October 13th, 2009 admin
Musings on Zacks, the Hippocampus, and Kafka
NOTE: This article has been modified slightly since I originally posted it. The section on the hippocampus has been subordinated to an inline note. It is interesting (at least I think so) but not part of the main argument I’m trying to make here.
A few weeks ago I had the good fortune of seeing Jeff Zacks give a talk entitled “Film, Narration, and Cognitive Neuroscience” at the Curry School of Education at U.Va. He was invited to speak by my colleague Glen Bull as part of the school’s Tea & Technology series (every Thursday at noon in Ruffner Library if you’re around). It was an excellent talk not only for its content, but for Zacks’ gift of clarity. At no point did the science overwhelm, and the talk had the useful effect of raising lots of interesting questions in
my mind and in the minds of others.
Zacks’ thesis is relatively straightforward: human beings have the capacity to perceive events as a series of discrete segments, and this capacity to segment events is correlated with the long-term memory of those events, as well as the ability to focus on and form concepts about the goings on in an event. There are big cognitive pay-offs to performing this work of segmentation, pay-offs which (predictably) are thought to correlate to evolutionary advantage. Interestingly, the boundaries that people spontaneously define for events — such as a sequence in a French film or a film of a man washing dishes (two examples used in Zacks’ experiments) — are widely shared. Where there is variance, subjects are either older or suffering from dementia (which gives me a really good feeling about the aging process). The mechanism for segmenting thus appears to be hard-coded and deeply rooted, probably in the hippocampus.
One of the things that intrigues me about Zacks’ work is the light it sheds on the hippocampus — the odd, chili pepper shaped organ that sits in the center of the brain. Conventional wisdom (based on research with rats’ brains, it turns out) is that this region of the brain is devoted to spatial orientation and long term memory. This is what a neuroscientist friend of mine told me in the ‘80s, and it’s reflected in the Wikipedia article linked to above. These two functions may appear to have no obvious relationship, but as a structural cultural anthropologist, it has always made sense to me — to my way of thinking, the hippocampus must be involved with the process of symbolization, the encoding of experiences into symbolic structures, many of whose structural armatures map onto spatial metaphors, such as left|right, up|down, etc.
Now what Zacks (or some recent research he builds on) adds to the picture is that the hippocampus also plays a role in segmentation where time perception and short term memory are in operation. So there is some sense in which the proportion — short-term memory : time :: long-term memory : space — links these core ontological dimensions at the basis of cognition. I find this idea very interesting because (1) it correlates memory with ontology, and (2) it’s the opposite of what you might think — surely time perception (perception beyond the present) involves long-term memory, and space perception would scaffold short-term memory. Perhaps in the transduction of experience into memory, such a reversal is necessary. (Or perhaps this view is the product of too philosophical a mind, one prone to seeing connections between abstractions where there are none.)
One of the most interesting parts of Zacks’ thesis is the process by which event boundaries are perceived, or rather, defined by the brain. Apparently, boundaries are inserted where the brain experiences what Zacks calls “prediction error” — when things break a pattern of repetition and thus signal to the brain a boundary that is used to construct the temporal model for the event — its typical sequence. Zacks did not mention this, but I would be surprised if this capacity were not in some way connected with the capacity of the brain to perceive information in Shannons’s sense. For prediction error is an excellent name for the newness that his negative entropy equation defines. My tentative hypothesis is that we must be wired to both perceive information in this sense, and to make use of it in the formation of perceptual structures which, in turn, become the materials from which cognitive structures are built.
Now I mention this because the response of the audience — comprised mainly of educational experts — and of Zacks himself is that one practical lesson from his research is that creators of narrative content, such as film, should make an effort to provide more obvious segmentation in their products. Clearly, if this is how the brain works, we should work this way too.
I think this is a major fallacy that pervades the reception of brain science research. People tend to assume that if the brain works a certain way, then so should we. I call it the fallacy of brain-behavior mirroring (at least until I come up with a better name), a more recent variant of the mirror of nature fallacy described by Rorty. For example, since we know (since Kant and then Gestalt psychology) that the brain actively constructs objects from experience, then, the argument goes, we should have students actively construct things too. But clearly, if the brain already works a certain way, then it works that way — in spite of, or perhaps because of, how we behave, oblivious to a detailed description of its workings. In the case of event segmentation, it seems clear to me that Zacks’ research suggests an opposite lesson — it says that people who can perceive prediction failures can also segment experiences, and thereby gain cognitively. If so, then the lesson is to get good at perceiving and creating event boundaries, which requires not pre-segmented media, but the opposite — hard to grasp art, stuff that violates expectations and rewards the perciever with a different perspective. In fact, giving students media with well defined boundaries may cause their capacity to construct boundaries to atrophy, much as caffeine causes our adrenal glands to shrink. (I know, it’s a good reason to stop drinking coffee.)
