I attended an interesting webinar by Golden Source (www.thegoldensource.com) today about Solvency II. Solvency II is a huge pan-European insurance regulatory framework that is going to be implemented over the next few years.
Not unexpectedly, definitions came up. The point was made that an insurer has to not only know what its definitions of concepts are, but also definitions used by its partners. For instance, an insurance company may utilize the services of many asset managers (as part of its overall investment activities). For Solvency II purposes, the insurance company must know what its definition of e.g. "Country of Risk" is, and also how each of its Asset Manager partners defines "Country of Risk".
This is an important point. Data managers often only look within the enterprise when it comes to definitions. Yet there can be compelling reasons to track the definitions that are used by other organizations which the enterprise interacts with.
I have noticed that when I bring this point up, some colleagues think that reason to do this work is to figure out which definition is "right". However, the practical need is for semantic interoperability, not arguing about correctness of a term. We need to understand definitions used by our partners as a first step to integrating data they send to us. Therefore we have a requirement to track the definitions used by our partners. An interesting challenge, but one clearly highlighted by the requirements of Solvency II.
Wednesday, November 30, 2011
Monday, November 28, 2011
Evolution of Definitions – The Problem of Pluto
In early 2006 I had the privilege of seeing NASA’s New Horizon’s mission blast off on its way to Pluto. At that time, Pluto was a planet. By August of the same year it was not.
On August 24, 2006, the International Astronomical Union (IAU) publicly defined a planet as "a celestial body that (a) is in orbit around the Sun, (b) has sufficient mass for its self-gravity to overcome rigid body forces so that it assumes a hydrostatic equilibrium (nearly round) shape, and (c) has cleared the neighbourhood around its orbit.".
This raises questions such as:
As to the IAU, it is quite free to come up with a definition for any term – just as the Red Queen did in Alice in Wonderland. And I too am free to have my own definition of a planet. Whether the IAU’s definition will stand up is a good question. New research suggests that extra-solar planetary systems are very diverse. The IAU’s definition may very well not stand up in the face of future discoveries – but surely such evolution is part of what science is. As to motivation, that is a discussion for another post – but it often matters for all kinds of reasons.
On August 24, 2006, the International Astronomical Union (IAU) publicly defined a planet as "a celestial body that (a) is in orbit around the Sun, (b) has sufficient mass for its self-gravity to overcome rigid body forces so that it assumes a hydrostatic equilibrium (nearly round) shape, and (c) has cleared the neighbourhood around its orbit.".
This raises questions such as:
- Can definitions change? Pluto had been called a planet until the IAU changed the boundaries of the definition.
- What authority has the IAU to define a planet?
- I still think of Pluto as a planet – am I wrong to do so?
- The IAU’s new definition seems a bit contrived. Will it stand up?
- What motivation did the IAU have to change the definition?
As to the IAU, it is quite free to come up with a definition for any term – just as the Red Queen did in Alice in Wonderland. And I too am free to have my own definition of a planet. Whether the IAU’s definition will stand up is a good question. New research suggests that extra-solar planetary systems are very diverse. The IAU’s definition may very well not stand up in the face of future discoveries – but surely such evolution is part of what science is. As to motivation, that is a discussion for another post – but it often matters for all kinds of reasons.
Saturday, November 26, 2011
A Note on the Role of Precision in Definitions
The term "precision" seems to have changed its meaning over the centuries, which may cause confusion to anyone dealing with the literature of definitions. It signifies more than one concept, which muddles things up. Unfortunately, I may be adding to the muddle, as some of my points in this post are from memory, and I will have to rediscover the references for them. However, I wanted to capture what I now have about precision.
The etymology of "precision", according to Peirce, means "to cut off at the end" (from "Issues in Pragmatism", The Monist, Vol 15, Oct 1905 pp481-499). Apparently, it is connected with "curt denials and refusals" - cutting someone off. Oddly, this seems to have tradionally meant that the more cutting off you did, the greater precision you achieved. As such, it runs counter to our idea of numerical precision, where the greater the number of decimal places, the greater the precision. On the traditional view, the fewer the number of decimal places (the more chopping off we have done) would seen to mean the greater the precision (though I cannot find an example to confirm this numerical aspect of precision in traditional literature).
