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Understanding Classification Systems

(This blog post relates to trying to sort out two very good graphs (graphic 1, graphic 2) for the purpose of creating a better graphic which includes XBRL and other things related to XBRL. The first step is to sort out all the terms used in the diagrams.  This blog post focuses on classification systems.)

A classification system is a grouping of something based on some criteria.  There are many different types of classification systems.  David Wenberger's book Everything Is Miscellaneous points out two important things to remember about classification systems:

  • That every classification scheme ever devised inherently reflects the biases of those that constructed the classification system.
  • The role metadata plays in allowing you to create your own custom classification system so you can have the view of something that you want.

Everything is Miscellaneous also describes the three "orders of order" of classification systems:

  • First order of order. Putting books on shelves is an example the first order of order.
  • Second order of order. Creating a list of books on the shelves you have is an example of second order of order. This can be done on paper or it can be done in a database.
  • Third order of order. Adding even more information to information is an example of third order of order. Using the book example, classifying books by genre, best sellers, featured books, bargin books, books which one of your friends has read; basically there are countless ways to organize something.

The following is a summary of terminology used to describe different types of classification systems on the two grapics pointed out above plus other items which seem to belong in the list of classification systems:

  • List: A set of items or things.
  • Dictionary: A dictionary is much like a list, a dictionary had no hierarchy.
  • Glossary: A glossary contains explanations of concepts relevant to a certain field of study or action. In this sense, the term is related to the notion of ontology.
  • Thesaurus: Lists grouped together according to similarity of meaning.
  • Controlled vocabulary: Controlled vocabularies provide a way to organize knowledge for subsequent retrieval. They are used in subject indexing schemes, subject headings, thesauri, taxonomies and other forms of knowledge organization systems. Controlled vocabulary schemes mandate the use of predefined, authorised terms that have been preselected by the designer of the vocabulary, in contrast to natural language vocabularies, where there is no restriction on the vocabulary.
  • Taxonomy: A taxonomy is a classification system which does have a hierarchy, but the hierarchy tends to be less formal.
  • Folksonomy: A folksonomy is a system of classification derived from the practice and method of collaboratively creating and translating tags to annotate and categorize content; this practice is also known as collaborative tagging, social classification, social indexing, and social tagging.
  • Ontology: An ontology is a set of well-defined concepts which describes a specific domain. Ontologies tend to be more formal, more complete, and more precise classification systems.  The goal of an ontology is to provide a formal, machine readable, referancable set of concepts which are used in communications within a domain which precisely describes the domain. An ontology is also expressed as a hierarchy, but the hierarchy is more explicit and much richer in meaning than a taxonomy.

These things appear to be modeling systems which were somewhat intermingled with classification systems; they seem to be approaches to representing a classification system:

  • Entity-relationship diagram (ER model): An entity–relationship model (ER model) is a data model for describing the data or information aspects of a business domain or its process requirements, in an abstract way that lends itself to ultimately being implemented in a database such as a relational database. The main components of ER models are entities (things) and the relationships that can exist among them.
  • Conceptual model: A conceptual model is a model made of the composition of concepts, that thus exists only in the mind. Conceptual models are used to help us know, understand, or simulate the subject matter they represent.
  • Concept map: A concept map is a diagram that depicts suggested relationships between concepts.
  • Topic map: A topic map is a standard for the representation and interchange of knowledge, with an emphasis on the findability of information.
  • UML (Unified Modeling Language): The Unified Modeling Language (UML) is a general-purpose modeling language in the field of software engineering to model systems. The basic level provides a set of graphic notation techniques to create visual models of object-oriented software-intensive systems. Higher levels cover process-oriented views of a system.
  • XMI (XML Metadata Interchange): XML standard for exchanging metadata information.

All this stuff seems to fit into these general notions: (the big picture)

  • Network theory: Network theory concerns itself with the study of graphs as a representation of relations between objects.
  • Graph theory: Graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects.
  • Theory of relations: A relation in mathematics is defined as an object that has its existence as such within a definite context or setting.
Posted on Sunday, March 30, 2014 at 10:53AM by Registered CommenterCharlie in | CommentsPost a Comment

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