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Knowledge Organization in the Light of Intertextual Semantics A Natural-Language Analysis of Controlled Vocabularies Yves MARCOUX Élias RIZKALLAH GRDS.

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Presentation on theme: "Knowledge Organization in the Light of Intertextual Semantics A Natural-Language Analysis of Controlled Vocabularies Yves MARCOUX Élias RIZKALLAH GRDS."— Presentation transcript:

1 Knowledge Organization in the Light of Intertextual Semantics A Natural-Language Analysis of Controlled Vocabularies Yves MARCOUX Élias RIZKALLAH GRDS – EBSI Université de Montréal

2 ISKO Montréal2 Overview Intertextual semantics (IS) IS's view of controlled vocabulaires (CVs) Example Consequences of IS view Future work

3 ISKO Montréal3 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)

4 ISKO Montréal4 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

5 ISKO Montréal5 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)

6 ISKO Montréal6 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)

7 ISKO Montréal7 Example Facts about some US cities CityPopulation Annual snowfall (inches) Denver850,00023 Rochester240,00088 Palm Spring48,0000

8 ISKO Montréal8 Modeler prepares “peritext” segments Elementtext-beforetext-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"

9 ISKO Montréal9 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.

10 ISKO Montréal10 Example Raw XML document: D F

11 ISKO Montréal11 IS view

12 ISKO Montréal12 IS specification of the model (peritexts prepared by modeler) Elementtext-beforetext-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)."

13 ISKO Montréal13 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

14 ISKO Montréal14 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

15 ISKO Montréal15 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

16 ISKO Montréal16 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

17 ISKO Montréal17 Overview Intertextual semantics (IS) IS's view of controlled vocabulaires (CVs) Example Consequences of IS view Future work

18 ISKO Montréal18 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

19 ISKO Montréal19 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

20 ISKO Montréal20 Overview Intertextual semantics (IS) IS's view of controlled vocabulaires (CVs) Example Consequences of IS view Future work

21 ISKO Montréal21 SKOS example Manmade waterway used by watercraft or for drainage, irrigation, or water power A feature type category for places such as the Erie Canal canals drainage canals hydrographic structures

22 ISKO Montréal22 IS view of same example [… Introductory section for the whole CV: background, purpose, scope, etc. (omitted) …] Section for concept with formal identifier: 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: The official accepted word or expression for referring to this concept is hydrographic structures. End of section

23 ISKO Montréal23 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

24 ISKO Montréal24 Overview Intertextual semantics (IS) IS's view of controlled vocabulaires (CVs) Example Consequences of IS view Future work

25 ISKO Montréal25 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

26 ISKO Montréal26 Extensions If SKOS extensions are used (e.g., custom relationships), IS specification is even more useful, because there are no "standard" interpretation of extensions

27 ISKO Montréal27 Overview Intertextual semantics (IS) IS's view of controlled vocabulaires (CVs) Example Consequences of IS view Future work

28 ISKO Montréal28 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

29 ISKO Montréal29 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

30 Thank you ! Questions ?


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