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Well, I set a date for defense of my dissertation proposal. It’ll be on June 12, 2008 at 9:00AM. I’ve got a few more weeks to refine and finish up the proposal. I want to get it to my committee members about four weeks prior.

So what’s my dissertation going to be about? The tentative title is The Ontology of Tags. It’s basically an exploration of the use of tags as representations of cultural schemas, which are the flexible and adaptable cognitive structures that comprise the conceptualizations of an ontology. I adopt a Heideggerian existentialist perspective on ontology, which is phenomenological rather than categorical.

The formal ontologies constructed for information systems today are based on a classical notion of ontology that consists of complex taxonomies comprised of categories and relationships between them. However, formal ontologies are problematic in that they simultaneously crystallize and decontextualize information, which in order to be meaningful must be adaptive in context. In trying to construct a correct taxonomical system, formal ontologies are focused on syntactic precision rather than meaningful exchange of information. It is not fair to claim that syntax is irrelevant, but the meaning we make of information is dependent upon more than its syntactic structure. The semantic content of information is dependent upon the context in which it exists. For true semantic interoperability to occur among diverse information systems, within or across domains, information must be contextualized.

The way to introduce this contextualization is through the notion of culture. Culture is a phenomenon that emerges through the interplay of intrapersonal cognitive structures (i.e., schemas) and the extrapersonal structures of the world. Culture shapes the way we conceptualize the entities and phenomena of the world of our experience. What I describe as culture, Heidegger describes as background, in which we are continually immersed as Dasein. We are always being-in-the-world. Moreover, we are always being-in-becoming, emerging into the world as it were.

My thesis is that ontologies are more properly conceptualized as cultural schemas (i.e., shared cognitive schemas) rather than taxonomical structures. Situating them as cultural schemas means that they are inherently flexible and adaptable. I believe we can create schematic or phenomenological ontologies for information systems using sets of tags and folksonomies, which can complement and supplement the formal ontologies that are developed by ontology engineers and information scientists.

So, that’s my thesis and proposal in a nutshell. Although I try to explain it as simply as I can, most people still have trouble grasping it. I consider myself very lucky to have a committee that gets it. And each brings a particular expertise to the committee that touches on the major components of my justification and research project. I’m really excited and looking forward to June 12th.

Tags:cultural schemas, culture, folksonomies, Heidegger, ontologies, ontology, semantics tags
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6th Internet Identity Workshop Coming Up :: Off the Top :: vanderwal.net

Discussions around persona (not the IA persona variety) and identity abound and the need for services that grasp these differences are worked through. The need for better understanding the incredible value the role of identity in tagging services has also been discussed here, which is something many services do not grasp and are doing a dis-service to the people who want to tag items in their own perspective and context to ease their own refinding of the object (Twine really needs a much better understanding of tagging as their automated tagging is incredibly poor and missing many tangents for understanding that need to be applied for full and proper understanding of the objects in their service).

As I began my research into computational ontologies, I immediately realized that the promise of interoperability that an ontology was supposed to provide was basically unachievable in its current manifestation. Ontology is the theory of being that has ancient roots in philosophy. Aristotle’s elements, for example, were used as a taxonomic system to describe the existence of things in the world. Ontology has been confused, in my opinion, for classification and categorization systems. And for many philosophers throughout the ages the assumption was that there was a single, objective universe that existed, with the implication that there was a single ontology that could be constructed to describe it. The Aristotelian tradition of classification has continued through the ages has spawned studies in the philosophy of language, and the study of meaning and reference. Language, however, is a symbolic reference system and its traditional primacy in ontology perpetuates the notion of ontology as a classification system. To describe a thing, however, is not to necessarily understand its being. But we are trapped by language because we are forced to use it to communicate with one another about the nature of being of things. Existentialist philosophy shows us one way out of this dilemma of being able to describe the being of entities and phenomena in the world without confusing that being with the categories that are used to describe it. Existentialist philosophy always spoke to me since I first began reading it as an undergraduate. It spurred in me an insatiable desire to understand how different peoples conceptualized the world and what they perceived to exist.

The assumption that different peoples had different conceptualizations of the world wasn’t necessarily a new one, but the very idea that “our” particular conceptualization of it wasn’t necessarily the “correct and objective one” was a radical notion born of the postmodern age. It is in this context that I first encountered existentialist philosophy. It leads me to a completely different conceptualization of ontology than has been traditionally understood. It also led Quine [1] to conceive of multiple domain ontologies in contrast to a single ontology shared by all.

Domain ontologies made sense. The ontological commitments made by physicists in terms of mass and energy were completely different than the conceptualizations of chemists or biologists had of mass and energy. As we developed our independent domain knowledge, our conceptualizations of the same or similar entities or phenomena became increasingly complex and varied from one another. Enter computers and the digitization of information, the digitization of these complex conceptualizations we wanted to share. What better way to share than to develop an ontology of the conceptual relationships of the information contained in the information system? The ontology would provide the structure for communicating our conceptualizations! It’ll be brilliant!