Peirce also had something to say about precision in definitions. According to him, removal of superflous words achieves greater precision in a definition (again from my memory, so needs to be checked). I think that this rule applies more to summary than to definition, and Peirce may have been thinking about definition work he was doing for dictionaries, where printing costs are a factor. Too much text may be repetitous or confusing. However, repetition may be valuable to drive a point home. Confusion is not always produced by additional text, but can be a danger.
Perhaps a more important point involves using the word "prescind" (the act of precision) which today seems to be replaced by the overloaded term "abstraction". When we prescind we cut away from concrete instances. E.g. the concept "animal" can apply to individual instances, but "animality" cannot (from Sullivan, An Introduction to Traditional Logic ISBN 1-4196-1671-4, pp 23-24). The greater the precision of a concept, the greater its "abstraction". Traditionally, "concrete concepts" are abstractions "without precision" (since they apply to individuals), while "abstract concepts" are concepts "with precision" since they cannot apply to individuals (Sullivan, footnote on p24). So, perhaps counter-intuitively, the more abstract a concept is, the more precise it is.
The etymology of "precision", according to Peirce, means "to cut off at the end" (from "Issues in Pragmatism", The Monist, Vol 15, Oct 1905 pp481-499). Apparently, it is connected with "curt denials and refusals" - cutting someone off. Oddly, this seems to have tradionally meant that the more cutting off you did, the greater precision you achieved. As such, it runs counter to our idea of numerical precision, where the greater the number of decimal places, the greater the precision. On the traditional view, the fewer the number of decimal places (the more chopping off we have done) would seen to mean the greater the precision (though I cannot find an example to confirm this numerical aspect of precision in traditional literature).
Peirce also had something to say about precision in definitions. According to him, removal of superflous words achieves greater precision in a definition (again from my memory, so needs to be checked). I think that this rule applies more to summary than to definition, and Peirce may have been thinking about definition work he was doing for dictionaries, where printing costs are a factor. Too much text may be repetitous or confusing. However, repetition may be valuable to drive a point home. Confusion is not always produced by additional text, but can be a danger.
Perhaps a more important point involves using the word "prescind" (the act of precision) which today seems to be replaced by the overloaded term "abstraction". When we prescind we cut away from concrete instances. E.g. the concept "animal" can apply to individual instances, but "animality" cannot (from Sullivan, An Introduction to Traditional Logic ISBN 1-4196-1671-4, pp 23-24). The greater the precision of a concept, the greater its "abstraction". Traditionally, "concrete concepts" are abstractions "without precision" (since they apply to individuals), while "abstract concepts" are concepts "with precision" since they cannot apply to individuals (Sullivan, footnote on p24). So, perhaps counter-intuitively, the more abstract a concept is, the more precise it is.
Friday, November 25, 2011
Must a Definition Include Identification of Related Concepts?
The traditional answer to this question is "yes", because classic essential definitions follow the formula Definition = Genus + Specific Difference.
However, definitions of concepts in natural science tend to be more like descriptions than classical definitions. This may be unavoidable, but there is always a danger in a descriptive definition of not mentioning any related concepts. Such definitions may give the impression of a style in which definitions should be written, and this sometimes carries over into analyst work - so that some analysts tend to write descriptive definitions, even if essential ones could be provided. And such definitions lack mention of related concepts.
But should a definition always identify related concepts? I think it should. I think that practical usage of a definition requires an understanding of the Concept System in which the definition is located. Without such an understanding, the user runs a risk of not being able to use the definition adequately. I will have to return to this to offer a proof in the future.
The Concept System itself is a concept. Merely identifying the Concept System may be at too high a level of generalization - but it is better than nothing. Better would be to find a proximate superordinate genus (an immediate parent supertype) within the Concept System, but this may sometimes be difficult.
A concept need not have just one relation (to the Concept System or a higher-level concept within it). It may have other relationships. Identifying such relationships in definitions will be helpful too. This is a topic that leads to matching definitions to Conceptual Models, which we will have to return to.
Therefore, I think that we have an additional quality assurance point for definitions: a definition must identify a superordinate genus within the Concept System in which it is located, or identify the Concept System itself.
