Changes between Version 84 and Version 85 of ISO15926Primer_Glossary

11/20/11 03:51:45 (10 years ago)
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  • ISO15926Primer_Glossary

    v84 v85  
    33= Glossary = 
    5 ---- 
    6 [[PageOutline(2-4,Contents,inline)]] 
     5The '''ISO 15926 Primer''' has been replaced with '''An Introduction to ISO 15926''', a free download from Fiatech. 
    8 ---- 
    9 == Introduction == 
    10 There are a great many glossaries available, as well as on-line dictionaries and, of course, Wikipedia.  Here are two: 
     7This page is out of date and has been deprecated. 
    12   * [  USPI Glossary]  Look for Glossary_jun99.doc. 
     9If you reached this page from a link in another web page please inform the webmaster. 
    14   * [ ISO Terms] 
     11For a peek at the new book and instructions on how to download a copy please follow this link. 
    16 So the world does not need another complete listing of computer terminology.  But to save you time searching, the following are terms that are particularly interesting to the study of ISO 15926. 
    18 ---- 
    19 == Artificial Intelligence and the Semantic Web:  Difference Between == 
    21 '''Artificial Intelligence''' - Quick 'n Dirty 
    23   Making ''machines'' smarter 
    25 '''Semantic Web''' - Quick 'n Dirty 
    27   Making ''data'' smarter 
    29 We all want to be able to find and use information on the World Wide Web easier and more reliably.  The Artificial Intelligence approach is to make machines smarter by teaching them to infer the meaning of web data by using techniques such as natural language and image processing.  In contrast, the Semantic Web approach is to make the data itself smarter (that is, by making the data easier for machines to find, access, and process) by using techniques for expressing data and meaning in a standard machine-readable format. 
    31 ISO 15926 uses some Semantic Web technology to describe plant objects in a way that computers can understand.   
    33 '''Suggested Reading''' 
    35   * [ Wikipedia: Semantic Web]  [[BR]]Good introduction describing the need, promise, and some of the considerable challenges to making the Semantic Web ubiquitous. 
    37   *  [[BR]]A Scientific American article describing how the Semantic Web could be used.  (Login Required) 
    39   * [[BR]] The main W3C Semantic Web site. 
    41   * [[BR]]A compilation of resources for learning about Semantic Web enabling technology. 
    43   * [[BR]]Introduction to the Semantic Web. 
    45 ---- 
    47 == RDF (Resource Description Framework) == 
    48 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. 
    50 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. 
    52 === Metadata === 
    53  * Metadata 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. 
    55 === Data Model === 
    56  * A data model is an ''abstract'' model that describes how data is represented and accessed. 
    58 === Abstraction === 
    59  * ''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.) 
    61 === RDF === 
    62 Putting it all together, then, RDF is: 
    64  * instructions on how to represent 
    65  * just the bits of data you are interested in 
    66  * that describes certain other bits of data 
    67  * then access it easily 
    69 (Whew!  I bet you thought that was going to be difficult!) 
    71 In particular, RDF makes statements about things, which it calls ''Resources'', in the form of ''Subject''-''Predicate''-''Object'' expressions known as ''Triple'' ''Stores''. 
    73 === Subject-Predicate-Object Triple Stores === 
    74 "The ISO 15926 Primer was written on the POSC/Caesar wiki" might be stored in the RDF as the triple: 
    76  * the subject: ''ISO 15926 Primer'' 
    77  * the predicate: ''was written on'' 
    78  * the object: ''POSC/Caesar wiki'' 
    80 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''. 
    82 === Uniform Resource Identifier === 
    83 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: 
    85  * the subject: '' 
    86  * the predicate: ''was written on'' 
    87  * the object: ''POSC/Caesar wiki'' 
    89 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. 
    91 '''Suggested Reading''' 
    93   * "Other Resources for Learning About ISO 15926", [ RDF] 
    95 === XML (Extensible Markup Language) === 
    97 ISO 15926 uses Extensible Markup Language as a transport language.  With XML, information is written in a manner that allows machines to know what the data values represent.  Like HTML, XML uses tags bounded by "<" and ">", but the tags in XML are intended to describe what the data is, rather than how to render it on a computer screen.  Thus, the appearance of an XML document is not generally important. 
    99 === OWL (Web Ontology Language) === 
    101 OWL is actually a family languages for creating ontologies.  It is fundamental to the Semantic Web.  OWL ontologies are usually expressed using RDF/XML syntax. 
    103 === SPARQL === 
    105 SPARQL, pronounced "sparkle", is a query language designed to be used with RDF triple stores.  It's name is self referencing, "SPARQL Protocol and RDF Query Language".  The ISO 15926 RDS/WIP uses SPARQL. 
    107 === Gellish === 
    109 Gellish (originally derived from ''General'' ''Engineering'' ''Language'') is a language in which information can be expressed in a manner that is computer readable.  Gellish is one way to make the ISO 15926-7 templates.   
    111 ---- 
    113 == RDS/WIP (Reference Data System / Work In Progress) == 
    115 The classes that make up Part 4, the dictionary of ISO 15926, are stored in what is called the RDS/WIP (Reference Data System/Work In Progress.) To search the classes you use an RDS/WIP browser.  