As I began to understand what computational ontologies were and how they were constructed. I saw that they were categorization systems–slightly more complex perhaps than a typical taxonomy, but still rigid and mistakenly confusing the description of the entity or phenomenon with its being. The idea that language can fully represent a conceptualization remains at the core of computational ontology development. Enter me and my radical Heideggerian and relativistic notions…

Ontology refers to the underlying conceptualization we have of phenomena in the universe, not the language employed in its description. What we perceive to exist is largely based on our cultural upbringing and training. We perceive what we are “culturally programmed” to perceive. This is true for national/ethnic cultural groupings as much as it is true for domain specialists who share a particular conceptualization. Ontology, therefore, is dependent upon culture, and just as there are many cultures there can also be many ontologies. Moreover, ontologies are cultural, they are the shared conceptualizations of a culture.

Creating logical formalisms to describe these cultural conceptualizations fails to account for the fact that culture is an emergent phenomenon. It emerges from the interplay of intrapersonal cognitive schemas and the extrapersonal structures of the world. Our shared cognitive (i.e., cultural) schemas are flexible and adaptable, allowing us flexibility in understanding and adaptability to context. Ontologies constructed as logical formalisms eliminate these essential qualities, crystallizing the conceptualization as a rigid definition and hierarchy of relationships, and decontextualizing it, thereby voiding it of its semantic content. How can we overcome these difficulties?

It seems obvious to me that ontologies are cultural schemas. We should construct them in such a way that reflects their nature. We need a connectionist element to our ontologies that allows for the flexibility and adaptation they exhibit as cultural schemas. Ontologies, from this perspective are more like folksonomies than logical formalisms.

Folksonomies are constructed with tags. They continue to grow and change, but are relatively stable over periods of time, just as cultural schemas are. Tags are individualized, but when aggregated into tag sets or tagclouds represent a cultural understanding of the entities and phenomena by a culture. Tags are lexical units that represent the entry points into the complex networks of conceptual associations that comprise our schemas, and hence our ontologies.

The difficulty with this notion is that an individual can have many cultural identities, many types of shared conceptualizations that would make the interpretation of a particular tag difficult. Without knowing the cultural identity of the person creating or offering that tag, we cannot know its semantic content. It remains decontextualized. Identity is an important element in understanding ontologies. For example, a single individual could tag a geographic space or entity as part of a geographic ontology. That individual may tag it “exciting” if he were a hunter, but he might also tag it “dangerous” if he is also a father. Hunter and father are two cultural identities of a single person. And knowing his cultural identities are essential to properly interpreting the tags he has created and added to the folksonomy.

Van der Wal is right. Identity is an important element in the study of tagging. The reason it is important is that it provides context for semantic understanding of the entity or phenomenon being tagged. One way to understand how and why it is important is by putting into the context of ontologies as cultural schemas, and recognizing that tags represent entry points into a complex network of conceptual associations but are not the conceptualizations themselves.

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[1] Quine, W. V. O. (1953) “On What There Is”, as reprinted in From a Logical Point of View, New York: Harper & Row.

Tags:cultural schemas, emergent, identity, ontologies, tagging tags
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[This is not meant to be a well-written, coherent essay. Rather, it is simply my reflections of some of the concepts discussed in: Uschold, M. (2003) Where Are the Semantics in the Semantic Web? AI Magazine 24(3): 25-36.]

Talking about an agent’s ontology, Uschold says:

If it were written only for people to understand, this specification could be a glossary.

It is a simple statement that belies the complexity of human cognition and its ability to function as a connectionist network. Humans are able to read a word and its definition and recall a complex of associations and experiences to create meaning, to understand its semantic content and the ontological commitments that are shared within a community. An agent doesn’t have this ability and must rely on explicit specifications (ala Gruber) and formal languages to communicate its meaning to other agents. Successful communication is the goal, but machines are confronted with heterogeneous sources, “different ontology representation languages, different modeling styles, and an inconsistent use of terminology.”

Uschold describes the semantic continuum:

Semantics can be implicit, existing only in the minds of the humans who communicate and build web applications. They can also be explicit and informal, or they can be formal. The further I move along the continuum, the less ambiguity there is, and the more likely it is to have interoperable, robust, and correctly functioning web applications.

The difficulty with implicit semantics is their inherent ambiguity. People don’t always agree about the meaning of a term. Yet this is exactly where people live, so to speak. Humans engage in dialogue and discourse in order to clarify meaning. Through this interaction, we make the implicit semantics explicit. Engaging with machines isn’t as interactive, typically. We don’t expect our machines to be intelligent in terms of understanding semantic content and to be able to express that understanding as humans do. We also don’t expect that machines will be able to assess contextual cues that we use as humans to make meaning of our interactions with others, nor do we expect machines to remember our previous interactions with them (unless we explicitly encode that into the preferences of each particular application or service).

