Topic Maps for Cultural Heritage Collections Conal Tuohy Senior Developer New Zealand Electronic Text Centre www.nzetc.org.

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Presentation transcript:

Topic Maps for Cultural Heritage Collections Conal Tuohy Senior Developer New Zealand Electronic Text Centre

NZETC

Website visitor statistics (daily)‏ around 9k visitors around 70k hits around 30k web pages > 1GB traffic

Website content statistics 75k web pages –50% represent digitised documents books, magazines, letters articles, chapters, sections illustrations –The other 50% are about things people, organisations places, ships, literary works even a few animals! 3.5M hyperlinks

Resource-centric vs subject-centric systems “Resource-centric” systems focus narrowly on digital resources –a catalogue of digital items –everything else is peripheral or secondary “Subject-centric” systems can accommodate anything of interest: –information resources –abstract concepts, –or physical things

Information Architecture goals Need to present information in context on every page Need an explicit model of the entire website logical structure. Not just a sitemap, but an ontological model Need to build the model automatically Information resources must be transformed, chunked, and linked together into a navigable web

so how does it work?

Topic Map layer above the digital resources TEI XML documents HTML (including other websites)‏ PDF files JPEG images Topic Map Web page authority database

topic map engine harvesting texts texts topic maps ontology topic map ontology topic map complete topic map of NZETC website name harvester text harvester name lists name lists names topic maps name authority database bibliographies of external sites external site topic maps bibliography harvester

Entity Authority We built an authority file of entities of interest. We've developed a specialised database for this purpose, which we call “Entity Authority Tool Set” (EATS) to manage names and identifiers (a PSI server). In our digitised documents we tag every mention of these entities with their identifier. Our taggers search in EATS for a name, and select from the possible matches.

“authority” topic maps is a a b person is a d text is a about website

Text Encoding for Interchange (TEI) Bibliography Subject classification Textual structure Cross-references External references Commentary etc.

a document's internal structure document topic map

literary works document structure people literary works expressed in wrote a b x y intro expressed in subject heading wrote about

Multiple editions of a single work

mentions, depictions, citations document structure mentioned, depicted and cited things mentioned in cited in mentioned in

Topic map statistics 126k topics 126k occurrences 242k associations 1M roles 115k base names 69k variant names (sort names)‏

Benefits Easier to provide links and contextual information Easy to pull together information from a variety of sources Implicit topics of interest are made explicit Improved our own understanding of our collection Easier to find information on the site Google searches work better

questions? only easy questions please contact me: