ogy is a rela­tion between struc­tures, not terms.  The asser­tion A : B :: C : D is, at minu­mum, an asser­ta­tion about the rela­tion­ship between two asser­ta­tions, A : B and C : D.  (The pred­i­cate of the asser­tions them­selves is usu­ally X has_part Y.)  An anol­ogy looks some­thing like this then:

[A has_part B] just_as [C has_part D]

The eas­i­est way to accom­plish this task would be to pro­vide URIs for each RDF triple.  I haven’t seen a gen­eral solu­tion to this prob­lem.  I know I can cre­ate local URIs within a spe­cific triple store, and use these in triples.  But I need to define an RDF triple as a datatype first.  And I antic­i­pate prob­lems fur­ther down­stream; I won­der if the cur­rent RDF toolset is designed to han­dle index­ing and infer­enc­ing of these kinds of triples.

If any­one has sug­ges­tions about how to han­dle this issue, I’d be glad to hear them.

AFTERTHOUGHT:

After writ­ing this, it strikes me that to say that two triples are anal­o­gous is just to say that they share a predicate–so long as that pred­i­cate is suf­fi­ciently spec­i­fied.  To assert an anal­ogy, then, is to assert that such an iden­tity is impor­tant or rel­e­vant in a cer­tain context.

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Rituals, Texts and Databases

May 12th, 2009 admin

Com­par­a­tive ontol­ogy asserts that humans already have ontolo­gies, and that machine ontolo­gies are both pro­jec­tions of human ontolo­gies (those of the numerati) and mate­r­ial agents that inter­vene in the ongo­ing repro­duc­tion of ontolo­gies (every­one else’s).  Devel­op­ers of ontolo­gies for the web of linked data would do well to under­stand the nature of human ontolo­gies, as well as they way machine ontolo­gies inter­vene in the ongo­ing con­struc­tion of social life.

Human ontolo­gies are not like ROM pro­grams, hard-wired into our brains and exe­cuted with­out mod­i­fi­ca­tion; they are designed to be repro­grammed through engage­ment with the world. They are one of our most effec­tive adap­tive traits.

Ontolo­gies are adaptive

Anthro­pol­o­gists have stud­ied ontolo­gies in the wild for a long time, under the var­i­ous cat­e­gories of “struc­ture,” “sym­bol­ism,” “cul­ture” and “col­lec­tive rep­re­sen­ta­tions.”  One of the most impor­tant con­trib­u­tors to the study of ontol­ogy is the Amer­i­can cul­tural anthro­pol­o­gist Mar­shall Sahlins.

Sahlins’ prin­ci­pal the­o­ret­i­cal con­ti­bu­tion to cul­tural anthro­pol­ogy has been to retrieve the con­cept of cul­tural struc­ture of the ahis­tor­i­cal, for­mal­ist, and mech­a­nis­tic con­cep­tion devel­oped by Lévi-Strauss, whose own work on mythol­ogy belies his more the­o­ret­i­cal pro­nounce­ments.  Rather than sep­a­rat­ing struc­ture from event (and his­tory), and locat­ing the for­mer deeply within a uni­ver­sal mind–like a camshaft respon­si­ble for the jig­saw puz­zle of culture–Sahlins focuses on what he calls the “struc­ture of the con­junc­ture” of struc­ture and event.  His­tory emerges as a cul­tur­ally dis­tinc­tive second-order struc­ture that results from the ongo­ing work of cat­e­gories in praxis. So cat­e­gories have a struc­ture, but that struc­ture under­goes reeval­u­a­tion and change as it is applied to the world.

In Islands of His­tory Sahlins describes the process of cul­tural (onto­log­i­cal) change in terms of the “risk of ref­er­ence”: as cul­tures clas­sify things in the world–as they deploy ontologies–they also put these ontolo­gies at risk.  For things in the world do not always behave as clas­si­fied, or planned.  Even the sun  has an occa­sional eclipse.  Although the keep­ers of culture–from priests to grandmothers–try to enforce adher­ence to the cat­e­gories, the behav­ior of things will inevitably con­tra­dict the cat­e­gories and call for their revi­sion.  Sahlins reads the Hawai’ian’s clas­si­fi­ca­tion of Cap­tain Cook as Lono as just such a world chang­ing event.

