1	The Myth of Topic Maps: What Works and What Doesn’t?
2	Innovations in search? How about, “Innovations in understanding?”
3	Semantic Web?
4	Price? 1.98? Price of what? Newspaper? Stadium seat? Article? $, , Ÿ, £? Wholesale? Retail? Sale? How?
5	Meaning and retrieval start with a knowledge organization system (KOS) Uncontrolled list Name authority file Synonym set/ring Controlled vocabulary Taxonomy Thesaurus
6	Meta Data Data about data Information about information Natural Added
7	Data about ‘stuff’ - like what? Author name Date of creation Language used in the creation Title of the creation Subject of the creation Keywords...
8	Narrowing the focus Keywords (aka subject headings, index terms, identifiers, etc.) are one type of meta data.
9	For example... A bibliographic database record usually includes information such as author, title, language, date of creation, and subject area. So does a traditional library card catalog
10	But did you think about… The legend on a street map? The yellow pages in a telephone book? The aisle signs in a supermarket?
11	Meaning of meta data Meta data is information that points to an answer or a solution Meta data makes statements about an information resource or object
12	Sidebar - meta data or metadata? ‘Metadata’ is “a word coined by Jack E. Myers to represent current and future lines of products implementing the concepts of his MetaModel, and also to designate his company, The Metadata Company, that would develop and market those products.”
13	Metadataä A term not used prior to 1969 Used first in 1973 Registered U.S. Trademark (in 1986), owned by Jack Myers Metadataä granted incontestable status in 1991 Designed to be a term with no particular meaning
14	Meta Data
15	Meta data as indexing language List of words Synonyms Taxonomy Thesaurus
16	Taxonomy / thesaurus Main Term (MT) Top Term (TT) Broader Terms (BT) Narrower Terms (NT) Related Terms (RT) See also (SA) Scope Note (SN) History (H) NonPreferred Term (NP) Used for (UF), See (S)
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19	Taxonomy, Thesaurus, & Ontology Taxonomies and thesauri are not ontologies They are entities Ontology – science of describing kinds of entities “an explicit and formal specification of a conceptualization”
20	Ontology From philosophy – the science of describing Kinds of entities in the world How they are related
21	OWL Web Ontology Language W3C Recommendation 10 February 2004 http://www.w3.org/TR/2004/Rec-owl-guide-20040210/ http://www.w3.org/TR/2004/Rec-owl-ref-20040210/ http://www.w3.org/TR/2004/Rec-webont-req-20040210/
22	OWL OWL output Provides semantic meaning to these kinds of entities Web resource Accessible to automated processes
23	OWL Ontology May include Classes Properties Instances Capture semantics Multiple, distributed, related ontology schema Normative OWL exchange syntax RDF/XML Resource Description Framework/Extensible Markup Language
24	Structure of controlled vocabularies List of words Synonyms Taxonomy Thesaurus
25	"<TermInfo" <TermInfo> <T>Agrotechnology</T> <BT>Biotechnology</BT> <NT>Animal management technologies</NT> <NT>Controlled environment agriculture</NT> <NT>Genetically modified crops</NT> </TermInfo> Source: www.DataHarmony.com
26	"<TermInfo" <TermInfo> <T>Agrotechnology</T> <BT>Biotechnology</BT> <NT>Animal management technologies</NT> <NT>Controlled environment agriculture</NT> <NT>Genetically modified crops</NT> <RT>Agricultural science</RT> <RT>Food technology</RT> <UF>Plant engineering</UF> <Scope></Scope> <Editorial_Note></Editorial_Note> <Facet></Facet> <History></History> </TermInfo> Source: www.DataHarmony.com
27	"</PreferredTerm" </PreferredTerm> <PreferredTerm rdf:ID="T131"> <rdfs:label xml:lang="en">Agrotechnology</rdfs:label> <BroaderTerm rdf:resource="#T603" newsindexer:alpha="Biotechnology"/> <NarrowerTerm rdf:resource="#T252" newsindexer:alpha="Animal management technologies"/> <NarrowerTerm rdf:resource="#T1221" newsindexer:alpha="Controlled environment agriculture"/> <NarrowerTerm rdf:resource="#T2166" newsindexer:alpha="Genetically modified crops"/> <Related_Term rdf:resource="#T127" newsindexer:alpha="Agricultural science"/> <Related_Term rdf:resource="#T2020" newsindexer:alpha="Food technology"/> <Non-Preferred_Term rdf:resource="#T3898" newsindexer:alpha="Plant engineering"/> </PreferredTerm> Source: www.DataHarmony.com