A futher quality assurance point might be that a definition must identify all relations between the concept being defined and other relevant concepts - but this point needs to be followed up in a future post.
This leads to the consideration that a definition of a concept will change depending on the Concept System it is located in, and one concept can be located in more than one Concept System. And that it yet another topic for a future post.
However, definitions of concepts in natural science tend to be more like descriptions than classical definitions. This may be unavoidable, but there is always a danger in a descriptive definition of not mentioning any related concepts. Such definitions may give the impression of a style in which definitions should be written, and this sometimes carries over into analyst work - so that some analysts tend to write descriptive definitions, even if essential ones could be provided. And such definitions lack mention of related concepts.
But should a definition always identify related concepts? I think it should. I think that practical usage of a definition requires an understanding of the Concept System in which the definition is located. Without such an understanding, the user runs a risk of not being able to use the definition adequately. I will have to return to this to offer a proof in the future.
The Concept System itself is a concept. Merely identifying the Concept System may be at too high a level of generalization - but it is better than nothing. Better would be to find a proximate superordinate genus (an immediate parent supertype) within the Concept System, but this may sometimes be difficult.
A concept need not have just one relation (to the Concept System or a higher-level concept within it). It may have other relationships. Identifying such relationships in definitions will be helpful too. This is a topic that leads to matching definitions to Conceptual Models, which we will have to return to.
Therefore, I think that we have an additional quality assurance point for definitions: a definition must identify a superordinate genus within the Concept System in which it is located, or identify the Concept System itself.
A futher quality assurance point might be that a definition must identify all relations between the concept being defined and other relevant concepts - but this point needs to be followed up in a future post.
This leads to the consideration that a definition of a concept will change depending on the Concept System it is located in, and one concept can be located in more than one Concept System. And that it yet another topic for a future post.
Thursday, November 24, 2011
The Fallacy of Language As The Mirror of Reality
Analysts can sometimes create huge problems if they try to produce single definitions for terms within a single semantic community and within a single universe of discourse. This may sound crazy, so let me start by giving an example.
Not long ago I was in a discussion concerning data quality. The group leaders decided there was a need to discuss the so-called "dimensions of data quality", e.g. Accuracy, Consistency, Timeliness, and so on. We started with Consistency. Each individual in the group offered their view of what Data Consistency was. Several different definitions were offered. Eventually, the group took a vote and decided which definition of Data Consistency they preferred. The alternative definitions were not discussed further, nor recorded. The individuals who had proposed the unaccepted definitions felt slighted, perhaps even hurt. And they had a right to - as far as I could tell, the alternative definitions represented valid concepts.
What a broken process! Definitions of valid concepts were simply rejected, and lost. Individuals were turned off from definitional work, maybe permanently. Why did it happen? I think I can offer a hypothesis.
The first mistake is to believe in that every concept that is known of is represented by a term in language. Unknown concepts will obviously not be so represented. But what is "unknown" in a semantic community? Is it any concept not known by everyone in the community? What about a concept only understood by a minority in the community?
Secondly, in technical language, there seems to be more expected of technical terms than is warranted. They sound "scientific". They sound as if we should expect them to convey something precise - a trick taken advantage of by thousands of misleading advertisements every day. But there is no reason to expect a technical term to have an agreed definition by everyone in a semantic community. There may be several valid concepts competing to be signified by the term.
The expectation - in technical areas - that terms mirror known reality should not be relied on. The phrase "language as a mirror of reality" is connected with Wittgenstein (see http://www.percepp.com/lacus.htm). It should be granted he may not have been talking about terms per se, and granted that probably few analysts are conciously influenced by Wittgenstein. However, the presupposition seems to have got about somehow, and, anyway academics show little interest in how analysts go about their daily work.
Language cannot be assumed to mirror reality in technical areas. Analysts must create governance processes that guide their definitional work so they harvest all valid concepts, and encourage members of semantic communities to contribute. Terms are starting points, not a final list of signs that denote all the individual concepts in a universe of discourse.