As Uschold continues to describe the continuum, moving towards the more formally expressed semantics for machine processing, it occurs to me that what we are doing is conforming our natural ways of interacting to the requirements of a machine. Why are we not trying to make the machine conform to our natural way of doing things? Shouldn’t the goal be to enable the machine to dynamically discover the meaning of content and how to use it? This, as it turns out, is what Uschold tackles next, machine-proccessible semantics:

For a computer to automatically determine the intended meaning of a given term in an ontology is an impossible task, in principle; it would require seeing into the mind of the author. Therefore, a computer cannot determine whether the intended meaning of two terms is the same.

Getting an agent to understand semantic content can be accomplished by hardwiring the meaning of terms and procedures into them, or through accessing external, publicly agreed to declarations such as ontologies. The heterogeneity of information and meaning makes both of these strategies limited. Information from different web sites may need to be integrated, so we require some way to map the different meanings to each other. Ontologies in conjunction with semantic mapping and translation techniques play a key role in semantic integration (Uschold citing Bradshaw et al. 2003).

Uschold speaks of human consensus regarding the use of terms. He refers to this consensus as an implicit shared semantic repository. I use the term cultural schemas to refer to this shared cognitive “repository.”

So, where are the semantics in the semantic web? Uschold offers these six explanations:

1. They are often just in the human-as-unstated assumptions derived from implicit consensus (e.g., price on a travle or bookseller web site).
2. They are informal specification documents, e.g., the semantics of UML or RDF SCHEMA.
3. They are hardwired in implemented code (e.g., in UML and RDF tools and in web shopping agents).
4. They are in formal specifications to help humans understand or write code (e.g., a modal logic specification of meaning of inform in an agent communication language).
5. They are formally encoded for machine processing, (e.g., fuel-pump has (superclasses SHO: pump)).
6. They are in the axiomatic and model-theoretic semantics of representation languages (e.g., the formal semantics of RDF).

Tags:cognition, concepts, cultural schemas, formal ontology, information, language, ontologies, semantics semantic web
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Explaining what ontology is is difficult enough. Everyone seems to have their own idea about what it is. I have my own ideas about what ontology is and how they should be constructed. Even more difficult is trying to explain what an ontologist does. The Preface to the FOIS’06 Proceedings crafts an extraordinary description of ontology and the work of ontologists as theoreticians and engineers.

Formal Ontology in Information Systems, Proceedings of the Fourth International Conference (FOIS 2006), Brandon Bennett and Christiane Fellbaum (eds.), IOS Press

Preface

Since ancient times, ontology, the analysis and categorisation of what exists, has been fundamental to philosophical enquiry. But, until recently, ontology has been seen as an abstract, purely theoretical discipline, far removed from the practical applications of science. However, with the increasing use of sophisticated computerised information systems, solving problems of an ontological nature is now key to the effective use of technologies supporting a wide range of human activities. The ship of Theseus and the tail of Tibbles the cat are no longer merely amusing puzzles. We employ databases and software applications to deal with everything from ships and ship building to anatomy and amputations. When we design a computer to take stock of a ship yard or check that all goes well at the veterinary hospital, we need to ensure that our system operates in a consistent and reliable way even when manipulating information that involves subtle issues of semantics and identity. So, whereas ontologists may once have shied away from practical problems, now the practicalities of achieving cohesion in an information-based society demand that attention must be paid to ontology.

Researchers in such areas as artificial intelligence, formal and computational linguistics, biomedical informatics, conceptual modeling, knowledge engineering and information retrieval have come to realise that a solid foundation for their research calls for serious work in ontology, understood as a general theory of the types of entities and relations that make up their respective domains of inquiry. In all these areas, attention is now being focused on the content of information rather than on just the formats and languages used to represent information. The clearest example of this development is provided by the many initiatives growing up around the project of the Semantic Web. And, as the need for integrating research in these different fields arises, so does the realisation that strong principles for building well-founded ontologies might provide significant advantages over ad hoc, case-based solutions. The tools of formal ontology address precisely these needs, but a real effort is required in order to apply such philosophical tools to the domain of information systems. Reciprocally, research in the information sciences raises specific ontological questions which call for further philosophical investigations.

Tags:concepts, fois, formal ontology, informatics, information, language, ontologies, philosophy, science semantics
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Mental map of London at Mauro Cherubini’s moleskine

Mauro posts about an interesting use of tags as applied to maps. This is one of the things that I’m interested in researching. I think it’s possible to develop an emergent and adaptable ontology of geographic spaces using tags. In order to do so, one needs to link information about the particular identity/role perspective in order to be able to interpret the tag appropriately. In this case, the identity would be Tourist.

