The Land of Chuck

Epistemology of models - and their output

2011-06-07T09:31:00.001-05:00

So when we have a model of some natural phenomena, what can we say about the results? Some amateur philosophical observations . . .

First, the model is a rational construct. It may be inspired or motivated by empirical observations of the referent it is abstracting, but the model in the end is a rational construct. That means it involves all of the limits of such constructs - such as limited view of the referent, perspective driven evaluation of possibilities, and so on.

Second, the access to results of the model involve using empirical observations of the operation of the model. So this is empiricism based on rationalism.

Or is it? What if the model is considered as a rational construct of a generative item? Still a rational construct, but designed to also create rational constructs - meaning the results of the model (which can be many things - models have many possible degrees of freedom as output.

So what does this say about the epistemology of model results? Do they represent some possible (possibly counterfactual?) version of "the original" the model is inspired by (the referent)? Not precisely. I believe they are nothing more than the rational output of a rational construct, but they are inspired by the referent. Within certain identified bounded differences, they can serve as an abstraction for study or to reveal certain behavioral phenomena - but they are not epistemologically equivalent. More thoughts later.

Tags: modeling, epistemology, philosophy

Simulation as a Symbol of Meaning

2010-04-27T17:48:00.005-05:00

These are a couple of board captures from a recent conversation on the relationship between the Semiotic Triangle (or Triangle of Reference) and the effort of representing some referent within a simulation (by first modeling it).

If the referent is the original object, in ideal form (whatever that is - meaning that all perceptions bring prejudice, so that in a Hume-like sense we can never know the ideal form, only our perceptions of the form), then a model of that referent is a conceptualization of it (much in the way that we talk about conceptual models as the blueprint for data modeling, and that an ontological representation is the expression of a conceptualization). By going one step further, and expressing that model in a simulation that mimics the dynamic existence of the referent (albeit, in some abstracted way - such as in a computer simulation), then the simulation becomes the expressed symbol representing the referent.

This highlights two prejudices that I (and others at the VMASC research group I interact with) have, namely that the act of going from referent to simulation really encompasses two different paradigms - the modeling paradigm (where we seek to understand the referent, in terms of some theory or model), and the simulation paradigm where that model (or theory) is then given form in a method that can give it dynamic existence (life?) over time, taking some inputs as the initial state of that "life", follow the strictures of the model (theory) and progress the processes of the model over time to induce changes to the objects and relations amongst those objects.

An interesting idea, if only because it implies that a simulation is a symbol for some referent. Much as a word (in natural language) is a symbol for some referent.

This reliance on the earliest version of the semiotic triangle leaves out an important stage in the transference of meaning from one agent to another - and that is understanding (or, more formally, in the domain of M&S, the agreement of one model with another).

Regardless of the flaws, the triangle is an interesting tool in understanding what is "modeling and simulation". And it can be seen (from the diagrams following) that there is some effort at reimposing the triangle on each of the vertical arms of the original triangle - (1) going from referent to model, and (2) going from model to simulation. An interesting theory like the triangle of reference is always coming up again and again the more you consider it in additional contexts...

Tags: semiotics, modeling, simulation, semantics, ontology

primitives of meaning - meet bundle theory

2010-04-02T09:38:00.003-05:00

My idea of primitives of meaning to describe a conceptual entity (by identifying all of the atomic concepts that combine to make the "whole" entity) is essentially the same as bundle theory, but I was (sadly) unaware of that theory when I did my writing on the atomic-concept based ontology for modeling and simulation (2005-2006) that led to my master's theory.

For a brief introduction to Bundle Theory see this wikipedia entry.

One of the things that Included in my model of an ontology for modeled worlds, is that the components are (1) concepts, (2) entities which are a combination of a set of concepts, (3) relationships between concepts, (4) rules determining under what conditions the relationships are valid. This is a system that is vulnerable to the same complaints about compresence that bundle theory is vulnerable to. However, since my theory is to apply to a modeled world that can be expressed, I don't think that the language/reality vulnerability of bundle theory applies here. By that I mean, since the point of my ontology theory is to provide an ontology for expressing the meaning of a world that can be expressed in a human generated artifact, an artifact about which questions concerning the described world are decidable, then the number and nature of relationships between (what I call) entities and their bundled concepts is countable and finite. But I may be wrong. :)

Tags: bundle theory

Modeling paradigms for modeling the Ontological elements of a PMESII environment

2009-10-20T10:23:00.002-05:00

In appendix C of Behavioral Modeling and Simulation: From Individuals to Societies there is a decent overview of some modeling techniques to capture PMESII factors.

These approaches/techniques include:
Concept Maps
Concept Graphs
Social Networks
Casual Graphs
Systems Dynamics Model
Neural Networks
Situation Theory

The link above gives a nice reference to particular appendix, or the book is available for browsing here:

Tags:

More on Topology

2009-10-15T09:18:00.003-05:00

A few more decent references on topology representing a couple of decades worth of text books on the subject (1961, 1970, 1980).

First this is from 1961 -

Here is one from 1970 -

And finally, from 1980 -

Tags: topology

System Topology

2009-10-15T09:01:00.003-05:00

I rely on System Topology in the same that a network engineer for an information network would refer to a Network Topology. Only I am referring to the interconnected processes, and their relations amongst each other (as captured in the IDEF series of diagrams, or more recently, by Sowa's claim that a system is much more appropriately looked at as an interconnected graph of processes, rather than a group of data/object states, that only use process as a connective tissue).

A nice little definition (from Wolfram Mathworld) -

Topology is the mathematical study of the properties that are preserved through deformations, twistings, and stretchings of objects. Tearing, however, is not allowed. A circle is topologically equivalent to an ellipse (into which it can be deformed by stretching) and a sphere is equivalent to an ellipsoid. Similarly, the set of all possible positions of the hour hand of a clock is topologically equivalent to a circle (i.e., a one-dimensional closed curve with no intersections that can be embedded in two-dimensional space), the set of all possible positions of the hour and minute hands taken together is topologically equivalent to the surface of a torus (i.e., a two-dimensional a surface that can be embedded in three-dimensional space), and the set of all possible positions of the hour, minute, and second hands taken together are topologically equivalent to a three-dimensional object.

My intention is to use the term system topology to refer to the overall graph of interconnected processes within a system, which I submit is potentially dynamic and can be potentially changed as much as the value or nature of objects affected by those processes.

A decent book (compliments of Google Books, once again) introducing the mathematics of topology . . .

Tags: system topology

Data Modeling - the quest for a good definition of Conceptual Model

2009-09-09T18:06:00.002-05:00

Some promising results are herein:

Also Interesting:

Tags: data modeling

Dimensions of Processes (1) - Time and Temporal Placement

2009-08-29T22:59:00.002-05:00

The first dimension I am exploring, concerning a methodical decomposition of process, is the dimension of time and temporal placement of the process within its universe of occurrence.

First, on spatial reasoning, there is an informal introduction to the whole concept on wikipedia, of which the salient point (for automata) is:

Spatial-temporal reasoning is also studied in computer science. It aims at describing the common-sense background knowledge on which our human perspective on the physical reality is based. Methodologically, qualitative constraint calculi restrict the vocabulary of rich mathematical theories dealing with temporal or spatial entities such that specific aspects of these theories can be treated within decidable fragments with simple qualitative (non-metric) languages. Contrary to mathematical or physical theories about space and time, qualitative constraint calculi allow for rather inexpensive reasoning about entities located in space and time. For this reason, the limited expressiveness of qualitative representation formalism calculi is a benefit if such reasoning tasks need to be integrated in applications. For example, some of these calculi may be implemented for handling spatial GIS queries efficiently and some may be used for navigating, and communicating with, a mobile robot.

Much ink has been spilt on this topic in the artificial intelligence community - on temporal relationships and temporal reasoning. In beginning my review in this area, I will take the Elsevier handbook on Temporal Reasoning as my root node, and begin exploring the research of the PhDs whose work is featured there.

First the three editors

Next the contributing authors

Side Topics:

Qualitative Spatial Reasoning using Constraint Calculi by Renz and Nebel

Guido Governatori very interesting series of publications on related topics

Approximate Qualitative Temporal Reasoning by Thomas Bittner

Tags: time, temporal reasoning, processes

Artificial Intelligence Applications Institute

2008-04-14T11:07:00.003-05:00

Artificial Intelligence Applications Institute Nice looking organization, with some interesting links. Associated with Edinburgh University, so it is reasonable to assume legitimacy of the organization (rather than a group using AI as just a buzzword to generate business).

Tags: artificial intelligence

The Knowledge Representation Requirements Model

2008-03-18T23:46:00.003-05:00

Laszlo's Pyramid of Meaning is certainly an interesting way to view the presentation of meaning. It is an upside down triangle, with the narrowest point being "data", which then ascends through "information", "knowledge", and on up through "comprehension", "understanding", "wisdom", and finally "enlightenment". It looks like this (sort of)...

. . . . . enlightenment . . . . . .
. . . . . . wisdom. . . . . . .
. . . understanding . . . .
. . . comprehension . .
. . . knowledge . .
. information .
. . data. .

The objection that I have to the Laszlo pyramid, for my work at least, is that it seems to blur knowledge representation (for automata) at the lower levels, and then knowledge, epistemology, mereology, and a bunch of natural language concepts at the upper levels.

Because of this, I think that my own Knowledge Representation Requirements Model will serve as a better benchmark for what I want to show. It is more in line with the ontological representation method I am proposing, and also in line with the Levels of Conceptual Interoperability Model.

The lowest level of the KRRM is data. Data with semantic identification becomes information. Information in context becomes knowledge. Knowledge in a time-senstive context becomes awareness. Awareness subject to comprehending context changes becomes understanding.

Understanding
Awareness
Knowledge
Information
Data

More later...

Tags: enlightenment, wisdom, understanding, comprehension, knowledge, information, data, knowledge representation

Does Artificial Intelligence worm its way into Studies of Cognition

2008-03-05T13:41:00.003-05:00

Artificial Intelligence and Study of Cognition I
Artificial Intelligence and Study of Cognition II

Interesting article (two parts) discussig AI and cognition studies. Often, in the literature, the second is seen as (partially) a rebranding of the first, but I have felt that there is more difference than overlap. Nice to see this author agrees.

Tags: ai, cognition

Comparing

2008-03-05T13:34:00.003-05:00

Cognitive Distortion

Interesting to see how these sorts of "leaps in thinking" compare to the techniques of analogical reasoning

Tags: cognition, cognitive distortion, analogic reasoning, artificial intelligence

Why the Semantic Web will Succeed

2007-03-22T09:31:00.000-05:00

Half an Hour: Why the Semantic Web Will Fail

The above link is to an article that gives some basic reasons (according to the author) as to why the semantic web will fail. In summary, his argument is that the semantic web will fail not because of any technology shortcomings, but because businesses will not want to cooperate for reasons of profit, proprietary domain, competition, etc.