28	Statements about what?
29	Topic Maps ISO standard - ISO 13250:2002 For merging back-of-the-book indexes Collection of structured markup Describing KOS Associating KOS with information resources (objects) Separation of KOS from objects
30	Topic Maps Three main concepts Names of things Occurrences of the named things Associations between names Three additional constructs Identity Facet Scope
31	Topic map
32	Topic with occurrence
33	Topics, associations, occurrences
34	Problems with Semantic Web Complexity Lack of tools Lack of skills Limited resources Gaming the system The syllogism trap KOS biases Lack of agreement Lack of interest Good enough Topic Maps vs. OWL
35	Lack of agreement “Symbionese Liberation Army credited with offing an SUV” About - ‘revolutionaries’ or ‘freedom fighters’ About - ‘revolutions’ or ‘freedom movements’ “Symbionese Liberation Army accused of firebombing SUV” About - ‘terrorists’ or ‘anarchists’ About - ‘terrorism’ or ‘anarchy’
36	The syllogism trap Humans are mortal Greeks are human Therefore, Greeks are mortal
37	Topic Maps vs. OWL TMCL Topic maps XTM, HyTM, LTM ISO OWL RDF Schema RDF RDF/XML, N3 SOAP, WSDL W3C
38	Next best thing(s) Full-text and applied indexing languages Social book-marking Make do
39	Social book-marking del.icio.us www.citeulike.org www.firststopwebsearch.com www.flickr.com www.furl.net www.jeteye.com www.zniff.com
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41	Full-text search and applied indexing languages Full-text search engines - getting better Thesauri applied using machine automated indexing - easier, faster, cheaper Taxonomic navigation Faceted navigation Table of contents drilldown - taxonomy views Query disambiguation
42	Full-text search and applied indexing languages Long history Many richly developed thesauri with legs Tools that work Large body of professionals Almost as rich
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45	Organizational objectives ASIS&T -- virtual library Subject matter ASRT -- internal information control Organization chart Naval Postgrad -- Homeland security degree Curriculum outline SLA -- Web content Public Web navigation
46	SLA website and thesaurus
47	SLA search
48	Naval Postgraduate School’s Homeland Security Taxonomy
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51	Myth of topic maps Not a myth They do work Limited adoption Narrow, tightly defined niches
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53	Resources www.accessinn.com www.dataharmony.com www.iso.org www.ontopia.com Lars Marius Garshol, “Metadata? Thesaurui? Taxonomies? Topic Maps!” Steve Pepper, “The TAO of Topic Maps” www.topicmaps.org
54	Resources Cory Doctorow, “Metacrap: Putting the Torch to Seven Straw-men of the Meta-utopia,” http://www.well.com/~doctorow/metacrap.htm Russell Glass, “Is Anyone Going to Tag all of this Stuff?,” http://zoominfo.blogs.com/soughtafter/2005/03/semantic_web_is.html Clay Shirky, “The Semantic Web, Syllogism, and Worldview,” www.shirky.com/writings/semantic_sllogism.html Pete Norvig, “Semantic Web Ontologies: What Works and What Doesn’t,” www.alwayson-network.com/comments.php?id=P7480_0_3_0_C