Not long ago I was in a discussion concerning data quality. The group leaders decided there was a need to discuss the so-called "dimensions of data quality", e.g. Accuracy, Consistency, Timeliness, and so on. We started with Consistency. Each individual in the group offered their view of what Data Consistency was. Several different definitions were offered. Eventually, the group took a vote and decided which definition of Data Consistency they preferred. The alternative definitions were not discussed further, nor recorded. The individuals who had proposed the unaccepted definitions felt slighted, perhaps even hurt. And they had a right to - as far as I could tell, the alternative definitions represented valid concepts.
What a broken process! Definitions of valid concepts were simply rejected, and lost. Individuals were turned off from definitional work, maybe permanently. Why did it happen? I think I can offer a hypothesis.
The first mistake is to believe in that every concept that is known of is represented by a term in language. Unknown concepts will obviously not be so represented. But what is "unknown" in a semantic community? Is it any concept not known by everyone in the community? What about a concept only understood by a minority in the community?
Secondly, in technical language, there seems to be more expected of technical terms than is warranted. They sound "scientific". They sound as if we should expect them to convey something precise - a trick taken advantage of by thousands of misleading advertisements every day. But there is no reason to expect a technical term to have an agreed definition by everyone in a semantic community. There may be several valid concepts competing to be signified by the term.
The expectation - in technical areas - that terms mirror known reality should not be relied on. The phrase "language as a mirror of reality" is connected with Wittgenstein (see http://www.percepp.com/lacus.htm). It should be granted he may not have been talking about terms per se, and granted that probably few analysts are conciously influenced by Wittgenstein. However, the presupposition seems to have got about somehow, and, anyway academics show little interest in how analysts go about their daily work.
Language cannot be assumed to mirror reality in technical areas. Analysts must create governance processes that guide their definitional work so they harvest all valid concepts, and encourage members of semantic communities to contribute. Terms are starting points, not a final list of signs that denote all the individual concepts in a universe of discourse.
Wednesday, November 23, 2011
A Brief Review of Nordterm 8 - A Guide to Terminology
In the sparse literature about definitions, most publications are from Academia. However, Nordterm 8 Guide to Terminology by Heidi Suonuuti (ISBN 952-9794-14-2) is a very useful and practical booklet from a practicioner community. Further details can be found at
http://www.nordterm.net/info/Publ/PNORDTERM8-en.html.
Nordterm describes itself as follows: "Nordterm is an association of organisations and societies in the Nordic countries which are engaged in terminology work, training and research.". Terminology work, of course, covers much more than definitions, but A Guide to Terminology does contain a fair amount on definitions, and has a very practical focus.
Nordterm 8 contains a very useful set of references, particularly about ISO Standards. It introduces definitions in a section on Concept Analysis, that is also valuable as an overview of ontology - again from a practical perspective. A section dedicated to definitions follows, with systematization in terminology work as a special focus. A valuable high level methodology for terminology work is presented next - again very practical. Deficient definitions are examined next. The following major section is on terms. This, of course, is a specialist topic within terminology, but obviously closely allied to definition work. Finally, there is a summary of the terms used in terminology work (alas without definitions) and their translations in Nordic languages. The whole booklet is 42 pages.
A Guide to Terminology would be valuable just because there is so little literature, and Academia seems to have a mission to avoid any practical contributions. However, the booklet packs a lot into a small volume and is highly informative and will be a help to any practicioner.
http://www.nordterm.net/info/Publ/PNORDTERM8-en.html.
Nordterm describes itself as follows: "Nordterm is an association of organisations and societies in the Nordic countries which are engaged in terminology work, training and research.". Terminology work, of course, covers much more than definitions, but A Guide to Terminology does contain a fair amount on definitions, and has a very practical focus.
Nordterm 8 contains a very useful set of references, particularly about ISO Standards. It introduces definitions in a section on Concept Analysis, that is also valuable as an overview of ontology - again from a practical perspective. A section dedicated to definitions follows, with systematization in terminology work as a special focus. A valuable high level methodology for terminology work is presented next - again very practical. Deficient definitions are examined next. The following major section is on terms. This, of course, is a specialist topic within terminology, but obviously closely allied to definition work. Finally, there is a summary of the terms used in terminology work (alas without definitions) and their translations in Nordic languages. The whole booklet is 42 pages.