Now it turns out that some research form the University of California at Santa Barbara corroborates this view. According to the headline of the New York Times,’ piece in this work, nonsense — such as the absurdist work of Kafka — sharpens the intellect. (Another summary of this research is entitled This is Your Brain on Kafka.) Essentially, your brain has to work hard to make sense of things, which it is evolved to do, and this has the side effect of making you smarter, or at least sharper in the period following the effort to make sense where there is none. And what is nonsense but prediction failure on a large scale?
So, what is the pedagogical and media design lesson here? Learning Teaching is not about making content easy to ingest, it’s about creating environments where students can play this game of meaning formation, which isn’t always stress-free. Marketers may disagree, but they are in the business of indoctrination, not teaching.
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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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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 began as a cultural materialist but had a road to Damascus experience in the 1970s in which he got culture. You may recognize his name as the unfortunate target of fellow anthropologist Gananath Obeyesekere, who criticized Sahlins’ interpretation of the events leading to Captain Cook’s death in Hawai’i as orientalist. In fact, Obeyesekere’s criticism was an exercise in occidentalist stereotyping and, in any case, Sahlins’ control of the material eventually proved his critic’s position incoherent.
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 this, Sahlins is consistent with both Victor Turner’s understanding of processual structure in ritual behavior, and Bourdieu’s concept of the habitus which mediates, through improvization, the “dialectic of objectification and embodiment.” In fact, I believe that the revised structuralism developed by these anthropologists (and others) is coherent enough to deserve a name; I call it “neostructuralism.”
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.
Texts, as forms of discourse, can be likened to rituals and prophetic movements. Novels in particular are efforts to both makes sense of an influence the world, a task in which they often succeed. They deploy a set of categories that make sense, to the author at least, in a certain time and place. The risk of reference works at various levels–from the basal meanings of words out of which tropes are created, to the description of scenes in which the unsaid is shared among a presumed audience, to more elaborate allegorical mappings of fictional characters to real persons. But the referrential risk of textuality is compounded as the message is removed from its original personal, cultural, and historical contexts, and the world of the text is forced to fit new contexts for new readers. Hermeneutics arose as a method to retrieve meanings lost in this way; Roman Law and the Christian Bible being two major examples of distanced texts being applied and reapplied to new situations. The French philosopher and hereneutic theorist Paul Ricoeur called the result of this risk the “surplus of meaning” in a text, and saw it at as an opportunity for a kind of ontological excavation.
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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May 11th, 2009 admin
I am all for user-driven design methodologies. My instinct is to distrust the Central IT ethos of “we know better” because “we think more rationally about things” and all that. That perspective is based on a simultaneous over-valuing of a linear, rational notion of process (“planning”) and a grudging acceptance of user behavior as “cultural” and therefore outside the scope a requirements gathering process.
The term “non-functional requirements” speaks volumes and captures the Central IT attitude very well. Under that category, the whole point of effective software design is swept under the rug. We know that software will be most effective when it adapts to user behavior and vice versa, but we often sidestep that issue, hoping for incremental, evolutionary changes to produce the desired effects over the long run. We miss the opportunity to innovate, leaving that to the less timid.
But I also find that user-centric methodologies are based on naive assumptions about what users want, or who The User is, or what the point of the user research is in the first place. Unless you have a very restricted audience for your software–and admittedly one often does–it is very difficult to translate the views of a few people, whether captured by focus group, survey, or even participant-observation, into generalized principles for an application. Ultimately, good design is what works, and we retrospectively attribute success to our process. But we really have no clue.
What is it that one is capturing by user-centric research, anyway? The attitudes and dispositions within a class of individuals? This can’t be it. User attitudes and mental models are highly variable, and they are mutable because humans are adaptive, more than we think. If you build software based on some static notion of what users want, what they say they want, you will miss the effect software has on redefining what they really want. This is because users inhabit cultural environments, and software inevitably has effects on those environments. If you focus too much on the abstract user–what’s “in” the user–you will often have the feeling of the goal posts moving. Or you may end up dismissing the user altogether as fickle and irresponsible, and go on with your own design ideas. If you design software for a living, I am sure you know what I am talking about.
I think the proper focus of user-centric software design has to be the user-in-context. That is, not the user but the Situation. But sutuation defined in a specific, rigorous way. Situation as the objective, institutional framework of power and infrastructure in which people work. This is difficult terrain to study, hedged in as it is by all sort of taboos and misrecognitions that keep the social gears moving. Let me give you an example.