Rit­ual is one mech­a­nism humans use to syn­chro­nize the world with world view.  As peo­ple grow, for exam­ple, and change sta­tuses, rites of pas­sage are used to medi­ate this “con­tra­dic­tion” and reclas­sify peo­ple so that they can fit into the sys­tem.  Another mech­a­nism is prophecy, where  the reverse is true–world views are aligned with a world that has changed.  Mil­lenar­ian move­ments are the clas­sic exam­ple of this: a prophet emerges who can make sense of the new in terms of the old, but changes the old in the process.

Rit­u­als and prophetic move­ments are the orig­i­nal forms of change management.

This is the ongo­ing work of cul­ture.  Cul­tural repro­duc­tion is never mechan­i­cal.  That is one rea­son we humans have his­tory.  There is always a dis­pro­por­tion between words and things, plans and situations.

Data­bases (and the point of this post)

Now, a data model, such as a set of tables and fields in a rela­tional data­base, an XML schema of ele­ments and attrib­utes, or an RDF vocab­u­lary of classes and prop­er­ties, is a plan, a schema of clas­si­fi­ca­tion.   And data­base appli­ca­tions, like rit­u­als and texts, have their own forms of ref­er­en­tial risk to con­tend with. They clas­sify the world and, in the process, both effect the world they clas­sify and open them­selves up for revi­sion by that world as it changes.

For exam­ple, the cat­e­gories pro­duced by a require­ments elic­i­ta­tion process for an appli­ca­tion designed to improve some work­flow, and encoded in a data­base that sits at the bot­tom of an appli­ca­tion stack, may not accu­rately rep­re­sent the work­flow as it is actu­ally prac­ticed, and as it will inevitably change as new devel­op­ments take place–changing per­son­nel, clients, strate­gic plans, etc. The data­base, then, is put into a situation–the sit­u­a­tion of the conjuncture–into which its cat­e­gories are at risk.

In this sit­u­a­tion, data­bases are like texts–they are built on the arma­ture of a hard-coded ontol­ogy, and they can move beyond their orig­i­nal domain of applicatibility.

But unlike most texts, and very much like sacred texts, data­base appli­ca­tions (and their admin­is­tra­tors) are usu­ally given a cen­tral posi­tion within an orga­ni­za­tion.  They are often deployed as key ele­ments of an enter­prise archi­tec­ture that calls the insti­tu­tional shots.  Thus they can insu­late them­selves from ref­er­en­tial risk.  They can force con­for­mity to their logic–as Michael Wesch’s New Guinea vil­lagers redesigned their set­tle­ment pat­tern to con­form to the gov­ern­ment census–or they can pro­duce a black mar­ket of behav­iors in an orga­ni­za­tion that bypasses the data­base gov­erned work­flow.  This is what fac­ulty do who are forced to use an LMS but would rather use Google Docs.

Com­par­a­tive ontol­ogy can help here.  If we view ontolo­gies as always sit­u­ated, then we should (1) design sys­tems for max­i­mum flex­i­bil­ity and adapt­abilty, and (2) learn a les­son from the rit­ual life of peo­ples around the world and through­out his­tory: engage our ontolo­gies in con­stant reeval­u­a­tion and mod­i­fi­ca­tion, mak­ing the world (of our orga­ni­za­tions) fit where appro­pri­ate, and also refin­ing the cat­e­gories to fit the world.

To meet the first chal­lenge, we shouldn’t cre­ate over­wrought ontolo­gies, but rather focus on just enough clas­si­fi­ca­tion to achieve the effects we need. Usu­ally, the effects we are most con­cerned with are con­nect­ing peo­ple to peo­ple, peo­ple to infor­ma­tion, and infor­ma­tion to infor­ma­tion, in as few links as possible.

To meet the sec­ond chal­lenge, we may want to refine what we mean by “social oper­at­ing system”–for that is pre­cisely what a rit­ual sys­tem is.  Maybe it’s time to fol­low McLuhan’s advice and exploit the rit­ual effects of the elec­tric, in order to mit­i­gate and shape the more dan­ger­ous effects of the elec­tronic.   When we build ontolo­gies, maybe we should also be think­ing of the phys­i­cal and vir­tual spaces in which they will be deployed, and the mate­r­ial and dig­i­tal arti­facts that will be their vehi­cles of expression.

