[sc34wg3] New attempt at TM standards guide

Lars Marius Garshol sc34wg3@isotopicmaps.org
02 Jun 2002 21:25:02 +0200


--=-=-=


I've now written a new draft of the guide to the topic map standards.
I think (hope) that it is more understandable than the previous
versions, but feedback is still very much welcome.

-- 
Lars Marius Garshol, Ontopian         <URL: http://www.ontopia.net >
ISO SC34/WG3, OASIS GeoLang TC        <URL: http://www.garshol.priv.no >

--=-=-=
Content-Type: text/html
Content-Disposition: attachment; filename=roadmap.html

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN">
<html>
<head>
<title>Guide to the topic map standards</title>

<style type="text/css">
th {
  text-align: left;
  vertical-align: top;
}

h1, h2, h3, h4 {
  font-family: Verdana, Helvetica, sans-serif;
}

body {
  margin-left: 10%;
  margin-right: 10%;
  margin-top: 48pt;
}

dt {
  font-weight: bold;
}

blockquote {
  color: #555;
}
</style>
</head>
<body>

<h1>Guide to the topic map standards</h1>

<p>
This document describes what is happening with topic maps
standardization right now. It describes the current activities, the
problems they are intended to solve, and how those problems came to
be. (In the opposite order, for ease of understanding.)
</p>

<h2>The past</h2>

<p>
The first substantial result of the topic maps effort was ISO
13250:2000, an ISO standard that defined a syntax for topic maps.
This syntax was an SGML DTD, which used the ISO 10744 HyTime standard
for linking and addressing, and so the syntax is known as HyTM (short
for HyTime Topic Maps).
</p>

<p>
HyTM is not an XML syntax, is not a fixed DTD, and does not use URIs
to refer to information resources. The result was that each topic map
software developer made <a
href="http://www.cogx.com/xslt4tm2xtm.html">its own HyTM version</a>,
derived from the standard HyTM DTD.  These things were seen as
problems at the time, and in order to <a
href="http://www.topicmaps.org/xtm/1.0/index.html#goals">adapt topic
maps to the web</a> the TopicMaps.Org organization was set up to
create a new topic map syntax based on XML and URIs.  The syntax
TopicMaps.Org created is known as XTM (XML Topic Maps), and solves the
problems with HyTM.  Today, the HyTM syntax is rarely used, as most
people use XTM.
</p>

<p>
In October 2001 the XTM DTD <a
href="http://www.y12.doe.gov/sgml/sc34/document/0260.htm">was accepted
into ISO 13250</a>, and so ISO 13250 now contains two syntaxes: HyTM
and XTM.
</p>

<h2>The present</h2>

<p>
Some problems remain, however. The current ISO 13250 defines two
interchange syntaxes, but does not explain how they relate to one
another. As the two syntaxes are subtly different, this is a problem,
as implementors are likely to map between the syntaxes in different
ways, which means that the same topic map may not be treated the same
way by different software.
</p>

<p>
Another problem is that both syntax specifications in the current ISO
13250 are quite informal. For the most part this is not a problem, but
in a number of more subtle situations developers have interpreted the
specification text differently, and this causes interoperability
problems. If different implementations interpret the same topic map
differently topic map applications may only work with a single
implementation, which defeats the purpose of having a standard in the
first place.
</p>

<p>
ISO SC34 has also resolved to create two new topic map standards:
</p>

<ul>
<li>ISO 18048: Topic Maps Query Language (TMQL), a query language for
topic maps. This language is intended to be a kind of SQL (or XML
Query) for topic maps, and will greatly simplify topic map application
development by making it much easier to extract information from topic
maps. A <a
href="http://www.y12.doe.gov/sgml/sc34/document/0249.htm">requirements
specification</a> has been created.</li>

<li>ISO 19756: Topic Maps Constraint Language (TMCL), a schema or
constraint language for topic maps. Using TMCL one can write schemas
for topic maps that constrain what is allowed to say in the topic map,
such as "a person must be born in a place," "a person must have at
least one name," and so on. A <a
href="http://www.y12.doe.gov/sgml/sc34/document/0226.htm">requirements
draft</a> has been created.</li>
</ul>

