[sc34wg3] Occurrences in the data model

Patrick Durusau sc34wg3@isotopicmaps.org
Mon, 22 Dec 2003 07:20:32 -0500


Greetings,

Working my way through the data model and while using an example with
XTM syntax, my questions (see below) are about the data model and not
the actual syntax below.

 From ned1.xtm, a topic map for astronomy, I drew the following bits of
XTM syntax:

(http://www.astro.caltech.edu/~aam/science/topicmaps/ned1.xtm):

****
<topic id="description">
	<subjectIdentity>
		<subjectIndicatorRef 
xlink:href="http://psi.ontopia.net/xtm/occurrence-type/description"/>
	</subjectIdentity>
	<baseName>
		<baseNameString>description</baseNameString>
	</baseName>
</topic>
****

then:

****
<topic id="ra">
	<instanceOf><topicRef xlink:href="#description"/></instanceOf>
	<baseName>
		<baseNameString>ra</baseNameString>
	</baseName>
</topic>
****
(Note: The topic "ra" represents Right Ascension, a coordinate used
with Declination to define the location of a celestial object. see,
http://scienceworld.wolfram.com/astronomy/RightAscension.html and
related entries for details.)


then:

****
<topic id="*2MASXiJ0427573+261918">
	<instanceOf><topicRef xlink:href="#object"/></instanceOf>
	<baseName>
		<baseNameString>*2MASXiJ0427573+261918</baseNameString>
	</baseName>

<snip>

	<occurrence>
	<instanceOf><topicRef xlink:href="#ra"/></instanceOf>
	<resourceData>04h27m57.3s
</resourceData>
	</occurrence>
****

So, there is an occurrence with resource data, of a topic (ra) that is
an instance-of the topic (description).

In data model terms (checking my understanding here so please correct
if necessary) the occurrence has the values marked by ()'s:

1. [value]: A string or null. (04h27m57.3s)

2. [resource]: A locator item or null. (null)

3. [scope]: A set of topic items. (unconstrained, inferred from the
    definition of scope in 5.4.4)

4. [type]: A topic item, or null. (<topicRef xlink:href="#ra"/>)

5. [reifier]: A topic item, or null. (null)

6. [source locators]: A set of locator items. (none)

7. [parent]: An information item. (<topic
    id="*2MASXiJ0427573+261918">) (computed value)

The equality rule applicable to occurrences is:

Equality rule: Occurrence items are equal if the values of their
[value], [resource], [scope], [type], and [parent] properties are
equal.

Assuming the foregoing analysis is correct, then merger of another
occurrence item would not occur:

1. If the second occurrence (same parent) used a resource (#2) to point 
at a resource with the same value;

2. If the second occurrence (same parent) had the same value (#1) but a 
different scope (#3);

3. If the second occurrence (same parent) used a resource (#2) and had a 
different scope (#3);

4. If the second occurrence had a different parent (#7) but all other
    values were identical.

I don't find 1-3 (inclusive) troubling but the failure on #4 seems
problematic.

To compell merging of occurrences within a topic to eliminate
duplicate entries makes sense, although one assumes it will be a
limited number of cases where duplicates will really be a problem.

The more interesting case arises with location information,
such as Right Ascension/Declination in astronomy, longitude and
latitude in GIS systems (and targeting systems), where finding all the
occurrences that share a point on a particular axis could well be important.

Note that I don't think making coordinates topics would solve the
problem as given the fine grained nature of coordinate systems there
would be a proliferation of topics for any relatively sophisticated
system of coordinates. Not to mention that coordinates are commonly
thought to be characteristics of objects/locations and not subjects in
their own right.

Is there some conceptual reason for this treatment of occurrences in
the data model?

Hope everyone is having a great day!

Patrick

-- 
Patrick Durusau
Director of Research and Development
Society of Biblical Literature
Patrick.Durusau@sbl-site.org
Chair, V1 - Text Processing: Office and Publishing Systems Interface
Co-Editor, ISO 13250, Topic Maps -- Reference Model

Topic Maps: Human, not artificial, intelligence at work!