A Guide to Terminology would be valuable just because there is so little literature, and Academia seems to have a mission to avoid any practical contributions. However, the booklet packs a lot into a small volume and is highly informative and will be a help to any practicioner.
A First Note on Partial Definitions
I think that partial definitions exist, and there are practical reasons for being interested in them. I cannot find any literature about them, and this post is my first attempt at dealing with partial definitions.
The only conceptualization of a partial definition that I have figured out in any detail can be summarized by the formula:
Partial Definition = Name of Concept System + Type of Relation in Concept System
E.g., for "Wristwatch"
Definition of "Wristwatch" = "A type of timepiece"
Obviously, this parallels the Aristoteialan formula of Definiton = Genus + Specific Difference. However, I think that Aristotle commits definitions to being only in a Concept System of generic relations (supertype-subtype to our data modeling friends). Other types of Concept System exist, e.g. partative (part-whole), and associative.
In a partial definition we provide information by locating the concept to be defined within a particular Concept System, giving context to the minds we are communicating with. Of course, we must expect that these minds know about the Concept System we name in the partial definition.
The Concept System does not have to be a proximate Genus, as Aristotle would like. It could be a much higher level generic concept, though this may broaden the context too much. In the above example, locating "Wristwatch" in the concept system "Timepiece" provides more precise context than if I said "A type of instrument", "instrument being a more generic concept containing "Timepiece". Obviously, there is skill required to choose the level appropriate to the mind being communicated with.
There is also the choice of Concept System to locate the concept in. For "Wristwatch" I could have alternative partial definitions such as "A fashion accessory", or "An item of jewelery". These identify different Concept Systems within which I wish to locate "Wristwatch" for whatever my purposes may be.
The Type of Relation in the Concept System in my formula above (e.g. "type", "part", "item") is one level of abstraction up from a description of the Concept System itself. I think it serves to reinforce the essence of the Concept System.
While full definitons are not something we work on every day, I think partial definitions are very common in everyday communication.
That's enough for now. To summarize (and these points may need further proof):
The only conceptualization of a partial definition that I have figured out in any detail can be summarized by the formula:
Partial Definition = Name of Concept System + Type of Relation in Concept System
E.g., for "Wristwatch"
Definition of "Wristwatch" = "A type of timepiece"
Obviously, this parallels the Aristoteialan formula of Definiton = Genus + Specific Difference. However, I think that Aristotle commits definitions to being only in a Concept System of generic relations (supertype-subtype to our data modeling friends). Other types of Concept System exist, e.g. partative (part-whole), and associative.
In a partial definition we provide information by locating the concept to be defined within a particular Concept System, giving context to the minds we are communicating with. Of course, we must expect that these minds know about the Concept System we name in the partial definition.
The Concept System does not have to be a proximate Genus, as Aristotle would like. It could be a much higher level generic concept, though this may broaden the context too much. In the above example, locating "Wristwatch" in the concept system "Timepiece" provides more precise context than if I said "A type of instrument", "instrument being a more generic concept containing "Timepiece". Obviously, there is skill required to choose the level appropriate to the mind being communicated with.
There is also the choice of Concept System to locate the concept in. For "Wristwatch" I could have alternative partial definitions such as "A fashion accessory", or "An item of jewelery". These identify different Concept Systems within which I wish to locate "Wristwatch" for whatever my purposes may be.
The Type of Relation in the Concept System in my formula above (e.g. "type", "part", "item") is one level of abstraction up from a description of the Concept System itself. I think it serves to reinforce the essence of the Concept System.
While full definitons are not something we work on every day, I think partial definitions are very common in everyday communication.
That's enough for now. To summarize (and these points may need further proof):
- Partial Definitions exist
- A common kind of Partial Definition is to locate a concept in a Concept System
- The Partial Defintion also describes the type of relation that predominates in the Concept System
- There is skill in selecting the Concept System as one concept can belong to many Concept Systems
- There is skill in selecting the level of generalization of the Concept System
- Partial Definitions are very common in everyday language (does that mean that everyone is an ontologist?)
Subscribe to:
Posts (Atom)