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CompOnt Tenet 3: Human Ontologies are Built out of Symbols

April 25th, 2009 admin

Sym­bols — from core sym­bols like the Vir­gin of Guadalupe to abstract ones like the white­ness of Melville’s whale — fix and gen­er­ate onto­log­i­cal cat­e­gories.  How and why this hap­pens is a ques­tion of deep inter­est to me, but that it is true seems obvi­ous and well estab­lished.  Human beings cre­ate sym­bols like plants pro­duce oxy­gen, and sym­bol for­ma­tion is inex­tri­ca­bly bound to a defin­ing trait of human beings — rich, dis­cur­sive, and always already metacog­ni­tive  lan­guage (human beings have always talked about talk­ing, a prac­tice that must be regarded as intrin­sic to human lan­guage).  Lin­guis­tics up to now, wed­ded as it has been to a Chom­skyian Carte­sian­ism, has missed this role, although philoso­phers have not lost sight of it.  As Ricoeur wrote, “the sym­bol gives rise to thought.”

The rela­tion­ship between lan­guage and sym­bol­ism is com­plex and (still) not well under­stood.  My own view is close to that of the (admit­tedly dis­cred­ited in its orig­i­nal form) gen­er­a­tive seman­tics school, asso­ci­ated with George Lakoff.  I believe that cat­e­gories and rules are in some way gen­er­ated by the trans­duc­tion of mean­ing that takes place between neural rep­re­sen­ta­tions of con­crete objects.  Dis­cur­sive lan­guage — not “deep gram­mar” — tries to fix these mean­ings in propo­si­tional form, but the sym­bolic sub­strate has a dynamic qual­ity, in no small mea­sure do to its adap­tive nature in response to what Merleu-Ponty called the “pri­macy of perception.”

With writ­ing and then print­ing, and the monop­o­liza­tion of explicit knowl­edge, in the form of writ­ten records, ref­er­ence works, etc., by gov­ern­ments, uni­ver­si­ties, etc., the rela­tion­ship between dis­cur­sive fix­a­tion and embod­ied sym­bols becomes ten­u­ous and con­tested, result­ing in a mind/body prob­lem unfa­mil­iar to rit­ual societies.

In any case, a num­ber of prac­ti­cal obser­va­tions fol­low from this tenet, which I will quickly enu­mer­ate, and hope­fully take up later:

1. Human ontolo­gies are not plans.
2. Human ontolo­gies are overde­ter­mined.  That is, there is always more than one way to express an ontol­ogy  The fix­ing of mean­ings will always fail if the goal is to cre­ate non-overlapping, non-redundant descriptions.
3. Human ontolo­gies are rhi­zomic.  In their nat­ural form, ontolo­gies are not hier­ar­chi­cal.  Rather, the hier­ar­chi­cal rep­re­sen­ta­tion is one form of seri­al­iza­tion that works well because of its anal­ogy to kin­ship (see Durkheim and Mauss, Prim­i­tive Clas­si­fi­ca­tion).
4. Human ontolo­gies are local and sit­u­ated.
5. Human ontolo­gies evolve.

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CompOnt Tenet 2: Social Life Makes the Categories

April 25th, 2009 admin

Just as insti­tu­tions require shared ontolo­gies to func­tion, so are insti­tu­tions involved in cre­at­ing the cat­e­gories that nake up ontolo­gies.  Admit­tedly, assign­ing agency to insti­tu­tions poses a num­ber of ques­tions that need to be answered; I won’t attempt that here.  Essen­tially, I fol­low Mary Dou­glas (see video below), espe­cially her How Insti­tu­tions Think.  The cat­e­gories and rules that com­prise human ontolo­gies fol­low and enable a prac­ti­cal logic that in turn enables sus­tain­able human interaction.

A corol­lary idea to this is that ontolo­gies exist (in large part) to medi­ate social action.  They are the result of human beings’ mutual cal­i­bra­tion of indi­vid­ual cog­ni­tion through col­lec­tive inter­ac­tion.  Typ­cially, this cal­i­bra­tion takes place through rit­ual.  But media (old and new) — which grow out of but even­tu­ally dis­place rit­ual — also take on this role. (McLuhan’s fre­quent ref­er­ence to rit­ual to describe the effects of new media is telling.)

“Social Life Makes the Cat­e­gories“
The late Mary Dou­glas being inter­viewed in 2006
about her book Purity and Dan­ger.
See the full inter­view and films at Sci­enceS­tage.

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Tenets of Comparative Ontology 1: People already have ontologies.

April 25th, 2009 admin

This is the first in a series of posts in which I define some of the tenets of com­par­a­tive ontol­ogy, in order try to flesh out its sig­nif­i­cance to the work of mak­ing and using RDF vocabularies.

The over­whelm­ing con­clu­sion to be drawn from the ethno­graphic record is that human beings are sur­pris­ingly struc­tured in their think­ing and behav­ior, even when that behav­ior seems to be ran­dom and non-linear.  Although it is a com­mon­place to observe that social life is inher­ently messy, unpre­dictable, and resis­tant to cap­ture by physics-like laws (post-Einsteinian included) it remains true that pat­terns of cul­ture are remark­ably wide­spread and per­sis­tent.   Lan­guages, mar­riage prac­tices, cal­en­dar sys­tems, gift exchange sys­tems, mar­kets, etc. — essen­tially, any func­tional human insti­tu­tion — all rely on shared cat­e­gories and rules to oper­ate, and these are dis­cov­er­able and describ­able.  The mis­take of the struc­tural­ists was to con­ceive of these cat­e­gories and rules as log­i­cal in a for­mal, almost scholas­tic sense, like a plan that agents fol­low strictly.  Instead, it is more likely that they exist as dis­po­si­tions that con­strain behav­ior and encour­age improviza­tion, as Bour­dieu describes in his idea of the habi­tus (which he got from Mauss, by the way).

To the extent that for­mal RDF ontolo­gies are meant to medi­ate human-computer inter­ac­tion (and not sim­ply allow com­put­ers to share infor­ma­tion), ontolo­gies should be designed to inter­dig­i­tate with the cat­e­gories of their human par­tic­i­pants.  Machine ontolo­gies should be inter­op­er­a­ble with human ontolo­gies.  They should be designed to encour­age the sym­bi­otic devel­op­ment and evo­lu­tion of human col­lec­tive rep­re­sen­ta­tions (to use Durkheim’s expres­sion), given the role of the net­worked com­puter and com­puter net­work as an insti­tu­tion in its own right.

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Two More Thoughts on Comparative Ontology

April 16th, 2009 admin

Fol­low­ing up on my last two posts (here and here), I thought I’d flesh out a lit­tle more what I mean by Com­par­a­tive Ontol­ogy — and, at this point, maybe I need a han­dle for the con­cept, like CO or “comp-ont.”

First thought:  I imag­ine that a comp-ont vocab­u­lary could be accom­plished in two ways: (1) by just using exist­ing vocab­u­lary def­i­n­i­tion lan­guages (RDFS and OWL) to cre­ate a new vocab­u­lary, or (2) by cre­at­ing a new vocab­u­lary def­i­n­i­tion lan­guage using, say, Rod­ney Needham’s cod­i­fi­ca­tion of Eng­lish Struc­tural­ism in  Sym­bolic Clas­si­fi­ca­tion.

As an exam­ple of type 1, one might deploy the implicit ontol­ogy of Kautilya’s Arthashas­tra (with maybe a lit­tle of Machiavelli’s Prince thrown in) using OWL to cre­ate an “Enemy of an Enemy” (EOAE) vocab­u­lary. This would be a use­ful vocab­u­lary for describ­ing polit­i­cal agents, link­ing them through the neg­a­tive tran­si­tive logic of polit­i­cal alliance for­ma­tion, with the result that you could actu­ally pre­dict or sug­gest alliances that don’t yet exist. I can imag­ine this vocab­u­lary describ­ing peo­ple (politi­cians, pun­dits, etc.), ideas, insti­tu­tions, etc., and applied to daily news sources.

As an exam­ple of type 2, my ques­tion would be whether con­structs like anal­ogy or metonymy could be con­structed on top of set the­ory (OWL) or if it would require a whole new sys­tem (and there­fore logic of inference.)

Sec­ond thought:  It strikes me that one way to bring home the value of comp-ont is to view it in the con­text of knowl­edge man­age­ment (KM).  Clearly there is a strong con­nec­tion between KM and ontol­ogy (and the seman­tic web and linked data).  But within KM, it is clear that ontolo­gies can’t just be log­i­cal.  Ontolo­gies must be prac­ti­cal, and intel­li­gi­ble to the peo­ple in an orga­ni­za­tion who engage in ontology-mediated knowl­edge trans­fer.  They must serve the pur­pose of medi­at­ing between indi­vid­ual and col­lec­tive mem­ory.  But this is pre­cisely what the great onto­log­i­cal sys­tems from the ethno­graphic record pro­vide — from Aus­tralian totemic sys­tems to Mayan cal­en­dars.  Viewed from the per­spec­tive of social mem­ory, then, it makes a great deal of sense to build KM ontolo­gies on gen­eral prin­ci­ples adduced from anthro­po­log­i­cal exam­ples, and described in terms of struc­tural­ism.

