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  1. Introduction
  2. RDF (Resource Description Framework)
    1. Metadata
    2. Data Model
    3. Abstraction
    4. RDF
    5. Subject-Predicate-Object Triple Stores
    6. Uniform Resource Identifier
    7. More Information about RDF
  4. RDL ( Resource Description Library)
  5. RDS/WIP (Reference Data System / Work In Progress)
    1. Encapsulate
  6. AEX (Automating Equipment Information Exchange)
  7. Ontology and Taxonomy: Difference Between
    1. Taxonomy
    2. Generalization/Specialization
    3. Subtype/Supertype
    4. Ontology
    5. More Reading
  8. Some More Definitions
    1. Semantic versus syntactic
    2. Semantic precision
    3. Semantic fidelity
    4. Reuse
  9. Next


There are a great many glossaries available, as well as on-line dictionaries and, of course, Wikipedia. A particularly detailed Glossary is right here: STEPDEX: Glossary of Data Management Terms

Another glossary is on the USPI website, Look for Glossary_jun99.doc.

The following are terms that are particularly interesting to ISO 15926 enquirers. They are not in alphabetical order, but are in groups.

RDF (Resource Description Framework)

If you dig deeper under the hood of ISO 15926 you will soon run into this term because it is the means of storing the Part 4 definitions.

Wikipedia says that Resource Description Framework is a set of specifications originally designed as a metadata data model. But if you are like the author, this doesn't help at all, so we will deconstruct the definition.


  • Metatdata is data about data. For instance, one piece of metadata about the ISO 15926 Primer is that it was written on the POSC/Caesar wiki website.

Data Model

  • A data model is an abstract model that describes how data is represented and accessed.


  • Abstraction is a process of generalizing about something to reduce the information content about an object to only those attributes you are interested in. A typical abstraction is the answer 7600 Glover Road to the question "Where do you live?" You might live in a beautiful split level house with a wonderful view of the ocean framed by huge 100 year old pine trees but your questioner only wants to know where to have a package delivered. (On the other hand, yours could be a very ordinary house on a very ordinary road, but the city just wants your land for a freeway bypass and the friendly bulldozer operator needs to know where you live.)


Putting it all together, then, RDF is:

  • instructions on how to represent
  • just the bits of data you are interested in
  • that describes certain other bits of data
  • then access it easily

(Whew! I bet you thought that was going to be difficult!)

In particular, RDF makes statements about things, which it calls Resources, in the form of Subject-Predicate-Object expressions known as Triple Stores.

Subject-Predicate-Object Triple Stores

"The ISO 15926 Primer was written on the POSC/Caesar wiki" might be stored in the RDF as the triple:

  • the subject: ISO 15926 Primer
  • the predicate: was written on
  • the object: POSC/Caesar wiki

The each term in the subject-predicate-object triple may be explicitly named, as in the example above, or they could be in the form of a URI, a Uniform Resource Identifier.

Uniform Resource Identifier

You can think of a Uniform Resource Identifier as a website for a piece of information. This allows the same resource to be reliably referenced many times. So instead of writing the Subject-Predicate-Object triple as above, it could be rendered as:

And in fact we could carry this further by defining somewhere on the Internet the exact meaning of the phrase was written on, and put its URI in the predicate.

More Information about RDF

A good place to start if you want to know more about RDF is the RDF Primer written by the W3C. Be warned, it is not for the feint of heart. But if you can wade through it you will start to see what we mean when we say that "Everything, in the end, is reference data."



SPARQL, pronounced "sparkle", is a query language designed to be used with RDF triple stores. According to Wikipedia, the name stands for "SPARQL Protocol and RDF Query Language". The ISO 15926 RDS/WIP uses SPARQL.