This is ridiculous. The first (our current) version of the web works because there is a reasonable stable standard way for people to exhibit information, and for people to retrieve that information. The semantic web is the same thing, only for systems to do the exhibition and retrieval. The first time any company has a number of services that can be accessed by consumers in a system-to-system manner and this shows even an inkling of profit, the corporate world will beat a path to the doorstep of some self-synchronized standard.

This has happened in history - think of the adoption of comon means of trade, the adoption of common formats of record keeping, using standardized banking transfer methods, the adoption of the fax machine, the adoption of supercalc, the adoption of microsoft office as a defacto standard. The adoption of the pdf. In all of these cases, collaboration proved to be more profitable and more valuable than choosing a (perhaps better) different path to the same goal.

Once people saw that there was benefit to producing information in a semi-standardized format (html?), then everyone felt the need to produce their information in such a format. Sure it was bumpy and crunchy fighting through the evolution of the "standard" (and the evolution continues) and there were corporate sticks-in-the-mud that purposefully deviated in order to capture some market advantage, but in the end it is all still pretty much standardized.

Almost any browser can read almost any webpage, and if you have a business case for presenting information, then you are a Fool (notice the capital F) if you rely on a presentation method that locks out part of the audience by not adopting to the defacto standard. Sure, appealing to an elite part of the audience by using a cutting edge method for presenting content is cool and stylish, but you wouldn't want to base a business plan that needs to reach the masses on such an approach.

This same self-synchronization will occur in the system-to-system web world (the semantic web, as envisioned by Sir Tim Berners-Lee). Yeah, it will be rough, and it might take a couple of years to get to such a standard. But if we apply a little perspective here, we are talking about maybe a decade. And then think about what a difference there will be in the world when this starts to take hold. For comparison, think of the difference just a decade made between 1990 (no WWW) and 2000 (ubiquitous WWW).

Tags: semantic web

Raganathan's Facets

2006-11-22T01:38:00.000-05:00

Interesting idea - Raganathan's ideas of facets are similar to my idea of concepts. To be explored further . . .

Ranganathan

Tags: ranganathan, concept, facet

Information Architecture

2006-11-22T01:34:00.000-05:00

Interesting site, I found while looking up information concerning the formulation of a thesaurus.

Information Architecture

Ontopia Article Captures the Ontology Spectrum

2006-11-22T01:27:00.000-05:00

Leo Obrst has published (as slides from talks) a couple of times something that he calls the ontology spectrum (or, in an upcoming book, the "Logic Spectrum").

The same ideas appear in this article.

Tags: controlled vocabularies, taxonomy, thesauri, ontology, topic map

Why Johnny Can't Code

2006-09-14T13:51:00.000-05:00

Why Johnny Can't Code A Salon Article written by David Brin.

This is a great article talking about the sad reality that these days, many operating systems don't have a neat, easy built in command line programming language. Like BASIC, which was in all the OS's from the micro, mini, and home computer revolution in the 70's, 80's, and early 90's.

Great reading, and certainly gives some insight into why a generation of computer geeks (like myself) have it built into our system (crikey - I've been programming since 1977, when the father of a friend of mine taught his son and me how to program in basic on a TRS-80 Model 1). These days, kids learn it all in school. Many get into it because it will be a "good career". Well, you can certainly see the difference between someone who is self taught and has it in their soul, compared to someone who learns it as career development. The difference is between a practitioner (the latter) and a geek (the former). Geeks breathe the stuff, practitioners merely do it.

Tags: programming

Concept based ontology system described using set theory

2006-05-01T18:10:00.000-05:00

If my system (based on concepts) is right, then the universe of discourse can be described something like:

1. There exist a finite number of properties, the set of which we will refer to as P. There is, likewise, a set of property values, which we shall call Pv. Each property in P can be given quantification and qualification via 1 or more members of Pv which are mapped the member of P. Together this makes a P-PV mapped, which we shall describe as Pr{P, Pv}. When discussed in abstract, it is possible to acknowledge that a particular {P, Pv} pairing will have a range for its property values, rather than a specific value. Then when the property is applied with specificity, a value within that range reveals itself.

2. There exist a finite number of concepts, each of which have some subset of Pr that it exhibits. A concept, as described here, is an agreed to mental idea of a trait common to everything in the universe of discourse said to exhibit the concept (a somewhat circular definition, but it is being worked on). The set of all concepts, we shall call C. The idea of a propertied concept, that is the concept considered with all of it's exhibitted properties, exists, and the set of all of these propertied concepts we will call Cp. The properties in question come from Pr (and may, therefor, have the Pv expressed as a range, when discussed in the abstract, or an actual value, when discussed with instance specificity). Each member of Cp contains one or more members from Pr, which we signify by writing Cp(Pr*).

3. Within the universe of discourse, there are a number of entities. Entities are "things" within the universe of discourse. By "things", it is meant to consider both mental and physical things, as well as processes and events. For each of these, there are both abstract types as well as specific instances. The complete set of entities we shall call E.

4. There is a power set of Cp, which we shall refer to as power(Cp).

5. Each entity can definited by one subset from power(Cp). It is highly likely that within the universe of discousrse that members of power(Cp) will not be applicable to any of the entities within that universe of discourse, due to the conflicting nature of the concepts involved.

6. There is a universal entity type which is the most general of all entity types, which has no defining concepts other than those required to establish the existence of an entity. We shall call this universal entity U. U will have several children entities, each of which are disjoint from each other and also disjoint from their common parent by having a different subset of power(Cp) as its defining list of concepts, properties, and property values.

7. Each entity within the universe of discourse evolves as a child entity of some more general (i.e. - closer to U in heritage) entity. Each child entity inherits all of power(Cp) that its parent, yet is disjoint from its parent, and all its siblings, by having a different subset from power(Cp) that defines this. Note by 2 above, Pr is definied as a pairing of P and Pv, and that Pv can be a range or can be a value. If the only difference between siblings, or between a child and a parent, is a different specific value for Pv, then this required disjointness is satisfied.

8. Starting with U and tracing the "heritage" (path from parent to child to grandchild, etc) will give a series of propertied concepts, all of which accumulate with each new generation in the heritage.

9. Depending on the nature of the universe of discourse, there will be other semantic links between entities that are not parents or children or siblings of each other, depending on the entities in question and their relationship to each other within the universe of discourse. These semantic links we will call relations, and the set of all possible relations we will call Re. Each Re can have any number of satisfying strings, a string consisting of two (or more) entities that are linked together by the relation. We shall write this as Re(E1, E2), where E1 and E2 are entities (types, instances, objects, events, or processes).

10. It is possible that a number of entities that have semantic links (relations) can be combined to make a statement within the universe of discourse. In order to ensure that related entities are combined in the correct manner, there should be a number of guidelines ensuring that any declarative statements made within the universe of discourse create analytic statements (statements that have a priori truth) that are internally correct and make good semantic sense. These will be called the Internal Rules, and all of the possible such rules make up a set, which we shall call RuI. Such a set of rules could be considered a grammar. Each rule will have a condition describing when it could be applied, and the condition can have a conditional value. Condition values can exist as a specific value, or can exist as an allowed for range (i.e. - the Condition Value CoV(x) for Condition C(X) must be within the range of y to z in order for the RuI(a) to be true). Each member of RuI will then have a number of strings containing a relation, and a condition-condition_value pairing. We shall call conditions Co, and condition values CoV. The RuI string will be written RuI(Re,(Co,CoV)).

11. It is possible to make statements within the universe of discourse that have a number of contextual affects on when it is proper to make such a statement. There are a set of rules describing such statements, and these are referred to as the external rules. The set of all such external rules we will refer to as RuE. Rather than being analytic statements, which have a priori truth, these are synthetic statements, which are only true within a certain context. It is therefore important to capture the context state, and any values that the context state may have in order to describe when these rules may be applied. Note that as with conditions above, contexts values may exist as specific values, or defined as a satisfying range. A context will be writen as Ct, and a context value will be written as CtV. Therefore the total set of external rules will contain, for each RuE, a number of strings with the value RuE(Re,(Ct,CtV)).

Tags: ontology

Decidability of Class-Based Knowledge Representation Formalisms

2006-03-10T11:42:00.000-05:00

Dissertation (from 1995) on the Decidability of a knowledge representation system

Tags: ontology, knowledge representation

Universal Hierarchy of Abstraction

2006-03-10T00:40:00.000-05:00

Universal Hierarchy of Abstraction

Very interesting article formed around Feynman's hierarchy of ideas.

Tags: ontology, epistemology, abstraction,

Analytic and Synthetic rule sets

2006-03-09T20:09:00.000-05:00

Analytic statements vs. Synthetic statements

Kant's idea of analytic statements (which have self contained truth) and synthetic statements (which have truther which is established by the status of certain terms within the world) has been extended by Quine to include pragmatic situational statements.

I believe this to be similar to my distinction between "internal" and "external" rules within my component-based model for a formal ontology. The internal rules are analytic, or rather, they can have their truth determined completely by elements found within the formal ontology model. The external rules, on the other hand, are synthetic, in that they are based upon some external conditions or paradigm to have their truth established.

Tags: ontology, Kant, Quine, truth

Atomisation of Concepts - a Jerry Fodor Idea

2005-09-25T20:55:00.000-05:00

Concepts by Jerry Fodor is looking like a very good book. He takes the perspective of presenting concepts, within a cognitive system, as being basically atomic and simple ideas - rather than the general computational psychology model of proposing that semantic ideas only have meaning on their own - as compounds of concepts, rather than allowing for meaningful simple atomic concepts. I like having my work turn having been thought of earlier by experts, it gives me an idea that I'm on the right track.

Tags: concepts, cognitive science, ontology

Ontology paper presented at 2005 Fall Simulation Interoperability Workshop

2005-09-24T22:53:00.000-05:00

SISO sponsors several Simulation Interoperability Workshops each year. Many of the papers that I have been author (either first or subsequent author) on have been presented at these workshops, as they deal with the bigger picture of interoperability, but the current domain that I am working in is Simulation Interoperability.

In September 05, I presented (to two different tracks) the paper "Ontology of the C2IEDM - Further Studies to Enable Semantic Interoperability". This paper is the second in a series, where I have devised a systemic definition for what comprises an ontology (see the Components of an Ontology articles in this blog for more details), and then I have presented a cartesian method for evaluating a formal ontology in light of that definition.

The first paper(Evanulation of the C2IEDM as an Interoperability-Enabling Ontology) was presented in Toulouse France, in June of 2005. It was concerned mainly with presenting the definition, and also presenting the C2IEDM - a very full data model, which has both an implicit ontology (presented in its scope and coverage), and an explicit ontology (presented in its usage rules and documentation). The second paper (still to be made available on the web - email me for a copy) further extends the definition and goes into detail on the method - giving the results for its application to the ontology of the C2IEDM.