<p>
Both of these standards need to explain how the constructs in them are
evaluated, but the existing ISO 13250 does not provide a suitable
basis for such definitions. For example, when TMQL defines the "find
all base names of topic X in scope Y"-operator it needs to explain
carefully and formally what that operator does. This could be done in
terms of the XTM syntax, but it would then be difficult to see how to
apply it to the HyTM syntax. The explanation would also become very
involved, as XTM provides many different ways to express the same
thing, and merging must be performed before queries can be done.
</p>

<p>
So while the community is generally satisfied with the two syntaxes,
their specifications are in need of improvement on three counts:
</p>

<ul>
<li>Not all developers interpret them the same way.</li>

<li>They need to clearly relate the two syntaxes to one another.</li>

<li>They do not provide suitable foundations for the TMQL and TMCL
standards.</li>
</ul>

<p>
ISO SC34's solution to this is the topic map data model work that was
started in May 2001, and is now beginning to produce tangible results,
in the form of
<a
href="http://www.y12.doe.gov/sgml/sc34/document/0298R1.htm">N0298R1</a>
and <a
href="http://www.y12.doe.gov/sgml/sc34/document/0299.htm">N0299</a>. 
</p>

<h2>The future</h2>

<p>
ISO SC34's current plan is to revise ISO 13250 into a multi-part
standard. A key part of this new edition of the standard will be what
is known as the Standard Application Model (SAM), a formal data model
for topic maps. This model will be based on the same formalism as the
<a href="http://www.w3.org/TR/xml-infoset/">XML Information Set</a>.
This model will define the allowed structure of topic maps, as well as
how to perform key operations such as merging and duplicate removal.
The SAM will allow SC34 to solve all the three problems described
above. 
</p>

<p>
The problem with the interpretation of the syntax specifications will
be solved by writing new syntax specifications based on the SAM.  The
new versions of the syntax specifications will describe how to build
an instance of the SAM model from a document in a given syntax.  This
will be done very formally, in a way that leaves much less room for
interpretation. (The syntaxes themselves will stay the same. The only
thing that will change is that their interpretation will become much
clearer. DTDs will still be used to define the syntaxes; SAM is only
used to define their interpretation.)
</p>

<p>
Rewriting the syntax specifications in the way described above will
also solve the problem of how to relate the XTM syntax to HyTM, and
vice versa. The SAM will now serve as a common point of reference for
the two syntaxes, and comparison of parts of the syntaxes can be done
by comparing the SAM models they create. This solution will continue
to work even if new topic map syntaxes are introduced, and it provides
a way to relate non-standard topic map syntaxes (such as <a
href="http://www.ontopia.net/download/ltm.html">LTM</a> and <a
href="http://topicmaps.bond.edu.au/astma/">AsTMa</a>) to the standard
ones.
</p>

<p>
The SAM provides a much more suitble basis for TMQL and TMCL, since it
unites the different syntaxes and provides a much more convenient
basis for operator definitions. Defined using the SAM the "find all
base names of topic X in scope Y"-operator would become something like
"traverse the [base names] property of topic item X and return all
base name items whose [scope] property contains topic item Y". (In
practice the definition is likely to be somewhat different, but this
is the basic idea.) TMQL and TMCL will then also be applicable to any
topic map syntax that has a mapping to the SAM model.
</p>

<h3>Canonicalization</h3>

<p>
Although the new specifications will be clearer than the previous
versions there will still be necessary to verify that implementations
actually do conform to the specifications. This is best done by
creating a conformance test suite, much like those already created for
<a
href="http://www.oasis-open.org/committees/xml-conformance/xml-test-suite.shtml">XML</a>
and <a href="http://www.oasis-open.org/committees/xslt/">XSLT</a>. It
is easy to create a set of topic map documents in the XTM and HyTM
syntaxes, but harder to define what their correct interpretation is.
</p>