    117 The RDS/WIP is several things:  
    119   * a library of reference data for ISO 15926  
    120   * a means of publishing core ISO 15926 definitions  
    121   * a platform for developing new ISO 15926 definitions  
    122   * a workspace for harmonizing other standards with ISO 15926 (or each other)  
    124 The RDS/WIP is a large triple store in the form of Subject-Predicate-Object.  It uses semantic web technology (OWL, RDF, and SPARQL) over top of a conventional web technology such as HTTP to provide machine-oriented access to the stored definitions.  A conventional HTML presentation is used to provide a human-oriented interface to the same system. 
    126 Anyone can search the RDS/WIP and find terms, much like in a dictionary. Accredited users can add information to the RDS/WIP.  
    128 ---- 
    130 == Ontology and Taxonomy: Difference Between == 
    131 '''Taxonomy''' - Quick 'n Dirty 
    132  If you've ever made a classified list of all your CDs, you've made a ''taxonomy''.  (But if you're as old as the author, CDs are old hat.  You learned how to do this years ago with 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! 
    134 '''Ontology''' - Quick 'n Dirty 
    135  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?") The game ends when 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. 
    137 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'' among many other things.  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. 
    139 === Taxonomy === 
    141 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. 
    143 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: 
    145   * car is-a-kind-of automobile, which is-a-kind-of machine.  
    147 === Generalization/Specialization === 
    149 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. 
    151 === Subtype/Supertype === 
    153 Subtype/supertype is just another way of saying ''generalization/specialization''.  So continuing the example above, car is a subtype 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. 
    155 === Ontology === 
    157 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." 
    159 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. 
    161 Earlier in this Primer, we talked about an [wiki:ISO15926Primer_History#Ontology Ontology of Things That Will Carry a Bicycle].  This ''Ontology'' is the whole collection of things that will carry a bicycle in case the author's bicycle breaks down on the way to work.  Each object in the ontology would have a ''Taxonomy'' that you could examine. 
    163 '''Suggested Reading''' 
    165 If you want to see how deep the subject of Ontology is, here are two links. 
    167 Professor Dagobert Soergel of the University of Maryland has written an explanation of Knowledge Organization Systems: 
    169   * attachment:SoergelKOS.pdf 
    171 A number of ontology professionals have formed an organization called '''Ontolog'''.  It is devoted to advancing the field of ontology, ontological engineering, and semantic technology.  The organization hosts regular lectures via conference call that are open to anyone.  Links to past lectures are maintained on their website. 
    173   * [[BR]]Ontolog Home Page 
    175 == First Order Logic == 
    177 '''First Order Logic''' - Quick 'n Dirty 
    179   If you've ever taken a mathematics course where you have had to prove something, you've used first order logic. 
    181 First order logic is used in ISO 15926 as a basis for developing the classes, which make up Part 4, and the templates, which make up Part 7.  If you are looking for an introduction, [ Wikipedia] is hard to beat. 
    183 ---- 
    185 == Some More Terms == 
    187 === Semantic === 
    189 '''Semantics''' - Quick 'n Dirty 
    191   If you've ever read Alice's conversation with Humpty Dumpty, you've had a lesson in semantics.  An excerpt: 
    193   ''Humpty Dumpty:  "...How old did you say you were?"[[BR]]'' 
    194   ''Alice made a short calculation, and said "Seven years and six months."[[BR]]'' 
    195   ''"Wrong!" Humpty Dumpty exclaimed triumphantly.  "You never said a word like it!"[[BR]]'' 
    196   ''"I thought you meant 'How old ''are'' you?'"  Alice explained.[[BR]]'' 
    197   ''"If I'd meant that, I'd have said it," said Humpty Dumpty.'' 
    199 '''Semantics''' has to do with ''meaning''.  Sometimes the word is used derisively, as in ''...Yes'', ''but'' ''that's'' ''only'' ''semantics''.  But in ISO 15926 semantics is ''everything''.  Elsewhere in this Primer we have talked about embedding context with the data.  What we mean by this is capturing the semantics. 
    201 '''Semantic''' means that a precise meaning, neither no more or no less, can be had.  For instance, in a field of engineering there might be many versions of the word ''temperature''.  A user of any of the versions must be able to use each version reliably to convey the correct meaning. 
    203 ''' Semantic fidelity''' is used when describing information exchanges.  We are looking for high semantic fidelity to make sure the meaning of data values is preserved in the receiving end. 
    205 === Syntactic === 
    207 Syntax is concerned with structure and addressability.  That is, the ''position'' of a word in a formal logic statement affects its meaning. 
    209 === Reuse === 
    211 Reuse is a central idea in ISO 15926, in that once a compliant system for exchanging information is set up, it can be reused an infinite number of times at no extra cost.  This runs counter to the notion of point-to-point mapping to achieve interoperability, which is application-specific (and often version-specific) and cannot be reused for more than its original design. 
    213 === Encapsulate === 
    214 Hiding complexity from users who really don't want to know more. 
    217 == Next == 
    218  * [wiki:ISO15926Primer_AboutAuthor Primer: About the Author] 
    220 ---- 
     13  * [wiki:ISO15926Primer An Introduction to ISO 15926] 
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