I hope to do a third paper for the 2006 Spring SIW that will present to the Simulation Interoperability community some early ideas about usage and application of a formal ontology, and how it can be applied to both static and dynamic tools.

Tags: ontology, simulation, c2iedm, interoperability

IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantic Heterogeneous Data and Knowledge Sources

2005-09-24T22:31:00.000-05:00

IEEE Workshop on Knoledge Acquisition from Distributed, Autonomous, Semantic Heterogeneous Data and Knowledge Sources

Nice looking conference on KA - some ontology work, some KR work, etc.

It moved from New Orleans to Houston, now that RITA has wrought damage to east Texas, I hope that Houston will be ready. Prayers and Godspeed to those affected.

Meta-Object Facility and Common Warehouse Metamodel

2005-09-23T23:58:00.000-05:00

CWM, MOF, etc

OMG's Common Warehouse Metamodel is certainly a very good example of how data should be tagged and marked for ontological placement within a domain - and the related Meta-Object Facility (MOF) is a good enabling method.

I wonder if anyone has ever compared this to the Hierarchical Data Format, and it's metadata model?

Tags: ontology, mof, semantic web, tagging, xmi, hdf

alphaWorks : Emerging Topic : Semantics

2005-09-23T23:30:00.000-05:00

IBM has a nice alphaWorks topic on Semantics - they refer to the whole ontology/metadata issue as part of "Unstructured Information Management Architecture" - very nice

alphaWorks:Semantics

Another one from Ontopia

2005-08-19T23:08:00.000-05:00

Living with Topic Maps and RDF

Okay, okay, another good article from Ontopia. This one explores the relationship between topic maps and the RDF family of technologies (RDF, OWL, DAML-OIL, OWL-S, etc)

Tags: topic maps, RDF, OWL

Topic Map Article from Ontopia

2005-08-19T23:03:00.000-05:00

Metadata? Thesauri? Taxonomies? Topic Maps!

Yeah, it's by a company. Yeah, it's on their own website. But it IS a good paper describing how topic maps (descriptors of a domain's ontology for the purpose of supporting information retrieval) can be used, and how they relate to metadata and taxonomies. Good Stuff. Besides, they seem like such a nice company.

Tags: topic maps, taxonomies, XTM

Dublin Core Metadata Generator

2005-08-16T13:28:00.000-05:00

DC Dot

This is a Dublin Core compliant metadata generator, that is presented by UKOLN.

Basically, you give it a document or webpage, and it generates a set of metadata (in a variety of formats), such as XML, HTML, XHTML, RDF, etc. The metadata generated is compliant with the Dublin Core

Tags: metadata

W3C RDF validator

2005-08-16T11:21:00.000-05:00

W3C RDF Validator

This is an excellent tool. You give it an RDF file, or a URI to an RDF document, and it spits out a table describing all the derived tools, as well as a very handsome graphic showing all the relationships between the subject(s), predicate(s) and object(s). Cool.

Tags: RDF

Friend of a Friend

2005-08-16T11:19:00.000-05:00

FOAF-a-matic

FOAF is Friend of a Friend - what many consider to be the most successful semantic web application yet developed. It is very nice, in that it generates an RDF file describing you, and your attributes. Check it out...

Tags: FOAF

DOAP

2005-08-16T11:17:00.000-05:00

DOAP

DOAP is Description of a Project - a very nice semantic descriptor tool - very similar to RDF.

Tags: DOAP, semantic web

Lee Lacy Book on OWL

2005-08-16T10:27:00.000-05:00

OWL: Representing Information using the Web Ontology Language

Very nice looking book on OWL.

Tags: OWL, ontology

Data Reference Model workshop

2005-08-16T10:13:00.000-05:00

Data Reference Model Workshop

I'm writing this from the Colloborative Work Environment's Data Reference Model workshop. The DRM is the goal product of a government sponsored group. Its goal is to have a data reference model that can be referenced for the purposes of data interoperability, and bringing structure and form to data within Communities of Interest, and when data is passed between COI's.

Very interesting.

Tags: Semantic Web, RDF, OWL, XML, ontology, taxonomy

I'm Back

2005-08-03T21:25:00.000-05:00

A week on Vacation, a week at a Conference, and this week spent at a Study Group Workshop has left little time for keeping up my online journal.

However, I am full of fresh(!) ideas, so I should be sharing some of them soon...

Ontology editor comparison

2005-07-16T23:24:00.000-05:00

Ontology editor comparison

This is a nice chart comparing features of a large number of potential Ontology editors. Unfortunately, it is a little dated, but not too much.

It is part of an article on such things, found here.

Nice article, nice list. I just wish that someone would stand up to generate one a little more modern - comparing, for instance Protege 3.0 and 3.1, and others. Wish I had the time to do it myself.

Components of Ontology: Rules

2005-07-14T20:33:00.000-05:00

We believe that the application of relationships between entities must be based on rules for those relationships to create semantically correct communications. There are several reasons for that, but the first (and most obvious) is that without rules governing what objects to fill the slots in a sentence (or other collection of entities for communication) open to building semantically nonsensical collections of entities. As an example of this, consider the basic structure of an American English sentence, which follows the form of SVO (Subject, Verb, Object - as in "Jack carries the ball"). Even if you follow the correct syntax, you can come up with "Banana repairs mountain", which is syntactically correct, but semantically it is nonsense. There have to be rules - rules that state how whatever the verb implies that the subject is doing, then the object can match that original pairing both syntactically and sensibly. Another reason for rules is sense making out of the number of choices. This is especially true of automated systems that are attempting to make semantic sense, as they cannot hope to make sense out of the rapidly approaching infinite number of sources, even when working with a rather small and limited taxonomy.

Grammars and Ontology

Just as we have seen earlier that both taxonomies and knowledge bases are separate from a formal ontology, so too is a grammar separate from a formal ontology.
Grammar is defined as “containing the morphologic, syntactic, and semantic rules for a specific language” [American heritage dictionary reference]. The three elements of that definition can be specifically defined as this –

morphology is the study of the rules for forming admissible words

syntax is the study of rules for forming admissible sentences

semantics is the study of language meaning

The grammar of a system of communications to be used for information system is very similar to this definition. We propose that instead of forming words and sentences, we are forming data elements and meaningful packets of data elements making up more complex ideas than the individual elements are capable of (just as sentences are able to convey a lot more than the individual words). A grammar for a data system is concerned with the meaning of the data elements, the formulation of admissible (able to be transmitted, and able to be received) packets of communicating information based on those elements, and finally the meaningfulness of the packets of data to both systems (the transmitter and the receiver).

A formal ontology contains these same elements, and perhaps goes further in ensuring the specific definition of the concepts, property-exhibiting concepts, and property-values of those concepts that underlay all of the elements being addressed by the grammar. A formal ontology provides a specific attempt at satisfying the needs of the semantic portion of the grammar.

Rules from Three Sources

Within a linguistics system, these rules can come from one of three different places. They can come from the transmitter imparting the communication, or speaker. They can come from the perceiver, or listener, or they can be dictated by the system in question. With spoken language, the only discriminating source is the perceiver, as that is what finally determines the meaning of what is spoken, regardless of what the speaker had in mind. The listener can ask the speaker to restate something, and they can slowly come to understanding (perhaps the speaker can eventually ensure that the listener perceives what the speaker is saying in the manner that the speaker intended, but this is not automatically so). However, with the case of computer systems, we have an advantage. That advantage has been hinted at in the previous section, and we will go over it some more here as it has a great deal of bearing on the system of rules and evaluating them.

The Benefit of Not Understanding

The advantage that an information system has when considering the rules of a system, and the "semantic" meaning of a system-to-system communication method is this - the information system doesn't really understand what is being communicated. That may seem a bit pedantic and overstating things too much at first, but it has many implications. When a person hears a sentence, they "understand" the language. They have pre-conceived opinions about words, patterns, data. An automated system does not understand the words. At best, they have an ontological map that they can use to draw patterns and formulate ingest and process based on those patterns (and the understood implications of order and syntax). But those rules for ingest and process can be delivered (or be in place) before the communication takes place. The systems can agree to share, explicitly and without pre-conceived opinion or prejudice, exactly where in the ontology of the universe of discourse the data elements being exchanged fit, and what they mean. In short, the rules for communication and formulation of semantic ideas can come from the "system" of communication, and don't rely on either the transmitter or the perceiver alone.

This has been, so far, an introduction we felt necessary for the need of rules, and how they can benefit communications. Now we must consider where they reside. Even though we have suggested that the rules are part of the "system", that still leaves a big question. Are they a part of the formal ontology, or should they be up to the collection of systems relying on the ontology for communications? We believe that the answer is both, and this is an explanation of how we see that.

When considering rules, we believe that there is the possibility for two different types:

Rules that apply to the possible

Rules that apply to the actual

The former is necessarily a superset of the latter, and should be all encompassing and non-limiting. As the formal ontology will have uses and users that the original architects of it cannot conceive of at the time of inception, all of the possible eventualities that can exist between entities should be catered to.

As systems begin to use the formal ontology for specific purposes, there will necessarily be the demands of context and occasion, and the requirements for more detail and explicitness in some areas, and less in other areas. These comprise what are commonly called business rules. These business rules limit the possible down to a set of the actual, but it is a limitation with a purpose. It should eliminate ambiguities and redundancy, and it should make the operation of the overall system of communications more efficient for the purpose at hand.

We see that we have rules divided into the possible and the actual. The first set, the possible, is almost driven by the total matrix of what is possible within the syntax of the system, and these rules should reside within the formal ontology. The second set, the actual, is based on the business rules and use cases of the systems employing the formal ontology, to a certain extent, but also to the existent and changing states of the entities and relationships within the systems communicating, and as the states of those items change, then the rules determining the actual will change. It is very use dependent, yes, but it is also very much state dependent. These rules can not, without there being an insurmountably large number of such rules covering all possibilities, exist within the formal ontology, but should exist either within the systems making use of the formal ontology. Partially, what is the actual can be derived from the changing state of the entities, through implications. For instance, if you have a number of rules governing the possible that state all wheeled vehicle entities are capable of road movement, then the changing state of the location of the wheeled vehicles (sometimes on a road, sometimes not) will be an implicit limitation to the application of this rules (the actual rules).

Rules must be based on Properties

As can be seen from the aspects of this description and definition, the rules that are applied are all based on the properties of the entities and relationships affected. Without properties, there can be no application of rules, and all relationships would be equally applicable to all entities (a system of universality that results in no system at all). There must be properties, the application of rules must be based on properties, and then the connecting of entities via relationships must be based on these rules.