<p>
One way to do it is to create a so-called canonical syntax. In this
syntax, every logically equivalent topic map would be represented as
exactly the same sequence of bytes. This means that in order to see
how a topic map engine interprets an XTM file, one could import that
file into the engine, and then export it using the canonical syntax.
The test suite could then consist of a set of XTM and HyTM documents
with their corresponding canonical representations, and conformance
testing could be automated.
</p>

<p>
The new ISO 13250 standard is going to contain just such a Canonical
Topic Map syntax. It is expected that a conformance test suite will be
developed, either within OASIS or within ISO, once the necessary
infrastructure is in place. There also exists <a
href="http://www.ontopia.net/topicmaps/materials/cxtm.html">an early
proposal</a> for such a canonical syntax.
</p>

<h3>The Reference Model</h3>

<p>
The new ISO 13250 will also include a model known as the Reference
Model, which is a more abstract graph model of topic maps. In this
model, names and occurrence resources turn into topics, and they are
related to their topics using an association-like structure. The
result is a model that uses fewer constructs than the SAM, and which
can be extended without changing the metamodel.
</p>

<p>
The Reference Model provides a mechanism for explaining the
relationships between different knowledge representations, such as
topic maps, RDF, and KIF. This will make it easier for topic maps to
interoperate with these other knowledge representations.
</p>

<p>
It is planned that the SAM part of the standard will include a
normative mapping of the SAM to the Reference Model. The TMQL and TMCL
standards will thus relate to the Reference Model through the SAM.
Obviously, it is very important that the SAM and the RM are
consistent, and much work will go into ensuring that this is the case.
</p>

<h3>Overview</h3>

<p>
Below is shown a conceptual diagram of the relationships between the
different parts of the new ISO 13250, as well as TMQL and TMCL:
</p>

<div align=center>
<img src="roadmap.png" alt="[Diagram of new TM standards]">
</div>

<p>
The parts of the new ISO 13250 standard will be:
</p>

<ul>
<li><b>Part 0</b>: A guide to the structure of the standard
                   (Lars Marius Garshol)
<li><b>Part X</b>: The Standard Application Model
                   (Lars Marius Garshol and Graham Moore)
<li><b>Part X</b>: The Reference Model
                   (Steven R. Newcomb and Michel Biezunski)
<li><b>Part X</b>: The XML Topic Maps syntax (XTM)
                   (Lars Marius Garshol and Graham Moore)
<li><b>Part X</b>: The HyTime Topic Maps syntax (HyTM)
                   (Lars Marius Garshol and Graham Moore)
<li><b>Part X</b>: Canonicalization of topic maps
                   (Currently unknown)
</ul>

<h2>Meanwhile, at OASIS...</h2>

<p>
In order for topic maps created by different parties to merge
correctly it is crucial that these parties use the same identifiers
for their topics. This is unlikely to happen by itself, however, and
therefore three Technical Committees (TCs) have been formed within
<a href="http://www.oasis-open.org">OASIS</a>, in order to work on
something called <dfn>published subjects</dfn>. These are URIs and
descriptions for concepts considered important by some publisher.
</p>

<p>
The three OASIS TCs are:
</p>

<dl>
<dt><a href="http://www.oasis-open.org/committees/tm-pubsubj/">Published
subjects TC</a></dt>
<dd>Creates guidelines and recommendations for how to create, publish,
and maintain published subject sets.</dd>

<dt><a href="http://www.oasis-open.org/committees/xmlvoc/">XML
Vocabulary TC</a></dt>
<dd>Creates a vocabulary (or ontology) consisting of published
subjects for the domain of core XML standards and technologies.</dd>

<dt><a href="http://www.oasis-open.org/committees/geolang/">Geography
and languages TC</a></dt>
<dd>Creates published subject sets for geographical and linguistic
concepts. These published subject sets will be based on existing code
sets such as ISO 639 and ISO 3166.</dd>
</dl>

<p>
The published subjects activity within OASIS will layer on top of
specifications produced by ISO SC34, and will not in any way interfere
with what SC34 is doing. 
</p>

</body>
</html>
--=-=-=
Content-Type: image/png
Content-Disposition: attachment; filename=roadmap.png
Content-Transfer-Encoding: base64
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--=-=-=--