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Comparative Ontology (ii)

April 14th, 2009 admin

So, I make the claim in my pre­vi­ous post on Com­par­a­tive Ontol­ogy that com­par­a­tivsim will help us make bet­ter ontolo­gies and tools for using them. I real­ize I did not actu­ally make that case. Let me try to do that now, although, to be hon­est, I view the claim as an inter­est­ing direc­tion to fol­low (i.e. a hunch), not an estab­lished fact.

My argu­ment is pretty sim­ple. The Seman­tic Web, as every­one knonws, has a big prob­lem — in order for it to suc­ceed, pro­duc­ers of web con­tent have to mark up texts using RDF, with its long URIs and arcane vocab­u­lar­ies.  Most folks think this is a deal killer.  In addi­tion, many agree with Shirky’s claim that ontol­ogy is over­rated in the first place.   (The meme even makes an appear­ance in Michael Wesch’s viral “The Machine is Us/Using Us.”)

I hold out hope, though.  I think tools can be cre­ated to make the data entry part  a lot easier–withness Dru­pal 6.  I also think con­tent cre­ators show a remark­able ten­dency to use tags, enter meta­data, and engage in oth­er­wise tedious SEO tech­niques if they know that they will get some­thing out of it.  This ten­dency is espe­cially strong among dig­i­tal humani­tists, dig­i­tal librar­i­ans, and other cre­ators and cura­tors of dig­i­tal col­lec­tions.  (Think of the time peo­ple have put into TEI!) Right now, they don’t see a lot a ROI from using RDF.  But that is chang­ing, and faster than many think.

As is often remarked, it’s a clas­sic chicken and egg argu­ment.  But such prob­lems are actu­ally lib­er­at­ing, since you can inter­vene at any point in the cycle and have an effect.  One junc­ture in the cycle is in the design of vocabularies.

The prob­lem now is that vocab­u­lar­ies and ontolo­gies are just not sticky enough, and I think a big rea­son for this is that they are writ­ten from the per­spec­tive of sym­bolic logic and set the­ory.  These frame­works, though com­pre­hen­sive, are not human (enough).  On the other hand, there is a whole tra­di­tion of describ­ing cog­ni­tive sys­tems called struc­tural­ism, which has the advan­tage of being empir­i­cally grounded in the long­stand­ing com­par­a­tive study of cul­ture.  It stands to rea­son that if we cre­ated vocab­u­lar­ies using more “human” constructs–such as anal­ogy, metonymy, etc.–and vocab­u­lar­ies that rec­og­nized the role of verbs in pred­i­cates, then we might be able to pro­duce more sticky ontologies.

It also opens a way to har­vest the latent ethno­graphic data con­tained in folksonomies.

But I’ll leave it at that for now.

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Comparative Ontology

April 14th, 2009 admin

The Seman­tic Web has pop­u­lar­ized the con­cept of ontol­ogy. The usual def­i­n­i­tion one sees for the term is Gruber’s “spec­i­fi­ca­tion of a con­cep­tu­al­iza­tion” (Gru­ber 1993). The def­i­n­i­tion could use some unpack­ing. Essen­tially, it refers to the idea that the terms used by AI agents should be defined by ref­er­ence to a shared schema which clas­si­fies those terms. The shared schema, or spec­i­fi­ca­tion, sim­ply defines how terms are related to each other in a graph. More than a sim­ple data model, where the rela­tion­ships between enti­ties or objects are not explic­itly defined, an ontol­ogy also names the pos­si­ble rela­tion­ships between terms. So, instead of just hav­ing “address” as a field of the entity “per­son,” an ontol­ogy will explic­ity assert that a per­son has an address. So verbs (which are often buried in “pred­i­cates”) are an impor­tant part of ontolo­gies. In fact, one way to think of an ontol­ogy is to call it a data model with verbs. (Sort of.)

Ontolo­gies are use­ful for pro­gram­ming agents, which are just pro­grams that con­sume and pro­duce infor­ma­tion on their own. (I call them infophages.) So, when you pro­gram an agent to respond to a term, you have the agent’s pro­gram refer to an ontol­ogy to dis­am­biguate the term among syn­onyms, and to make log­i­cal infer­ences about the term. For exam­ple, if the agent encoun­ters the term “Socrates,” it will be found to be spec­i­fied as a mem­ber of the class “Human” and since “Human” will have the prop­erty “is Mor­tal,” the agent can trans­fer the prop­erty to “Socrates” too. (Truth, or valid­ity, is just trace­abil­ity within a ref­er­ence graph.)