It is enough, based on the section above, to allow that all of the actual limitations of the rules will take place from within the formal ontology based on the changing state of properties and property-values, however it MAY be that some of the limitations on the complete set of possible rules will be made from outside business rules. These are not for the formal ontology to define.

Method for Evaluation

The method for evaluation therefore falls, in this case, not to the use cases, rather to the potential for all possible rules. All possible rules are based on properties, which are exhibited via the range of concepts that apply to an entity or relationship (and the property-values applied to those concepts). The set of all possible rules should therefore be evaluated as to the ranges of concepts that exist to limit said rules. Are the ranges sufficiently limited to allow for the precise application of rules where necessary? And are the ranges sufficiently broad to allow for a finite and understandable set of rules to be in place? If the ranges are not sufficiently broad, then too many small rules are in place, and no system can hope to have sufficient understanding and functional cataloging of all of them.

While use cases are too specific to form the basis of an evaluation concerning the inherent rules of a formal ontology, it is true that the universe of discourse that the ontology is intended to support must be considered. If the types of communications require (generally) a great deal of precision, then the ranges of concepts can be appropriately smaller. On the other hand, if the universe of discourse is itself quite large, and the number of entities to be considered is correspondently very large, then the rules should be broader, and the evaluation of rules should consider broad ranges of concepts in a favorable light.

Tags: ontology

Components of Ontology: Relationships

2005-07-14T20:29:00.000-05:00

Relationships within a formal ontology are the means that allow entities to modify and combine with each other. It is important to realize that the relationship itself does not affect an entity, but that the entities that it relates provide the affects or changes. For instance, relating the entities "truck" and "movement" (truck HAS movement) give the idea of a truck moving somewhere. The relationship HAS does nothing for the truck, but it does allow for the semantic idea of the truck having movement (or "moving", using the correct syntactic form).

Concepts of Relationships

Relationships are comprised of concepts, just as the other compounds (entities and non-atomic concepts) are. These concepts are a little more abstract and difficult to see than they are in the other compounds, but they are present nevertheless. The reason they are difficult to see, is because we are not accustomed to thinking of them consciously. When we communicate, the rules of our language and semantics are definitely bounded by the concepts that comprise relationships. For an example, let us consider the binary relationship "tank has crew". There are two entities, tank (the subject of the relationship) and crew (the object of the relationship), brought together by the relationship HAS. These two entities each have a number of concepts, some of which should be apparent.

Consider the relationship "has". In this case, it is being used to define that an entity has as part of itself a number of other entities. To put it simply, think of it in terms of the taxonomical hypernym classes that exist outside of both "tank" and "crew". Those hypernyms are "vehicle" (in the case of "tank"), and "component" (in the case of "crew"). This then becomes "vehicle has component", for a tank is a vehicle, and crew is a component of a vehicle.

At this point, "has" now has a few interesting concepts. First, it has a time subjectivity concept, by which I mean this - if we say a tank has crew, we mean two things.

A tank has the CAPACITY to contain 4 crew members (and needs 4 to function fully).

A tank has the POTENTIALITY of carrying 0,1,2,3 or 4 crew members subject to it's current state (is it in storage, is it in the field, has it been damaged, etc).

Second, the relationship "has" can imply the concept of specificity, semi-specificity (or class specificity), or non-specificity. By this I men that the tank can have either

INSTANCE-SPECIFIC crew (Carol, Bob, Ted, and Alice

CLASS-SPECIFIC crew (gunner, loader, driver, commander

NON-SPECIFIC crew (4 bodies)

These are all concepts of the relationship, which allow it to be redefined, or to have its properties defined.

When looked at that way, the relationship "has" can be divided up into two more precisely defined relationships of "has capacity of" and "has currently".

Aspects of Relationships

Just as entities can have both a real/non-real aspect as well as a tangible/abstract aspect, so relationships have a number of different aspects, some of which were hinted out in the previous example.

One of the aspects of a relationship is the choice between a relationship showing an actuality or a potentiality. This is often a defining factor as to whether the relationship applies to persistent properties (or property values) of an entity (which are often associated with the class of an entity), or if they relationship applies to the non-persistent properties of an entity (which are often associated with the instance of an entity). A class-entity has the entities affecting its potentiality related to it (which indicates a persistent property), and an instance-entity has the entities affecting its actuality related to it (again, this indicates a non-persistent property).

The nature of relationships (and their application to entities) is sometimes based on the changing state of the entity. This gives a temporal basis to the relationship. As with so many other aspects affecting the other components of our formal ontology, this temporal basis is grounded in the use of the ontological definition. Temporal basis, as it is based on the changing state of entities through time, is very much related to events and phenomena (as events have a time component, and phenomena are concerned with changing state).

Finally, some relationships can be redefined based on qualification, as opposed to quantification. It is fine to say that "tank HAS crew", which is a qualification relationship (giving some definition to the tank entity, by relating it to a defining entity), but it is a quantification relationship to list the number of crew that the tank has (whether potential or actual). Quantification and qualification relationships are often used to define the state (current or otherwise) of the subject entity.

The inherent supporting needs for a relationship to exist between two entities are often very easy to accommodate. For instance, if a relationship exhibiting quantification is to exist, then the only structural (syntax) requirement is that both the object entity and subject entity of the relationship must each support the idea of a number of something being related to something else. Thus, syntactically, it is perfectly fine to say that "tank HAS 2 wings". This is syntactically correct, however it is not semantically correct (unless we are working within a universe of discourse that allows for winged tanks). The semantics of relationships are dealt with in the next system (rules).

Method for Evaluating Relationships

Our method for evaluating relationships should be simple, and easy to define, however it (as with the other methods discussed above) must be based in the intended use of the ontological definition.

The types of relationships (potential/actual, qualification/quantification, temporally based) that exist must each be considered to see whether all of the combinations of entities that are required to satisfy the universe of discourse can be assembled.

The syntactic requirements for the relationships are based on the properties (or concepts) of the entities being related must exist, for all the sorts of relationships that need to be supported for the universe of discourse.

Finally, the relationships must be accessible enough via definition that they can be the objects of relationship-controlling rules.

Tags: ontology

Ontological Components: Entities

2005-07-14T20:14:00.000-05:00

The ontology of an information system (whether for computer science, cognitive science, information management or other areas) differs somewhat from the Ontology referred to by philosophy. In philosophy, Ontology is the theory of being [reference], it is the theoretical description about all that is, and how it relates to each other, within a universe of discourse. There is a subtle difference existing within the study of ontology for purposes of enabling an information system - a difference that is helpful to keep in mind when considering entities. That difference is this - in an information system, ontology is the study of the REPRESENTATION of all that exists within the universe of discourse.

Taxonomies, Knowledge Bases, and Ontology

An interesting side topic that is of value to consider when discussing entities and the method for evaluating them is this: an ontology is not a taxonomy, nor is it a knowledge base, but it can include both of those things.

A taxonomical structure is a hierarchical classification of all the data or linguistic objects (words, datum, elements, etc.) to be found within a universe of discourse [reference]. A knowledge base is a taxonomy (which is just a hierarchy of classes) that has been populated with enumerations matching the various classes [reference]. A formal ontology includes the former, among other things, but where the elements of a taxonomy differ when they are included in a formal ontology is this - an ontological view of a taxonomy also includes a definition of all the underlying assumptions and properties that define each of the classes in the taxonomy. A formal ontology need not contain the enumerations that exist within a knowledge base (and it seems difficult to imagine such an enumeration being complete in any but the most simple of universes of discourse). As I mentioned this is a side topic, but it is interesting to know what we conceive of when we mention the terms taxonomy and knowledge base.

The entities of a formal ontology include the classified and defined representations of objects, events, and phenomena. Each of these are classified in a hierarchy similar to a taxonomy. They are defined by their component concepts, for all entities are compounds (as defined in the previous section). Some of the characteristic properties of entities derive from their place on the taxonomical hierarchy, and these should be captured as concepts of the entity.

Entity Class and Entity Instance

We see therefore that entities within a formal ontology are classes, in the taxonomical sense, but with a formal definition of how those classes are defined (the exhibition of concepts related to the entity). This (the class) is one of two possible views of entities within a formal ontology. The second possible view of an entity is the potential for enumerations within that class.

It is possible for an enumerated entity to begin to have a separate identity from that of its parent class. This is through the introduction of non-persistent properties. Each enumerated entity shares the same persistent properties, and these are defined by the taxonomical class, as well as all the ontological concepts that define that class. All enumerations deriving from that class inherit those concepts. These are the persistent properties of those enumerations. However, the nature of an entity to exist within space and time, and an entity's nature to change state as it is related to other entities (particularly phenomena), determine that it will have some properties that are non-persistent, and these change not only from enumeration to enumeration, but also over time.

As an example, let us consider the entity "GP40 Diesel Electric Locomotive". This entity is a class within a formal ontology that considers (as part of it's universe of discourse) railroad assets. Some of the persistent properties of this class are these - 3000hp engine, 40 inch wheel diameter, rated weight 257,000 lbs, etc. These are the properties common to the whole class. Now, if we take a particular enumeration of this class, say "CSX engine number 6936", this enumeration takes on a number of non-persistent properties. It's current location (Louisville KY?), it's consist of freight cars, it's driver, it's current paint job, it's maintenance state, it's actual rate. All of these things are properties that can define such an entity, if the ontological need exists. The value of these properties change (or perhaps not be existent) when considering other enumerations of the entity "GP40 Diesel Electric Locomotive". Property exhibiting concepts might exist across the various enumerations, but the value of those properties might change (such as location - each existing instance of a GP40 has the concept location, but the value of that concept changes from instance to instance, and over time).

It is important to make the distinction between the enumerations of a particular taxonomical class, and separate, but related classes. This distinction becomes especially important as we consider hypernyms and hyponyms within a taxonomical hierarchy. Hypernyms and hyponyms are redefinitions of classes, into other classes, at different resolutions. This is easier to see through example, than it is to explain. For instance, the taxonomical class "vehicle" is a hypernym for the classes "chariot", "helicopter", "locomotive" and others. Those other classes are also vehicles, but the more precise class is considered at a higher resolution of detail. Likewise, the taxonomical classes "hydrocodone", "penicillin", and "ritalin" are all hyponyms for the taxonomical class "drug". The class "drug" is similar to the others, but considered at a lower resolution of detail.

In a graphical representation showing the hierarchy of the classes of a taxonomy, the hypernyms are parents and the hyponyms are children. The failings of this sort of representation are that it becomes very complicated very quickly, when you have classes that are hyponyms for multiple "parents", which is very easy within any but the most simple of taxonomies (or ontologies).