RDL ( Resource Description Library)


RDS/WIP (Reference Data System / Work In Progress)

The RDS/WIP is several things:

  • a library of reference data for ISO 15926
  • a means of publishing core ISO 15926 definitions
  • a platform for developing new ISO 15926 definitions
  • a workspace for harmonizing other standards with ISO 15926 (or each other)

Anyone can search the RDS/WIP and find terms, much like in a dictionary. Accredited users can add information to the RDS/WIP.


Hiding complexity from users who really don't want to know any more.

AEX (Automating Equipment Information Exchange)

The Automating Equipment Information Exchange (AEX) project is developing, demonstrating and deploying XML specifications to automate information exchange for the design, procurement, delivery, operation and maintenance of engineered equipment. The AEX project is part of FIATECH's Roadmap Element 3. It it being developed in conjunction with the IDS-ADI project because of the large overlap between them.


Ontology and Taxonomy: Difference Between

Taxonomy - Quick 'n Dirty

If you've ever made a classified list of all your CDs, you've made a taxonomy. (If you're as old as the author, you might have to rephrase the question to "If you've ever made a classified list of all your player piano rolls...!") And if you've ever had to grapple with the question of where to classify Weird Al (under "Parody", "Rock and Roll", or "Idiot"?), you've come up against the idea of single or multiple inheritance!

Ontology - Quick 'n Dirty

If you've ever played the parlor game Twenty Questions, you intuitively understand ontology. In this game you more-or-less start with an Ontology-of-Everything-In-The-World, and with each successive question ("Is it a ...?") apply a more limited ontology as a filter (usually starting with "Is it an Animal, Vegetable, or Mineral?") until there is only one object left, The Answer, that satisfies membership (or non-membership in the case the answer to "Is it a ...?" is "No!") in all the ontologies.

Ontology and Taxonomy are both terms in a continuum that some information scientists call Knowledge Organization Systems (KOS). And just to confuse you some more, the continuum incudes Thesaurus, Controlled Vocabulary, and Faceted Classification. The bad news for those of you not used to dealing with ambiguity (All you mechanical engineers out there: Raise your hands!) is that there is a great deal of overlap in those terms. Even people who's job it is to know these things (All you mechanical engineers out there: Put your hands down!) can't give a short answer when asked where the boundaries are.


A taxonomy is a collection of terms that have explicit definitions that have been organized into a hierarchical structure. They tend to be organized in tree-like structures that are reasonably easy to understand, even by non-specialized people. Each term is related to its parent in a is-a-kind-of relationship.

For instance, a car is-a-kind-of automobile. But a car also is-a-kind-of machine, so if your taxonomy is concerned with machines, you should analyze the relative order of these three things. Depending on the purpose of your taxonomy, you will likely end up with:

  • car is-a-kind-of automobile, which is-a-kind-of machine.


The is-a-kind-of relationship is known as generalization/specialization. In the above example a car is a specialization of automobile; automobile is a generalization of car.


Subtype/supertype is just another way of saying generalization/specialization. So continuing the example above, car is a subytpe of automobile; automobile is a supertype of car. The understanding is that the subtype has all the constraints of the supertype, plus one or more additional constraints.


In the realm of philosophy, ontology is the study of being; the study of the things that are. In the realm of information science (which is where ISO 15926 firmly resides), ontology has a more formal meaning. Wikipedia says that an ontology is "a formal representation of a set of concepts within a domain and the relationships between those concepts."

Like Taxonomies, ontologies are also arranged in a is-a-kind-of relationship, but the relationships tend to be more richly defined. The difference is subtle. One commentator compared the difference between ontology and taxonomy to your computer hard disk. The taxonomy would be the directory structure without the files, while the ontology would be the files organized by the directory structure.

Earlier in this Primer, we talked about an Ontology of Things That Will Carry a Bicycle. The Ontology is the whole collection of things that will carry a bicycle. Each object in the ontology would have a Taxonomy that you could examine.

More Reading


Some More Definitions

Semantic versus syntactic


Semantic precision


Semantic fidelity






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