One of the areas where the Central IT software design ethos dominates is in the area of document management. Two factors drive the design of solutions: (1) developers assume (know) that paperlessness is a Good Thing, and (2) the paper-based workflows that users are enmeshed in are so crufty, complex, and idiosyncratic that it is impossible for users to describe them in enough detail to re-engineer them. The result is that the digital document management solution will almost always build around people’s behavior, or else it will break workflows where it has to. So, instead of stepping back and rethinking what the data flows entailed by a paper form entail, or taking advantage of the metasocial moment and asking Why are We Doing This in the First Place, document-logic is reproduced in the software. The efffect is not to reproduce the old way, and make it more efficient. It is something unpredictable and bound to have hidden consequences, not all of which can be good. Most likely, we’ve preserved the notorious stupidity of bureaucracies and have ensured its continued survival in a mutant and more powerful form. Because once categories get encoded in institutional databases, the tail wags the dog. Think health insurance.
So, what to do? I suggest that we pursue theory-driven design. We actually try to make sense of the sociology and anthropology of bureaucracies and operationalize the best ideas in these discourses as design principles. We think of how software behaves as an assemblage of artifacts in a living cultural environment. This is not social engineering, nor is it to tread the tired path of “organizational behavior,” a field that is too closely tied to the executive perspective. It is to pursue a rich, empirical understanding of software in the wild, or at least, the office.
Theory-driven design is not anti-empirical. It is the opposite: for a good theory generates testable hypotheses. It gives a framework to user-centric research beyond the unanswerable quest for what users really want. As they say, there is nothing so practical as a good theory.
A good starting point might be to take Ted Nelson’s ideas about documents and hypertext and combine them with, say, David Graeber’s critical anthropology of bureaucracy. Not to condone the anarchism of Graeber, but to lever the authenticity of perspective he brings to a discussion about the role of documents in the organization. Reading his essay, “Beyond Power/Knowledge an exploration of the relation of power, ignorance and stupidity,” it is hard not to believe that a radical rethinking of the document, and document-logic, would not benefit from his perspective.
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May 4th, 2009 admin
I suppose it is the prerogative of different generations to simultaneously dismiss and retrieve old ideas by introducing new words for them. I have in mind words like “metacognition” and “knowledge management.” In both cases there is an existing word that more or less describes the referent of the new(ish) word: epistemology and education respectively. Both metacognition and epistemology refer to, roughly, the activity of “thinking about thinking,” and the core mission of education is the management of knowledge — producing it, storing it, reproducing it, etc. However, in each case, the intent of the new word is clearly different from the older one, and this difference can be attributed to a different organizational context: knowledge management is about education and research in corporate settings (now defined as “knowledge producers”), as opposed to society or the world at large, while metacognition has flourished within the relatively narrow context of academic departments of education.
But why the complete absence of the old words in the new discourses? Why not call metacognition something like “applied epistemology”? Or knowledge management “corporate education” or “corporate teaching and learning”? It can’t be for lack of familiarity with the older words. Nor can we assume that the newer words are more “sticky” and easier to use; that just begs the question. I think it’s clear that the problem with these constructions is their connotations: they carry too much semantic baggage.
But now here’s the thing: the new words do not simply stand alongside the old ones, they actually seem to take their places. The new words take the place of the old words at an abstract level–but then replace the implicit social meanings in the process. The effect is to implicitly usher in newer or different institutions in the space reserved for the old. So knoweldge management is about education, yes, but education in a business setting where knowledge is viewed as a competitive advantage, not a general good for the betterent of humankind. And, eventually, this will have implications for education itself, as essays like “Applying Corporate Knowledge Management Practices in Higher Education” become more common.
Similarly, metacognition is about epistemology, but not as an abstract philosophical concern, nor one tied to the remote activity of a purely scientific enterprise as it once was; it is epistemology in the service of classroom teaching and learning, where the users of the word no doubt think it belongs. So the effect of the word “metacognition” is to usher out the ivory tower and to replace it with the more populist institution of the classroom. And this meaning is consistent with the current ethos of educational populism, as expressed in wider ideas like connectivism.
So language really does embody the social: these words are actually the encodings and amplifiers of social changes happening right now. Perhaps those of us familiar with the older names of things would do well to note these shifts and pay attention to their institutional commitments.
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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:
- Human ontologies are not plans.
- 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.
- 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).
- Human ontologies are local and situated.
- Human ontologies evolve.
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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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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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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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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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