The Categories of Entity

Within a formal ontology, there is room for both aspects of an entity, the class and the instance (or, enumeration). The class comes from the roots that a formal ontology has in a taxonomy, and the presence of instances allow the formal ontology to serve as a knowledge base. Both of these are required, as both have separate property issues that need to be addressed by the ontological concept structure. The same is true for all three aspects of entity - object, event, and phenomena.

Objects are easy to comprehend, as they are the objects and things of the world (universe of discourse) for which the formal ontology is describing representations. What is important to understand about objects is that they have several aspects that might not be immediately apparent.
1. First, objects can tangible or abstract. By naming an object tangible, I mean that it can be a physical object (such as a truck, or a country). Equally valid, however, is that an object can be an abstract thing - something that has definite properties but is not physical. Some examples of abstract objects could include culture, organizations, or decisions.
2. A second aspect to consider is that when discussing either tangible or abstract objects, those objects do not necessarily need to be "real". It is perfectly valid to have a formal ontology define representation of an entity (object or otherwise) that is non-real, so long as the entity has an "essence" that can be defined through a combination of property exhibiting concepts. This idea of non-real objects can include future objects, nominal objects, or potential objects (and in all cases, they can be tangible or abstract). The specific description of the representation is what is important for a formal ontology to be sound, not necessarily that all of the objects represented be soundly based in reality.

In addition to objects, there is also the sub-category of entity, which we refer to as events. We define an event as "an entity with a time component". An event-entity is similar to an object-entity in that it can be tangible or abstract, but it has a period of time (which, as above with object-entities, need not be a real period of time, but could be future, past, nominal, or potential) during which it represents an entity with defined properties. An example of a tangible event is a rainstorm (with a start time, a stop time, and a tangible object related to it - rainfall). An example of an abstract event is a meeting (an ad hoc organization structure with a time component).

The final sub-category of entity is phenomena. Phenomena are the entities that, when related to other entities through the relationship component of a formal ontology, change the state of the entity they are related to. This is done by affecting the properties or property-values of the affected entity. Phenomena share the aspects of entities in that they can be real or non-real, they can be tangible or abstract, and they can exist over time, similar to an event. Phenomena include the elements of linguistics that we think of as verbs and modifiers. Anything that implies action or change is a phenomena-entity, and some examples are damage, movement, unloading, growth, decay and others. They are related through relationships, and have properties (as all entities do) so that rules can be formed about their applicability for these relationships.

A Method for Entity Evaluation

Our method for evaluating entities must, as with concepts, be based in the intended use of the formal ontology. From that starting basis, we can move to the various aspects required for consideration in our evaluation.

First entities must have properties (more accurately, property exhibiting concepts). The concepts defining entities, and giving them accessible properties, must be apparent and accessible. In fact, for ontological purposes, they must be defined. This is true not only of entity classes, but also of entity instances. It is equally true for not only properties but also property values. In the previous section on concepts, we defined the range of concepts of a compound to be all of the concepts that define that compound - in the case of an entity (which has two possible states of existence - as a class and as an instance), this range can exist in several different states. All of them must be explicitly addressable and apparent for the entity component to be evaluated to be adequate.

The second consideration in our evaluation is the consideration of all the possible entities (objects, events, and phenomena). Are all of the requirements of communications within the universe of discourse satisfied by the enumerated list of all possible entity classes? Are the definitions of the entity instances sufficient to accommodate the needs of the universe of discourse?

The final consideration is the depth of definition that the ranges of concepts provide in defining the entities. Are the entities defined to enough (and not too much) detail to afford the sorts of use they will be put to in the universe of discourse? If we have a universe of discourse that is discussing the movement of cargo through a supply system, then it is necessary for the entity "truck" to have the concepts of capacity, reliability, speed, ease of use, etc as property exhibiting concepts within the formal ontology. The concept of "what color is the seat inside the truck" is probably too much detail. But the lack of "how easy is the cargo bed to access" might be necessary.

Entities within a Fractal Ontology

A word about this final consideration is in order. There exists the idea of a fractal ontology (or "fractology" as a colleague has suggested recently), which implies that the level of examination that the entities and relationships within the formal ontology might change in resolution, depending on the use that it is being put to. To support this sort of idea, then the attendant concepts of entities must exist to appropriately support the highest and lowest resolution of consideration, and all levels in between that may be adopted. At that point, we have a formal ontology that has a dynamic resolution, but if the properties and concepts existing at those different levels are compounds or components of each other as the scale of consideration shifts, then the formal ontology becomes a fractal ontology.

Earlier article on Entities

Tags: ontology

Components of Ontology: Concepts

2005-07-14T20:05:00.000-05:00

Earlier, in Evaluation of the C2IEDM as an Interoperability-Enabling Ontology we defined a concept as "anything that has addressable properties". Although this is a loose definition, it fits our usage. Within our formal ontology, concepts exist for several purposes - giving definition and identity to other concepts (which may be compounded of several entailing concepts), giving definition and identity to entities, and finally giving definition and identity to relationships. As these three purposes are very similar (all involve the endowment of definition and identity), they should be considered as part of a class. We will call members of that class compounds. Compounds are defined explicitly as any of the components within our ontology that are composed of several concepts in identity. This includes all of our ontology, with the exception of atomic concepts, and of course the rules (which are not composed of concepts, but are instead applied against concepts and compounds of concepts).

We have earlier mentioned that the various characteristics of concepts are defined as "properties". This is true, but when examined further it is easily seen that these "properties" are actually other concepts. To continue, without confusing the earlier term, we will call these concepts "property exhibiting concepts", or "properties" for short.

It is important to see that although a concept that exhibits a property might be attached to a compound, it is not necessary that the property have the same “value” at all times. For instance, if the concept “location” were to be correctly attributed to an entity, that concept is always linked to that entity, although the value of that concept may change, over time. This changing aspect of a “property exhibiting concept” is called, for convenience, a property value.

The Dimensions of Concepts

For evaluating the "concepts" component of a formal ontology, it becomes helpful to think of concepts in two dimensions.

First, each concept has a horizontal applicability, which consists of all the compounds to which a particular concept can possibly belong. This, we call the domain of a concept. The domain of a concept also contains all of the possible property values that it might exhibit. Very specific concepts will have a small domain (they apply to only a small number of compounds). Broadly applicable concepts will have a very large domain. As an example of this idea, think of the concept "red coloring". There are many, many red things, red is a concept with a very large domain. On the other hand, consider the concept "comprised of antimony". There are not too many things that we can think of that are comprised of antimony, hence that concept has a small domain.

Second, each concept has a vertical applicability, where the concept and a collection of other concepts together define a compound. This we consider the range of concepts that define a compound. The range of concepts that a compound has also contains all of the possible property values that the concepts in that range might have in relation to the compound. Any compound that is even moderately complex, and is non-trivially defined, will have a large range (meaning, that it will take a large number of defining concepts to describe all of the aspects of such a compound). A compound that is either non-complex, or defined in a non-complex manner, will have a small range of concepts defining it.

A Method for Concept Evaluation

For this component (concepts) of a formal ontology to be evaluated for completeness, then both aspects have to be considered.

First, the domain of concepts must be considered. There should be a mix of both general concepts (those with a large domain) and specific concepts (those with a small domain) for an ontology to be effective. If there are too many concepts that have a very small domain, then it will be difficult to compose rules for the formation of relationships between entities (all of the rules will be based on very small concept domains, therefore be very specific in nature, and not easy to wantify or analyze). On the other hand, if there are not enough concepts with a small domain, then it might become difficult to identify very specific entities, and composing rules becomes very easy, but very difficult to apply with precision.

As an example of this, suppose that the only concepts describing the size of vehicles were this "Motorcycle sized, or smaller" and "Larger than a motorcycle". With this simple set of concepts describing the characteristic size, it becomes very difficult to determine rules about relating a “vehicle” with “the ability to cross a certain bridge”. As the number of vehicles "larger than a motorcycle" is very large, and there is a great range of weights and widths of those vehicles, it can be seen that basing "bridge crossing ability" rules on this (with any sort of precision) is not possible without further subdivision of the size concept.

Second, the ranges of concepts have to be considered. We have described the range of concepts that an entity can have in two broad terms - those concepts exhibiting internal properties, and those exhibiting external properties. These two terms can apply to all compounds, but they are of particular interest in the area of entities. The terms deserve greater explanation, and they seem easy enough to define. Internal properties are those properties that give the compound self-identity. External properties are those properties that define how the entity affects, and is affected by, other entities within the ontology (via relationships).

For an example showing the applicability of internal and external properties, consider the entity granny smith apple. A granny smith apple is an entity that has (among others) the internal properties of being the fruit of a certain tree, having height and weight within a certain range, having a certain color and taste, etc. It also has a number of external properties, such as edible source of nutrition for herbivores and omnivores. If we have the n-ary tuple -

school boy => eating => granny smith apple

We see that we have the entity school boy related to the entity eating. As granny smith apple has the external property listed above, and school boy has the internal characteristic of omnivore, and the entity eating has the property of an act describing the ingesting of edibles, then it becomes clear how all these properties work together allowing for the ontological description of school boy eating granny smith apple.

In evaluating the ranges of concepts that exist for the compounds of a formal ontology, it is important to understand to what purpose the ontological description will be put. If it is to support all possible communications within a universe of discourse, then the sorts of interactions between entities, defined by the possible relationships and rules governing their application, must be considered. At that point, each range of concepts must be evaluated to ensure that it has sufficient coverage of external properties to accommodate all of the possibly required relationships between entities. Secondly, for each level of detail resolution that a formal ontology requires its entities to be considered at, there must be sufficient internal properties for the range of concepts for the entities to be considered sufficiently at that level of detail resolution. If a formal ontology is to be able to support the consideration of entities at several (or many) different levels of resolution, then the requirements of the range of concepts for the entities supporting those levels of resolution must be present.

It is apparent, now, that the evaluation of the concepts of a formal ontology is based heavily in the use that the ontology is to serve within the universe of discourse. This is unavoidable, unless the entire domain and range of all possible concepts were to be described as part of the formal ontology. We also see the basing of evaluation within the realm of "intended use" as being a good thing - it allows an application of detail to exist where it is needed.

Earlier article on concepts

Tags: ontology

The concept of an agglutinative language

2005-07-14T19:38:00.000-05:00

I have been considering the possibility of an Agglutinative Language. Some examples from linguistics would be German, Dutch, or Esperanto.

Can the same concept, whereby entities are created as needed from existing entities, apply to data engineering? Is there a way for data entities to (with agility) combine and form new data entities? My gut feeling tells me that there is an understood (unamibiguous) set of metadata describing each data element, that there should be problem in combining several together, to form complex entities. It is what I am proposing can be done in a formal ontology from a collection of concepts brought together to form a compound (complex concept, entity, or relationship).

The idea class inheritance intrigues me here.

Further thought warranted . . .