There’s also an issue of visualization, I think. As you can see on the map, the tagcloud is superimposed on a map of a particular scale. Zooming in would help to disentangle the tagcloud and make the tags more readable, but we should be albe to scale the tagcloud as well so as to avoid the obfuscation of some tags by others. This is more problematic, of course, in that the number of tags could vary to a considerable degree, and the question arises as to whether we could ever provide a non-obfuscatory representation of tags when the number of tags is quite large.

Anyway, interesting stuff that is of interest to me.

Tags:emergent, folksonomies, geographic, geospatial, maps, ontologies, tagging tags
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Ontology is the theory of being. It asks the fundamental questions: What exists? What is real? Philosophers have been trying to work out the answer to these questions since at least the ancient Greeks first posed them. Ontology has been understood by philosophers as being singular. Ontology, if one were to be devised, would delineate all things that exist in the universe and their relationships with one another. From a philosophical perspective, there can be only one Ontology.

Things changed in the twentieth century. Scientists, in particular a guy named Quine, began to conceive of Ontology a theory of a specific domain. Since there were many domains and types of domain knowledge, it stood to reason that there were more than one ontology. The concept of multiple ontologies, each being a way of explaining the knowledge of a different domain, caught on among scientists. And ever since, scientists and philosophers have been trying to devise ontologies for their respective domains of research. They are trying to capture not only the things that comprise the domain, but also the concepts and processes each domain deems pertinent.

Information and computer scientists have devoted a lot of time and resources to developing ontologies. The impetus behind such research is the promise of interoperability and the sharing of data and information between information systems. The problem with computers is that they don’t grasp meaning. They can manipulate data and identify patterns of information, but they can’t create meaning for themselves or for humans. Ontologies are seen to be the keys to the kingdom, as it were, for the creation and sharing of meaning among the bits and bytes of data and information we have floating around in our information systems.

Researchers in information systems have been working on developing ontologies for a while. And they’ve failed miserably. There have only been a few successful ontologies developed, but they’re not generalizable. Why have ontology engineers and researchers failed? For many reasons, I think. First among them is their failure to understand what an ontology is–a taxonomy, a concept model, a concept map is not an ontology. Yet, time and again, researchers attempt to create rigid hierarchical structures that they think are ontologies. Second, they give primacy to their own biased worldview. They are convince that their scientific paradigms–to the exclusion of other paradigms, scientific or other–are the only valid or meaningful ways of understanding the world. They attempt to reduce the concepts and entities of a given domain to some form of quantitative measure–the only “real” measure of what exists in the world.

In combining the first two mistakes, they commit a third: neglecting schematic forms of cognition in favor of a symbolic processing paradigm. Their attempts to make ontologies interoperable amount to vocabulary matching strategies. Anyone who has ever done any language translation understands that there is often a lot of cultural filling-in that must happen in order to make the translation meaningful. There is no such thing as word-for-word translation. Yet, we keep searching for strategies that allow our machines to do just that.

Ontologies are not taxonomies. Ontologies are not intelligible as discreet quanta of information. And ontologies are not the result of symbolic processes. Ontologies are concepts, variable and schematic in nature. I also contend that they are emergent and akin to cultural schemas. How we can develop ontologies for information systems that reflect their emergent and adaptable nature is the focus of my research. I’ll have lots more to post about my theoretical perspectives and research. I just wanted to get the ball rolling.

Tags:concepts, cultural schemas, emergent, ontologies taxonomies
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I recently attended the Vespucci Initiative’s summer institute on geographic information science. It was held from 3-7 July 2006 outside of Florence, Italy. I’d never been to Italy before, and I had a fantastic time. It was my first foray into my own academic community, meeting with people who are doing research related to my own. I established a number of contacts with other graduate students, some of whom I hope to collaborate with in the future.

I got to share a lot of my ideas on the creation of ontologies for geographic information systems. My ideas are pretty radical and unlike the approach most ontology engineers take. I was a bit scared that people would think me insane, but the opposite turned out to be true. I was able to explain the complexity of my reasoning to academics as well as industry folks. They were intrigued by my ideas and my approach, so I came away from the workshop feeling pretty good about the work I’ve been doing over this last year. Of course, there are several more pieces of the puzzle that I have to work out, but I’m confident that I can contribute to the research and development of ontologies in information systems.

Firenze and Fiesole were beautiful. I didn’t care too much for the crowds in the city, and it was hot as hell, but being immersed in such an historic city and the Italian food and culture compensated. I did take a few pics, including some of il Duomo. I’d love to go back to Italy at some point and explore some other cities, like Venice, Genoa, and maybe even Rome.

Tags:fiesole, florence, geospatial, gis, italy, ontologies, sdi, semantics, tuscany vespucci
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