Yves MARCOUX Élias RIZKALLAH GRDS – EBSI Université de Montréal

Knowledge Organization in the Light of Intertextual Semantics

A Natural-Language Analysis of Controlled Vocabularies

Yves MARCOUXÉlias RIZKALLAH

GRDS – EBSIUniversité de Montréal

ISKO 2008 - Montréal 2

Overview

• Intertextual semantics (IS)

• IS's view of controlled vocabulaires (CVs)

• Example

• Consequences of IS view

• Future work


Intertextual semantics (IS)

• A way to envision how meaning is conveyed by information-bearing objects

• Based on natural language (NL)

• Not a semantics for natural language

• Rather a natural-language semantics for artificial information-bearing objects

• Goal: design "better" information-bearing objects (more effective and usable)


Scope of IS reflection

• Information-bearing objects– Primarily structured documents (e.g., XML)– Any data structure designed to hold

information in an information system• Ex.: database table / record / field

• Communication of meaning to human persons interacting with the object through any kind of interface


IS – Background (1/2)

• Introduced at Extreme Markup Languages (EML) 2006– valid XML documents only– modeler-author communication– further development (EML 2007)

• Applied to classical data structure for information exchange (SIGDOC 2007)


IS – Background (2/2)

• One in a series of semiotics-based approaches to improve systems design– Knuth (1984), De Souza (2005)

• One in a series of semantic frameworks for structured documents (XML, etc.)– Sperberg-McQueen et al. (2000), Renear et

al. (2002), Wrightson (2005)


Example

Facts about some US cities

City PopulationAnnual snowfall (inches)

Denver 850,000 23

Rochester 240,000 88

Palm Spring 48,000 0


Modeler prepares “peritext” segments

Element text-before text-after

facts-about-US-cities"Here are facts about some US cities."

empty

city " The city " "."

name "named " empty

population" has a population of "

" inhabitants "

annual-snowfall-in-inches

" and an annual snowfall of "

" inches"


Possible “semantic” (or IS) view for authors

Here are facts about some US cities. The city named Denver has a population of 850,000 inhabitants and an annual snowfall of 23 inches. The city named Rochester has a population of 240,000 inhabitants and an annual snowfall of 88 inches. The city named Palm Spring has a population of 48,000 inhabitants and an annual snowfall of 0 inches.


Example

• Raw XML document:

<billing> <amount-burial>1205.47</amount-burial> <payable-burial>D</payable-burial> <amount-cremation>788.00</amount-cremation> <payable-cremation>F</payable-cremation></billing>


IS view


IS specification of the model(peritexts prepared by modeler)

Element text-before text-after

billing "This section gives the billing information for this order. "

" End of billing information section."

amount-burial "Amount charged for the burial service: "

" canadian dollars; "

payable-burial "this amount is payable by: "" (D = Funeral director; F = Family)."

amount-cremation

"Amount charged for the cremation service: "

" canadian dollars; "

payable-cremation

"this amount is payable by: "" (D = Funeral director; F = Family)."


IS – Key ideas

• The semantic (IS) view is the reference interpretation and should convey, in NL, to humans, all the meaning intended / expected by the modeler

• The semantic (IS) view can (and should) contain hyperlinks to material not already known by target community of users, but necessary to make sense of the data structure


IS – Hypothesis (ISH-1)

• The IS view of a document is one of the most workable incarnation of its meaning– Wittgensteinian position

• The (human) task of interpreting the IS view of a document is representative of the task of "understanding" the document


IS – Consequences on design

• An intricate structure of the prose in the IS view, or a high number of hyperlink traversals indicate that the document (or data structure) is hard to understand– Gaps imply incomprehensible document!

• Design goals for modelers are thus:– Prose as simple as possible (but no more)– Low number of hyperlink traversals


IS – Notes

• The network of resources anchored (via hyperlinks) in the semantic view suggests an actual interpretation (sense-making) path, but does not impose it

• Any specific reading of a document yields more information than the IS view, but the IS view is considered a minimum for all readings, and thus, serves as a reference


Overview



• Example


• Future work


Controlled vocabularies (CVs)

• Same scope as SKOS concept schemes:– Thesauri, classification schemes, subject

heading systems, subject indexes, taxonomies

• CVs are data structures– Designed by information professionnals– Populated by corpus analysts ("authors")– Used by document analysts to index

documents, and users to find documents


CVs in IS

• SKOS allows CVs to be expressed as XML documents– Eases the thought experiment of applying IS

• A CV can be expressed as a single XML document– Not as reductive as it sounds...– Example will concentrate on designer-author

communication


Overview



• Example


• Future work


SKOS example<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:skos="http://www.w3.org/2004/02/skos/core#"> <skos:Concept rdf:about="http://www.my.com/#canals"> <skos:definition>Manmade waterway used by watercraft or for drainage, irrigation, or water power</skos:definition> <skos:scopeNote>A feature type category for places such as the Erie Canal</skos:scopeNote> <skos:prefLabel>canals</skos:prefLabel> <skos:altLabel>drainage canals</skos:altLabel> <skos:broader rdf:resource= "http://www.my.com/#hydrographic%20structures"/> </skos:Concept> <skos:Concept rdf:about= "http://www.my.com/#hydrographic%20structures"> <skos:prefLabel>hydrographic structures</skos:prefLabel> </skos:Concept></rdf:RDF>


IS view of same example

[… Introductory section for the whole CV: background, purpose, scope, etc. (omitted) …]

Section for concept with formal identifier: http://www.my.com/#canals This concept can be defined as Manmade waterway used by watercraft or for drainage, irrigation, or water power. It can be used as A feature type category for places such as the Erie Canal. The official accepted word or expression for referring to this concept is canals. Another word or expression commonly used to refer to this concept is drainage canals. canals are special cases of hydrographic structures.End of section

Section for concept with formal identifier: http://www.my.com/#hydrographic%20structures The official accepted word or expression for referring to this concept is hydrographic structures.End of section


IS specification

• Table of text-before and text-after for all SKOS elements and attributes

• Specified by designer (modeler) of CV before it is populated


Overview



• Example


• Future work


IS specification

• Makes explicit the often hidden complexity of the CV model for users

• Is an opportunity for specifying extra semantics of the CV model, over and above SKOS semantics– Ex.: "is-a" instead of just "broader term"

• Cleary shows the cognitive price of using artificial codes, e.g., numbers instead of names to identify concepts


Extensions

• If SKOS extensions are used (e.g., custom relationships), IS specification is even more useful, because there are no "standard" interpretation of extensions


Overview



• Example


• Future work


Future work (1/2)

• Development of IS framework– From intertexts to geometrized text– Application to interface / interaction design

• Application to CVs– IS analysis of other uses of CVs, e.g., for

indexing and searching– Work out an IS specification for a real CV and

experiment


Future work (2/2)

• Integration of IS in SKOS – IS-peritexts are not by refinement of SKOS

documentation properties– Rather domain-specific XML elements and/or

attributes

Thank you !

Questions ?

[email protected]

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Yves MARCOUX Élias RIZKALLAH GRDS – EBSI Université de Montréal