Tags: agglutinative language, ontology, linguistics

Human-Robot Interaction Conference

2005-07-14T18:43:00.000-05:00

Human-Robot Interaction Conference

They have a track on Cognitive Science, and a track on Cognitive Modeling. Perhaps it would be of benefit to take a look.

XML Topic Maps 1.0

2005-07-13T10:21:00.000-05:00

XML Topic Maps (XTM) 1.0

Nice website with the standards and a good explanation of XML topic maps. Groovy.

Tags: xml, topic maps, taxonomy

Advances in Modal Logic - volume 4

2005-07-12T19:57:00.000-05:00

AiML: Volume 4

Very interesting, could be possibly used to form the basis of a temporal ontological description, or at least a temporal predicate logic system.

Tags: ontology, modal logic, predicate logic,

Formal Ontology = Taxonomy + Knowledge Base + Grammar + ??

2005-07-11T00:44:00.000-05:00

If you take the ideas behind a taxonomy (taxonomical classes, hypernyms, hyponyms, related ideas, hierarchy of concepts), plus the components of a knowledge base (a long list of enumerations satisfying the various classes of the taxonomy), plus a grammar (rules defining morphology, syntax, and semantics) you have a good start as to what an ontology is. But what is missing?

My current working definition for the missing part is this: The explicit and rigorous definition of the elements of the taxonomy, the knowledge base, and the grammar, as well as rules defining the relationships among the various components.

Tags: ontology, taxonomy, knowledge base, grammar

Handbook of Semantic Restructuring

2005-07-10T19:39:00.000-05:00

Handbook of Semantic Restructuring

Definitely calls for some further study. Just when I though I got a handle on generative grammars, generative semantics, and gemerative conceptualizations . . . what's next, talking dogs?

CETIS-The semantic web: How RDF will change learning technology standards

2005-07-09T10:25:00.000-05:00

CETIS-The semantic web: How RDF will change learning technology standards

Nice tie-together article concerning RDF and the SW

Tags: RDF, semantic web, eductional technology

Dave Beckett's Resource Description Framework Resource Guide

2005-07-08T01:17:00.000-05:00

Dave Beckett's Resource Description Framework (RDF) Resource Guide

Very nice - loads of links (take a look) and documents, papers, discussion boards, etc etc etc

Tags: semantic web, rdf

MindRaider - Semantic Web Outliner

2005-07-08T01:16:00.000-05:00

MindRaider - Semantic Web Outliner

Darn - the more I look at it, the more I like it. Maybe I should just learn to live with the $0 price tag....

Tags: semantic web

The semantic web

2005-07-08T01:14:00.000-05:00

The semantic web

Interest (if slightly dated) article from UK newspaper, the Guardian. Has some very nice things to say about the Semantic Web, and also some other future looking projects.

semantic web

Practical RDF

2005-07-08T01:11:00.000-05:00

Practical RDF

Shelley Powers' website about RDF. She wrote the book on practical RDF, and has a nice blog discussing a number of different related issues.

I like RDF, but I think that I like the additions to OWL as well.

I'm just not checked in yet on my decision as to which flavor of OWL. I mean, I really enjoy the idea of having executable ontological information (as in OWL-Lite, or even OWL-DL), but I also like the idea of having a full blown ontological description done of a system using OWL-Full.

Tags: rdf, OWL

Metadata Interoperability

2005-07-08T01:05:00.000-05:00

Metadata Interoperability

Nice to see the Library community is potentially having an effect, with it's own struggles in the area of metadata, on the semantic web.

Tags: interoperability, metadata

What is an ontology and why we need it

2005-07-05T21:46:00.000-05:00

What is an ontology and why we need it

Nice paper by Noy and McGuinness - it is on the Stanford protege site, so of course presents the different components of ontology in terms of the protege structures.

Still, good stuff, and helpful to me for delimiting concepts, entities, and taxonomies/knowledge bases/ontologies.

Tags: ontology, protege

The Semantic Conception of Truth

2005-07-05T21:32:00.000-05:00

The Semantic Conception of Truth

This paper from Alfred Tarski (Berkely, 1944) is very interesting in defining semantic concepts, linguistic structure, metalanguage, object language, and a lot of other cool ideas. Good bedtime reading for linguistic geeks. Like me.

Tags: linguistics, semantics

Semantics of Prostitution

2005-07-04T14:58:00.000-05:00

Prostitution

This is a very interesting semantic map of the different concepts that relate to the idea of prostitution.

I like this chart, because it shows how different concepts, and properties of concepts, can be applied to the various entities. And then, the rules based on categorization of those properties drive the relationships. Groovy.

PECULIARITIES OF VAN CYBERSPACE - SEMANTIC WEB

2005-07-04T14:54:00.000-05:00

PECULIARITIES OF VAN CYBERSPACE - SEMANTIC WEB

Interesting take on what the Semantic Web is, and where it is going.

Extending UML for Ontology Development

2005-07-04T00:24:00.000-05:00

Extending UML for Ontology Development

Very interesting paper, gives a number of what appear to be very good examples as to how to extend the various diagramming schemes of UML to support the definition of a formal ontology.

Tags: UML, ontology

Workshop Proceedings - Core Ontologies in Ontology Engineering

2005-07-03T01:01:00.000-05:00

Core Ontologies in Ontology Engineering 2004

A nice collection of papers and presentations from the 2004 Workshop on Core Ontologies in Ontology Engineering.

Mostly presents a selection of sample domain ontologies, and some of the rules for generating and exploiting those ontologies.

Components of Ontology: Entities

2005-07-03T00:46:00.000-05:00

Entities, as defined in 05E-SIW-045, are divided up into several possible classes - objects, actions, events (objects with a time component), and phenomena.

[I think that the interesting thing here is phenomena. After all, entities relate to each other through relations, yet phenomena are the objects of relations (or perhaps the subjects) that denote and decry change of state. Whether it is an action, an emotion, an environmental change, or an affectation on the nature of some other entity - phenomena are almost always defined within the the context of the effects they bring about on other entities. This intrigues me, from the point of view of phenomena being part of a system. Are they, in essence, each special case relations that relate an entity to the new state that the phenomena describes? Not sure. I'm not even sure if I have stated that correctly, but it still interests me.]

Again, from the description in the Toulouse paper, entities are comprised of concepts. I find it interesting how, if looked at in an object oriented fashion, that the structure of Entities constructed of Concepts allows for some Concepts to be part of many different Entities. What is more interesting (and making for some challenges) is that some entities, if defined within two seperate system, but that are modeling the same real life concept, might be composed of not only a divergent list of concepts, but possibly a completely seperate list of concepts. Ouch. That certainly makes the goal of semantic interoperability much harder to accomplish. It also makes the role of a central referential data model that allows for translation between seperate ontologies - much more difficult.

Tags: ontology, epistemology, phenomenology

Vocabulary and Ontology Workshop

2005-07-03T00:31:00.000-05:00

First EDOC Workshop on Vocabularies, Ontologies, and Rules for the Enterprise

Looks good - wish I could travel to the Netherlands in September. Sadly, I'll be in Orlando at SIW (most likely)

Semantic Web Science Association

2005-07-03T00:04:00.000-05:00

International Semantic Web Science Association

This organization looks very interesting. I have found copies of their journal (at least the first two years) online.

They have an annual symposium - this years is in Galway, Ireland. I wish I could find the $$ to attend. I am thinking seriously about submitting a paper for next year (2006) as it will be in Georgia.

Tags: semantic web

Agent communication

2005-07-02T23:46:00.000-05:00

Jacques Ferber has this to say when defining an agent . . .

An agent is a physical or virtual entity. . .

which is capable of acting in an environment.
which can communicate directly with other agents.
which is driven by a set of tendencies (in the form of individual objectives or of a satisfaction/survival function which it tries to optimize).
which possesses resources of its own.
which is capable of perceiving its environment (but to a limited extent).
which has only a partial representation of its environment (and perhaps none at all).
which possesses skills and can offer services.
which may be able to reproduce itself.
whose behaviour tends towards satisfying its objectives, taking account of the resources and skills available to it and depending on its perception, its representation and the communications it receives.

The part that gets me interested, of course, is item number 2 - the ability to communicate with other agents. Does this infer only agents that communicate using the same system? Or should there be, in an environment supporting the agile combination of agents from a variety of sources, the means for semantic communication between agents using a general system?

I'm betting that somewhere down the road, someone will be interested in the latter. I sure hope so.

Tags: agents, semantics, interoperability

What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model?

2005-07-02T21:33:00.000-05:00

What are the differences between a vocabulary, a taxonomy, a thesaurus, an ontology, and a meta-model?

From the website www.metamodel.com, this is a nice concise little article on defining and giving the borders between these five important concepts.

There is a nice comment (from Michael Uschold of Boeing) that summarizes the commonalities, as well as the differences. Good commenting. But then again, Mr. Uschold has quite a nice name going for himself in the Semantics and Semantic web community. See this paper for a good example.

Tags: semantic, taxonomy, metamodel, thesaurus, ontology

Singularity Institute for Artificial Intelligence

2005-07-02T09:48:00.000-05:00

Singularity Institute for Artificial Intelligence

AI is certainly a driver for the ability to semantically mark and understand data, and also for conceptual interoperability (is it probable that an artificial intelligence system will be one monolithic system? or is it more likely to be a system of systems?).

The singularity folks propose that a singularity event will occur in the next few decades - a time when mankind is capable of artificially creating intelligence greater than his own (through augmentation, or original creation). I'm not quite sure what I think of this yet, more thoughts to follow . . .

Tags: artificial intelligence

Metadata? Thesauri? Taxonomies? Topic Maps!

2005-07-02T09:40:00.000-05:00

Metadata? Thesauri? Taxonomies? Topic Maps!

This is a great introduction to the concept of topic maps, and how they fit in with other sorts of digital marking for the purpose of capturing an ontological description of information.

As I see it from my readin, I understand a topic map to be similar to a formal ontological description, with a few main exceptions:

Topic Maps (TM) are largely visually oriented in presentation
TM are more concerned with just the taxonomy
Formal Ontologies (FO) are more concerned (than TM) with capturing information about properties of concepts, and rules governing relationships
TM seem to be much less rigorous than FO

Tags: ontology, topic maps

Semantic Tagging, an extension to a Group's Thesaurus

2005-07-02T00:04:00.000-05:00

Semantic Tagging, an extension to a Group's Thesaurus

Interesting look as to how Haiko Hebig is playing with the idea of "facets" on tags.

A facet is linked to the term in the tag, to give context or a sense of perspective to the tag.

For instance, take the tag-word "fish". As it is interpreted by different perspectives, it can mean different things (and necessarily has different semantic lineage). If you mean "fish" as an animal, that is one view. If you mean "fish" as a food, then that is another. If you mean "fish" as a verb, then that is something totally different.