Or, if the agent encoun­ters the word “Madonna,” and that term is for­mally spec­i­fied as part of an ontol­ogy (say, by using Tim Berners-Lee’s URI method), the agent will be able to trace its class to either “Pop Singers” or “Reli­gious Fig­ures” or “Chris­t­ian Iconog­ra­phy” or whatever.

Sometimes–often–ontologies are described as if they pro­vide “mean­ing” for agents. Even the term Seman­tic Web implies this. When intro­duced to novices, the Seman­tic Web is often intro­duced as bring­ing “mean­ing” to the web. I find this expla­na­tion mis­lead­ing at best. Mean­ing is much to too impor­tant of a word to describe what is going on here, which is sim­ply a layer of clas­si­fi­ca­tion being added to what would other wise be a list of terms. Ontolo­gies are just sys­tems of clas­si­fi­ca­tion for terms, a second-order set of terms that (1) increases the prob­a­bil­ity that an agent can process a term in a way that users will expect, and (2) adds a layer of con­nec­tiv­ity, above the raw ver­biage on the web, that decre­ses the aver­age dis­tance, or degress of sep­a­ra­tion, between any two terms.

So, ontolo­gies have two prop­er­ties that make them use­ful and, as I want to argue, use­fully viewed from a com­par­a­tive per­spec­tive. First, they intro­duce verbs into the mix of data mod­el­ling. Sec­ond, they are just sys­tems of clas­si­fi­ca­tion–like Aus­tralian totemic sys­tems, Mayan cal­en­dars, and West­ern philo­soph­i­cal ontolo­gies such as Aristotle’s and Leibniz’s.

Com­par­a­tivism will help us cre­ate bet­ter ontolo­gies, and bet­ter sys­tems for using ontolo­gies, in two ways.

First, com­par­a­tivism can train our atten­tion on the great rab­bit war­ren of words and mean­ings that lies at the heart of the osten­si­bly neat world of triples–I refer to the pred­i­cates. Although the nouns that com­prise the vocab­u­lar­ies for sub­jects and objects in RDF can be neatly spec­i­fied as ana­lytic tax­onomies of terms, pred­i­cates are sub­ject to no such rules, and can con­tain within them­selves whole sen­tences. Unlike the nouns, pred­i­cates mask a great deal of what Kant would call “syn­thetic judge­ments.” I pro­pose a soci­olin­guis­tic approach to the use of verbs embed­ded in the pred­i­cate sys­tems of linked data vocab­u­lar­ies that will pro­vide a bet­ter basis for craft­ing predicates.

Sec­ond, com­par­a­tivsm can help us move beyond set theory–useful as it is–to con­sider other total­iz­ing schemes for orga­niz­ing ideas, such as those described by anthro­pol­o­gists. I men­tioned totemic sys­tems, cal­en­dars, and West­ern ontolo­gies. But there are many oth­ers to con­sider. What is more, anthro­pol­o­gists have done a great deal to describe, clas­sify, inter­pret, and even explain these. Such an approach would be grounded in the fol­low­ing works, all of which define or grow out of the struc­tural­ist tra­di­tion within anthropology:

1. Emile Durkheim and Mar­cel Mauss, 1903, Prim­i­tive Classification.
2. Louis Dumont, 1966, Homo Hier­ar­chi­cus.
3. Michel Fou­cault, 1966, The Order of Things.
4. Claude Lévi-Strauss, 1968, The Sav­age Mind.
5. Vic­tor Tut­ner, 1969, The Rit­ual Process: Struc­ture and Anti-Structure.
   
6. Mary Dou­glas, 1970, Nat­ural Sym­bols.
7. Pierre Bour­dieu, 1977 [1972], Out­line of a The­ory of Prac­tice.
8. Alfred Gell, 1975, Meta­mor­pho­sis of the Cas­sowaries.
9. Rod­ney Need­ham, 1975, Poly­thetic Classification.
10. Edmund Leach, 1976, Cul­ture and Communication.
11. Mar­shall Sahlins, 1978, Cul­ture and Prac­ti­cal Rea­son.
12. Jad­ran Mim­ica, 1988, Inti­ma­tions of Infin­ity.

And so forth.

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