Tags: ontology, tagging, semantic

Cosmik Debris » Ontology

2005-06-30T23:57:00.000-05:00

Cosmik Debris » Ontology

Nice to see the philosophy guys out talking about Ontology, too.

Forthcoming: prime tags or iffy overlapping tags

2005-06-30T23:47:00.000-05:00

Forthcoming: prime tags or iffy overlapping tags

I like this idea. I posted a comment, and I think its important to remember, that it is important to realize that an item within a data (or linguistic) taxonomy can have several different sets of parents, and hence have several different sets of children.

For instance, the entity "dandelion", within a taxonomy, could have the parents "weed", "wine", "scent", "salad", etc.

It is important that when we come up with interesting tagging methods, especially for the automated searching and consumption of data by systems (interoperability), that we refer to the tag lineage of information, not just it's particular tag.

on Ontology, Tagging, Seach, & Commerce

2005-06-30T23:10:00.000-05:00

The Hitchhiker’s Guide to 650 :: on Ontology, Tagging, Seach, & Commerce :: July :: 2005

Interesting arugument about the strengths and weaknesses of unstructured data vs. structured data.

I could be wrong, but I see things like google as having structured data, but the structure is dynamic - i.e. a dynamic and agile taxonomy exists, and is modified every time a googlebot comes back with more information about the data elements found on a page (i.e. - words on the page, and the words of pages that link to that page).

Off Topic - Alternative Energy

2005-06-30T21:04:00.000-05:00

Hydrogen
Is it just me, or does it become increasingly more and more apparent with each day that we need to be pushing on forward in the pursuit of alternative energy exploitation.

Wind, solar, nuclear - all good. Hydrogen - if realized, could be perhaps perfect.

We need to think about exceeding the arms race, the space race, and the information race of the past 20,40,60 years and concentrate a similar set of national treasure and resources on development and adoption of such energy.

This will help so many aspects of our world, I can't wait for the day when it's here. I just hope that it comes within my lifetime.

Tags: energy, hydrogen, conservation

exegesis on formal ontology - or where I learn to sleep quietly at night again

2005-06-30T20:35:00.000-05:00

Formal Ontologies are necessary.

I've said it, and I'm glad I said it!

The past several weeks, ever since becoming acquainted with Clay Shirky's diatribe against ontologies and digital marking (tagging) techniques (which are, at least according to Tim Berners-Lee, required for the semantic web), I have felt a deep blight covering part of my weltanschauung. I believe that within the area of data interoperability, and system composability, there is definitely a need for a formal specification of conceptualization (ontology). Where I believe that I and Mr. Shirky (whom I usually agree with, and enjoy reading) must part ways is this. When a group of individual people are attempting to all communicate, from different backgrounds, understandings and capabilities then ontology is not possible to concieve of on the part of the "speaker" (or in the case of posted information, the "producer"). This is because what is said is percieved of by someone with a different understnading. Because of this, when people talk, they are constantly refining, and re-refining their shared ontology. This is done through not only restatement of ideas in different terms, but also in inference and context. These things the human mind is capable of, where computers (not currently, if ever) are not.

This is where the idea of a "folkonomy" comes from. A folkonomy is a populist taxonomy derived from the bottom up, where people constantly contribute (the refining and re-refining), in the sense of a wiki. Perhaps with this, there will be a taxonomy (if not an ontolgy) that there can be general consensus on.

However, in the world of system interoperability, the situation is much different. Even though two computer systems have an ontology defining their data being interchanged, the two systems do not "understand" the data being exchanged. What they are capable of doing is understanding where in the ontology (which is a formalized structure defining the classes and instances of data being exchanged, and the allowable relationships between that data) the data resides. That is the level of "understanding" that a formal ontology brings to system interoperability. Does the ontology have to be semantically perfect? It has to be perfect enough to accomodate all the ways in which the participating systems can make use of the data (hence, all the possible properties and concepts making up the entities and relations being described). Does it have to be complete? That depends on what you mean by complete. It has to be complete enough to accomodate all of the aspects of data being interchanged, but it does not necessarily have to be a complete view of the whole universe of discourse (as would be required if the ontology were for a free communication mode, such as speech).

Note that this does get more and more complex when we speak of an ontology that will accomodate agile system to system connectivity and interoperability - such as when we have a large number of systems, which may or may not be known of when the ontology is derived. Any of these systems can be arranged to interoperate with each other on demand, and have to do so through the worldview afforded by the ontology - then it must be more "perfect", and more "complete" (as I've defined them above).

This where sufficiency comes into play.

So, Mr. Shirky, wherever you are tonight, I am now at peace with your writing. I believe that there is a home for metadata, tagging, and formal ontologies. But perhaps (and this coincides with my philosophical leanings) it is not achievable for general communications using the paradigms that we currently employ and are aware of. However, for the purposes of system interoperability, I believe that a "perfect" enough, and "complete" enough ontology is achievable with the defining and tagging technologies of today.

My weltanschauung is now complete again.

Tags: ontology

Components of Ontology: More thoughts on Concepts

2005-06-30T19:56:00.000-05:00

The different aspects of concepts (or perhaps, contributing concepts that combine to form higher order concepts) are known as the "properties" of the concepts.

Properties are very important, in that they are the aspect of the concept that allow different concepts to be grouped together. This ability to group together concepts is CRUCIAL for the formulation of rules (which provides for inference, and also the framework for relationships to exist within).

The existence of properties within concepts is also a key feature for the associated concepts, which are entities and relationships. Both of them are comprised of one or more concept, and those concepts have properties that allow them to be grouped together, and hence operated on by rules. Likewise, if our domain allows it (and the battlespace, which I am concerned with does), there can be categorical or "group" entities that are supersets of lower entities. Depending on the domain and it's own rules (and the nature of the relationships between entities and entity-sets) the properties of the entities might be inherited by the entity-sets.

An example seems like it will make this much clearer. For instance, in the battlespace domain, there is the entity of a Tank. This is (of course) an armoured vehicle that moves over land, has some defensive capability, a collection of engineering parameters, some offensive capability, and perhaps the capacity for crew members, supplies, and maybe the ability to tow or carry something. It is a fighting vehicle. In the ontology of the battlespace, it is an entity that falls somewhere under the entity "vehicle". Now there are also the entities within the battlespace of "armoured units", which are comprised of (among other things) "tanks". Some of the capabilities of tanks (derived from the concepts of the "tank") are going to be inherited by the entity "armoured unit". For instance, the maximum range with which an "armoured unit" can engage an enemy is based on the maximum range of the "tanks" that the "armoured unit" is a set of.

Likewise, not only entities but also relationships have concepts. These are a little more abstract than the concepts of entities, but only because we are not accustomed to thinking of them consciously. When we communicate, the rules of our language and semantics are definitely bounded by the concepts that comprise relationships. For an example, let us consider the binary relationship "tank has crew". There are two entities, tank (a subject entity) and crew (an object entity). These each have a number of concepts, some of which should be apparent.

But also consider the relationship "has". In this case, it is being used to define that an entity has as part of itself a number of other entities. To put it simply, think of it in terms of the set-entities that comprise both "tank" and "crew". This then becomes "vehicle has component", for a tank is a vehicle, and crew is a component of a vehicle.

At this point, "has" now has a few interesting concepts. First, it has a time subjectivity concept, by which I mean this - if we say a tank has crew, we mean two things. (1) A tank has the CAPACITY to contain 4 crew members (and needs 4 to function fully). (2) A tank has the POTENTIALITY of carrying 0,1,2,3 or 4 crew members subject to it's current state (is it in storage, is it in the field, has it been damaged, etc etc etc).

Second, the relationship "has" can imply the concept of specificity, semi-specificity (or class specificity), or non-specificity. By this I men that the tank can either (1) have SPECIFIC crew (Carol, Bob, Ted, and Alice), (2) have CLASS-SPECIFIC crew (gunner, loader, driver, commander), or (3) have NON_SPECIFIC crew (4 bodies). These are all concepts of the relationship, which allow it to be redefined, or to have its properties defined.

When looked at that way, the relationship "has" can be divided up into two more specific relationships of "has capacity of" and "has currently". Another aspect of the idea of "fractal ontology", where ideas can be re-represented at higher or lower orders of resolution. It can, of cource, be further divided up based on the specificity property.

Earlier concepts posting

Tags: ontology

Taxonomies and Tags

2005-06-29T00:39:00.000-05:00

Taxonomies and Tags

Good article from David Weinberger. It was written as a into article for Esther Dyson's online blogazine

I like what David has to say about taxonomies, especially his comparison with real world understanding viz what can be done with data (metadata, tags, etc). Plus he quotes that annoying git, Foucault, in a good way.

Nova Spivack: The Future of the Web

2005-06-29T00:22:00.000-05:00

Preoccupations: Nova Spivack: The Future of the Web

This is an article from the blog Preoccupations, which details some of Nova Spivack's writings concerning the future of the web. Of great interest is the graph that Nova has created, showing the convergence of the current web, social software, the semantic web concepts, all into a new "metaweb".

Tracing the Evolution of Social Software

2005-06-29T00:04:00.000-05:00

Tracing the Evolution of Social Software

From the blog "Life with Alacrity" - a very good history of social software.

See my thoughts below about the need for semantic web contents to support such systems as they become more agile and dynamic.

Many-to-Many

2005-06-28T23:58:00.000-05:00

Many-to-Many

Interesting blog on social software.

Overall, I see social software being a good thing. I believe that as the online community grows, things such as agents and search-avatars that will automatically go out and seek others for you to connect with will have the same needs as any other system which desires to make agile connections based on conceptual interoperability. And those needs start with common reference models for their modes of communication, and those common reference models need to be grounded in a domain ontology. (is that me standing on the soapbox?)

I do have to say that I find the aspects and issues of social software very, very interesting.

Tags and the Growth of Knowledge/Understanding

2005-06-28T23:42:00.000-05:00

Tags and the Growth of Knowledge/Understanding

Very interesting article from a writer who believes that tagging is a good thing. I can't disagree.

Tags: tagging, knowledge management

Unfolding Ontology: the topology of tagging

2005-06-28T23:32:00.000-05:00

digital digs: Unfolding Ontology: the topology of tagging

Very interesting. Yet another take on the Shirky proposal that tagging and ontology is going to be ineffective. Digital Digs proposes that a more bottom up (where a world-view is derived from folkonomy type concepts) approach might work.

The problem I see with the bottom up approach, is that it is based on perception (or worse, prevaricative perception, such as the failed metatag experiment with our current version of the internet), rather than transmitter's intent.

The plot continues to thicken . . .

Tags: ontology, folkonomy, tagging

apophenia: random ontology thoughts

2005-06-28T23:28:00.000-05:00

apophenia: random ontology thoughts

Very interesting - the author posits that before we can really evaluate ontology and the effects that a system which can exploit an ontollogy might make, we have to consider several of the big key ideas of ontology representation (cardinality, indirectness, multiple knowledge parents, etc)

Tags: ontology

Marcus Aurelius on Ontology

2005-06-28T21:16:00.000-05:00

Nothing has such power to broaden the mind as the ability to
investigate systematically and truly all that comes under thy
observation in life.

-Marcus Aurelius

Uncovering the epistemological and ontological assumptions of software designers

2005-06-28T20:47:00.000-05:00

Uncovering the epistemological and ontological assumptions of software designers

Attempts to exploit the fact that while software designers and developers are attempting to work together with weak epistemologies and ontologies, they must achieve this by concentrating on weak similarities between systems. Unfortunately, this only serves to marginalize the interesting features of each individual system. Interesting work, and of particular interest to me as it is strongly grounded in philosophical consideration.

Tags: ontology, epistemology, philosophy

Gardner Writes » Ontology, Ethics, Meaning

2005-06-28T20:05:00.000-05:00

Gardner Writes » Ontology, Ethics, Meaning

Gardner Campbell has written a concise and very interesting riposte to Clay Shirky's "Ontology Overrated" article. Very nice, and I agree with what he is saying.

Gardner's piece has encouraged me to see the effort of forming a formal ontology for a means of communication as a practice in Ethics. By undertaking the attempt to formulate such an ontology, rather than leave the interpretation of the universe of discourse to "popular" view, you are attempting to present the meaning of that discourse in a "correct" view.

Of course this then begs the question of who decides what is correct, but I think that I am getting at "correct" not in a sence of morality, but rather in the sense of being unambiguous in conveying exactly what you want to convey. Your meaning is taken correctly as you intended it when you undertook to communicate.

Thanks, Gardner.

Tags: ontology

Wired News: Folksonomies Tap People Power

2005-06-27T00:10:00.000-05:00

Wired News: Folksonomies Tap People Power

An interesting Wired article from earlier this year spoke about the concept of Folksonomies - the bottom up creation of a taxonomy. This appears to mostly be driven through things like tagging (whether through technorati, flickr, or metadata)

Tags: folksonomies, taxonomy, technorati, meta data

W3C on MetaData

2005-06-27T00:08:00.000-05:00

W3C on Metadata

This is a group that is a few years old, yet what they've produced is right up my alley, and indeed is related to many of the technologies and methods that interest in my studies on Ontology.

Some of the more interesting work is with RDF (largely supplanted by OWL), and also some links to the Dublin Core Metadata Initiative

One of the interesting areas that I worked in while working at the NASA Atmospheric Sciences data archive a few years ago was HDF. HDF stands for the Heirarchical Data Format. It allowed for the very interesting view of data at increasing levels of magnification. Part of how it worked, at least for us, was through copious metadata that solved a numver of different purposes. Here is a good presentation on HDF and it's method for modeling data.
Tags: metadata

Information Intelligence

2005-06-26T23:56:00.000-05:00

Information Intelligence: Intelligent Classification and the Enterprise Taxonomy Practice

This is a white paper put out in 2004 concerning the enterprise practice of organizing and describing their information within a taxonomy. Very nice.

Tags: taxonomy, ontology

Shirky: The Semantic Web, Syllogism, and Worldview

2005-06-26T23:49:00.000-05:00

Shirky: The Semantic Web, Syllogism, and Worldview

This is another article of Clay Shirky's. This one is a bit older, dating from 2003, but there are still interesting things to be found here.

My basic disagreement with Shirky in this article are twofold - first, I don't believe that Syllogisms are the only method that will make use of ontological information and tagging of data or services. Second, metadata does work, I've witnessed its valuable effects. I will admit, however, that for metadata to be useful it has to be accurate and honest.

Tags: Semantic Web

Clay Shirky takes apart Ontology

2005-06-26T08:35:00.000-05:00

Shirky: Ontology is Overrated -- Categories, Links,
and Tags

This is a very interesting article, from an author that has what I USUALLY find to be a very good opinion. This time, however, I think I must disagree with him. More on this later, as I examine the points in this article deeper.

On the other hand, perhaps I'm just a little defensive, as this is my thing these days...

Tags: Ontology Semantic Web

Dooku + Music = dooku.net

2005-06-24T08:56:00.000-05:00

dooku.net

Start it up and start pressing the white button. Groovy.

Conference Schedule

2005-06-23T22:29:00.000-05:00

Just came back from the 10th International Command and Control Research and Technology Symposium last week. It was in Tyson's Corner, and hosted by the Command and Control Research Program, under the Office of the Assistant Secretary of Defense for Networks and Information Integration (OASD/NII). That was a good conference. Made some good contacts, stayed at the Ritz-Carlton(!), had some good food, attended some good talks. Already working on a paper for next year's conference. Brought back some french chocolates from the Ritz-Carlton - Heidi likes the milk chocolate, which leaves the dark chocolate for me. I don't need that...

In July I am attending Summer Computer Simulation Conference, put on by the Society for Modeling and Simulation International. I have written an submitted (and had it accepted) a paper for this conference on "Extending the Levels of Conceptual Interoperability Model". I have entered this paper as a student author - I hope it is well received.

The week before the Summer Sim conference, I will be attending Historicon in Lancaster Pennsylvania. This is an annual event for me, and I've been doing it with the lads from Old Dominion Military Society for as long as that organization has existed (back to about 1989), and before that with the same lads, we just hadn't given ourself a fancy name yet. I will be hosting two wargames at this conference, with Chris Borucki. This year is a first for me, rather than attend with the guys, I will be going with Anita, instead. Should be fun; definitely will be expensive.

In september, I should(?) be attending SISO's Fall SIW (Simulation Interoperability Workshop). Cool. I have a paper already accepted for this one. Now I just have to write it. Damn skippy.

Today in History - Independence for Scotland and Venezuela

2005-06-23T22:14:00.000-05:00

Battle of Bannockburn in 1314 assured Scottish
Independence from the English. Battle won by Robert the Bruce, leading
the blue men.

Battle of Carabobo in 1821 assured Venezuela Independence from the Spanish Royalists. Battle won by Simon Bolivar, leading the Republican army. An awesome website, not in english, has great video of the battle.

SISO Forum Member

2005-06-23T22:01:00.000-05:00

I'm a member of the C4ISR forum for Fall SIW. That means I will be reviewing papers - which is a good thing for me. But it's a bad thing for a summer that I thought I wasn't going to have too many things to do over . . .

Components of Ontology: Concepts

2005-06-23T21:39:00.000-05:00

In paper 05E-SIW-045, the idea of a formal ontology was defined to comprise four different components. These are concepts, entities, relations, and rules. Here are a couple of ideas I'm having about concepts, based on the original paper and also based on a conversation held today with my thesis advisor - Andreas.

Concepts, in 05E-SIW-045, are defined as anything within the universe of discourse with addressable properties. This definition was chosen deliberately, for several reasons.

The first reason for defining concept as anything with addressable properties is based on the concept of a fractal ontology. In a fractal ontology, each layered view of the contents of the ontology can be redefined at a higher resolution view (where more details) or a lower resolution view (with fewer details). When you consider the lowest resolution that you can consider an ontology in - which is perhaps just the idea of "concepts" as a class, and then move through all the various layers of redefinition (starting with the first layer, where concepts are divided up into objects, events, actions, and phenomenology), each layer has more concepts, but each of these concepts is defineable by higher-resolution, comprising concepts. From the perspective of a data model based on our ontology, the highest resolution concepts would be property-values. These are enumerated details defining (and indeed, are instances of) properties. Properties, in turn, are then collected together into propertied-concepts. Propertied-concepts are higher-order ideas, things or entities, that are an abstracted way of thinking of the sum of the comprising propertied-concepts. These are then collected, at a level even further removed from the highest resolution property-vales, into associated-concepts. Associated-concepts are again collections of various propertied-concepts into higher order ideas (which, when considered apart from their comprising propertied-concepts, are necessarily at a lower resolution). And so on up the spiral away from resolution, but more towards higher and higher ordered ideas.

The second reason for defining concept as anything with addressable properties, is because they must needs be considered seperately, and individually at the more higher-resolution levels, due to the fact that they have to be re-assemblable into more than one higher order idea. Much as atoms are able to be combined with other atoms to make a whole bewildering set of different molecules, so the concepts of our ontology must be combined with other concepts to create a large number of other higher order constructions. Consider the battlesphere domain. Here we have a concept known as fuel (a gross simplification). It, itself, is a combination of other higher resolution concepts (the component elements, perhaps, the type of fuel, it's grade, etc). Now fuel is a concept that is combined with other concepts to create a number of higher order concepts. It is a commodity to be considered from a logistics and shipping point of view. It is a component for a vehicle to enable it to enjoy mobility. It is a material that is combustible and may exacerbate weapon effects on buildings that contain fuel. It is also a key component in a number of makeshift weapons employed by irregular troops (the molotov cocktail).

Tags: interoperability, composability, concepts, ontology

Agent Directed Simulation

2005-06-23T14:36:00.000-05:00

Interesting talk about agents and simulation given by Dr. Levent Yilmaz of Auburn University.

Reminds me of an idea I had a while back where a network of nodes, representing a map through a jungle, would be traversed by a bunch of agents simulating monkeys. Different nodes would have different benefits - such as places to sleep, places to eat, places to breed, or places to avoid like tiger clearings. The monkeys would move and while they were in a clearing (node) with each other, they would be able to share some limited information with each other. As the simulation operated over time, there would different goals that motivated the agents for different periods of time. A sleep time would drive the monkeys towards the good sleeping place; periodically there would be a "to breed" sleep time which would drive the monkeys to the boinky-place; etc. As the monkeys traversed and learned the map of nodes (the jungle) they would build up a simple (also incomplete and unreliable) knowledge and memory of paths.

The goal of all this monkey business would be to see if the agents would exhibit some behavior over time, such as learning optimum paths between various locations.

Hmmm. A project for the future.

Tags: simulation, agents

Douglas Hofstadter

2005-06-22T23:41:00.000-05:00

Douglas Hofstadter

An inspiration ever since I read metamagical themas way back in the mid 80s.

Tags: Douglas Hofstadter

Rebirth of the Land of Chuck

2005-06-22T23:18:00.000-05:00

It's been about a year since I first started playing around with blogs. Great idea, I just sort of lost track as I got back into the swing of graduate school and a new job. Now I've been at both for sometime, and I feel as if I need to journal some things. Here it is, begun afresh...I've blown up the old postings, and I begin here with the "official" start to my thesis project.

This will include mostly thoughts on ontology and the semantic web, along with some other wandering thoughts and interesting headbubbles.