1. Closing SWOT Analysis Topic Maps Norway / Emnekart 2006 Steve Pepper, Ontopia Coordinator RDF/TM Task Force Convenor SC34/WG 3 “The minority is always right” Henrik Ibsen

2. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 2 The Shape of Topic Maps to Come Issues I’d like to talk about: The range of applications of Topic Maps The untapped power of Topic Maps The state of the ISO Topic Maps standard The relationship to the Semantic Web This presentation is structured as a SWOT analysis

3. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 3 So wot’s a SWOT? WordNet (http://wordnet.princeton.edu/perl/webwn?s=swot) –S: (n) swot, grind, nerd, wonk, dweeb (an insignificant student who is ridiculed as being affected or studying excessively) Stupid Waste of Time Stichting Wetenschappelijke Opleidingen Twente Surface Warfare Over-the-horizon Targeting Student With Outstanding Talent Study Without Teachers Semantic Web Ontology Train Strengths – Weaknesses – Opportunities – Threats

4. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 4 STRENGTHS An elegant, flexible and intuitive model of knowledge Status as an international standard under the democratic control of the member bodies of ISO A passionate and committed community ( 장인 ) No big players pushing their own agenda Ready to go… …and in use today, all around the world –Witness all the case studies today –Norway, at least, has pretty much “crossed the chasm”

5. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 5 Chasm theory Theory of the technology adoption life cycle Developed by Geoffrey Moore in Crossing the chasm The tricky part is moving from early adopter phase to early majority phase In Norway, Topic Maps has pretty much crossed the chasm The “early majority” are listening (ref. today’s presentation on regjeringen.no) Public sector portals are our “beachhead” Now we start to spread out: geographically, and into other verticals and horizontals Source: http://faculty.msb.edu/homak/HomaHelpSite/slides/Crossing%20the%20Chasm%20-%20Presentation.ppt

6. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 6 South Korea Pansori Web Site –Korean folk music Subject of a study submitted to ASIST (American Society for Information Science and Technology)

7. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 7 United States DoE National Nuclear Security Administration The DoE’s Y-12 plant uses Topic Maps for asset management The purpose is to get an overview of –equipment, –processes, –materials required, –parts already built, –etc. Y-12 manufactures nuclear weapons –So I can’t show you a screen shot…

8. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 8 New Zealand Electronic Text Centre Mission: –To create a sustainable, optimally usable, and free online library of New Zealand and Pacific Island texts and materials Site built using Open Source TM4J –Topic Maps for navigation

9. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 9 Taxation: The IRS Tax Map When taxpayers call the IRS for assistance, they don’t always get the right answer. Too much information, changing rapidly. The call centres receive up to 1,000,000 calls a day. The answer? Topic Maps Built by Michel Biezunski and Steve Newcomb Distributed on CD- ROM to every taxpayer in the US

10. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 10 Norway: Kulturnett.no Principal portal of the Ministry of Culture Most advanced of the many Topic Maps- based portals in Norway Currently populating the TM with more and better data… … and building a PSI Server as the foundation for a national knowledge base of Norwegian culture

11. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 11 WEAKNESSES Not enough tools (but those that are, are pretty good) Insufficient penetration of industry (at least in Norway) Meagre toehold in academia (as yet, but TMRA will help) Lack of books on Topic Maps (mine is progressing) No big players to fund the work Too few active participants in standards work…

12. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 12 Standards Work: Current State ISO 13250 Topic Maps: New 7-part version of on its way: –Part 2 (Data Model) undergoing final ballot –Part 3 (XTM 2.0) to go to ballot in June –Parts 1 (Introduction), 4 (Canonicalization), 5 (Reference Model) in the works –Parts 6 (Compact Syntax) and 7 (Graphical Notation) proposed ISO 18048 Topic Maps Query Language (TMQL) –In the works ISO 19756 Topic Maps Constraint Language (TMCL) –Ditto More experts needed: Get signed up with Standards Norway –More information: www.isotopicmaps.org

13. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 13 OPPORTUNITIES Enormous! The market is ready –Witness all the talk about metadata, taxonomies and ontologies –Those that put all their bets on search engines are being disappointed There exists a real need that Topic Maps can meet TODAY –The range of applications is staggering –Potential to become as important as RDBs The topic mapping of the Norwegian National Curriculum is an event of global importance –Please tell the world about it !

14. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 14 THREATS (1 of 2) #1: The mistaken belief that the TAO is all there is Most Topic Maps applications we see today only use a fraction of the real potential; they are “Proto-Topic Maps” –Only use topics, associations, and occurrences –Limited number of topic types, association types, and occurrence types –Scope, reification, and merging yet to be fully exploited You ain’t seen nothin’ yet The biggest limitation is our own imaginations!

15. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 15 Today’s applications (on a logarithmic scale) Formal, standardized language Full topic maps Weakly structured Strongly structured Term Lists (flat) Classification and categorization (hierarchical) Ontologies (associative) Natural language TAO topic maps Thesauri Faceted classification Taxonomies Classification schemes Subject headings Synonym rings Authority Lists Controlled Vocabulary Mind Maps

16. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 16 Scope For handling the (very human) problem of context Currently used mostly when topics have multiple names (to express the contexts in which to use which name) But there are many other, very powerful, and as yet untapped uses: –Multiple world views –Contextual knowledge –Traceable knowledge aggregation –Personalized knowledge One good Norwegian example: –www.hoyre.no uses scope to enable over 400 different web sites (one per local branch) from a single topic map

17. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 17 Reification Provides a “zoom” mechanism for topic maps a)Simple relationships are expressed as associations: ( Henrik Ibsen ) wrote ( An Enemy of the People ) b)To say more about that event, reify the association : ( ( Henrik Ibsen ) wrote ( An Enemy of the People ) ) while living in ( Gossensass ) c)This statement can then itself be reified: ( ( ( Henrik Ibsen ) wrote ( An Enemy of the People ) ) while living in ( Gossensass ) ) according to ( Michael Meyer ) ) ) Using reification, applications can let you “zoom in” from (a) 50,000 feet, to (b) 10,000 feet, to (c) 1,000 feet – and “zoom out” again, as necessary

18. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 18 Merging The most powerful feature of Topic Maps is the ability to automatically merge arbitrary topic maps This makes it possible to –Collate information from disparate sources –Integrate legacy data systems –Aggregate knowledge across different organizations –Realize a Norwegian National Knowledge Base See next slide (from 2001) and http://www.aftenposten.no/meninger/kronikker/article242930.ece Successful merging requires careful use of identifiers –PSIs (Published Subject Indicators) are the key to this –Keep an eye on developments at psi.kulturnett.no – and follow their example

19. Det uunngåelige Ibsen-eksempelet SNL Skien kom- mune Cap Lex NBL Henrik Ibsen Hedda Gabler Skien Et dukkehjem A doll’s house skrev født i skrev “virkelighet” emnekartinformasjon kunnskap andre emnekart flettes inn... Ibsen- senter Et dukkehjem Helmer Dr. Rank Fru Linde Krogstad Nora

20. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 20 THREATS (2 of 2) #2 The widespread belief that RDF/OWL is a competitor –RDF/OWL are languages of the Semantic Web –Some people fear they might be betting on the wrong horse Semantic Web gets much more of the limelight –Partly because the W3C can bask in the glamour of the Web –Partly because RDF and OWL appeal more to academics Why the perceived competition with Topic Maps? –Partly because RDF/OWL and TMs have a number of similarities –Partly because they stem from rival organizations (W3C and ISO) –Partly because there are a few bigots (in each camp) –Mostly because people do not fully understand the difference

21. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 21 Yes, they are similar in many ways Both “extend” XML into the realm of semantics Both allow assertions to be made about subjects in the outside world Both define abstract, associative (graph-based) models Both are intensely concerned with “identity” Both allow some measure of inferencing or reasoning Both have XML-based interchange syntaxes Both have constraint languages and query languages und so weiter But they are also different in some crucial respects…

22. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 22 The Most Crucial Differences RDF/OWL is for machines; Topic Maps is for humans. RDF/OWL is optimized for inferencing; Topic Maps is optimized for findability. RDF/OWL is based on formal logic; Topic Maps is not based on formal logic. RDF/OWL is to mathematics as Topic Maps is to language.

23. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 23 Who can tell me what this is? Is it an H or an A? Human or Agent? T E C T H H H H A A A A

24. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 24 Different capabilities RDF/OWL, to support logic-based inferencing, cannot afford to be “fuzzy”; Topic Maps, because it is for humans, has to support fuzziness. OWL ontologies tend to be very stringent and complex; Topic Maps ontologies tend to be simpler and less formal. OWL has properties for things that Topic Maps doesn’t need; Topic Maps has features that would be too complex for OWL. So you need to decide what it is you really need…

25. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 25 RDF or Topic Maps: Some Rules of Thumb Do you simply want to encode document metadata? –RDF is ideal and you won’t need OWL Do you want to achieve subject-based classification of content? –Topic Maps provides the best combination of flexibility and user-friendliness Do you want both metadata and subject-based classification? –Go straight for Topic Maps, because it also supports metadata Do you want to develop agent-based applications? –Use RDF/OWL; if you already have Topic Maps, you’re already half way there Whatever you choose, know that you can move your data between Topic Maps and RDF, thanks to the RDFTM work…

26. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 26 The RDF/TM task force A W3C task force supported by the ISO Topic Maps group –Chartered to address RDF/Topic Maps interoperability –Working within the Semantic Web Activity of the W3C http://www.w3.org/2001/sw/BestPractices/RDFTM/ “Survey of RDF/Topic Maps Interoperability Proposals” published 3’05 http://www.w3.org/TR/rdftm-survey/ “Guidelines for RDF/Topic Maps Interoperability” at draft stage http://www.ontopia.net/work/guidelines.html Focus on data interoperability: “The primary goal of these Guidelines is to enable data to be translated from one form to the other without unacceptable loss of information or corruption of the semantics. Further goals are to be able to query the results of a translation in terms of the target model and to share vocabularies across the two paradigms.”

27. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 27 SWOT Summary We have a lot of strengths. We still have some weaknesses. The opportunities are immense. The threats are mostly in our own minds. As practitioners of Topic Maps, we are still a minority, but we have the future on our side Which brings us back to Dr. Stockmann…

28. © 2006 Ontopia AS – www.ontopia.net Topic Maps Norway / Emnekart 2006 Slide 28 Emnekart 2006 “The minority is always right... I think of the few individuals among us who have made all the new, germinating truths their own. These men stand, as it were, at the outposts, so far in advance that the compact majority has not yet reached them–and there they fight for truths that are too lately borne into the world's consciousness to have won over the majority.” Henrik Ibsen An Enemy of the People 1882 “The minority is always right... I think of the few individuals among us who have made all the new, germinating truths their own. These men stand, as it were, at the outposts, so far in advance that the compact majority has not yet reached them–and there they fight for truths that are too lately borne into the world's consciousness to have won over the majority.” Henrik Ibsen An Enemy of the People 1882 The minority is always right… “The minority is alway right” Dr. Stockmann An Enemy of the People Henrik Ibsen William Archer Dr. Newcomb Vanity Fair William Makepeace Thackeray Colonel Newcome The Newcomes

29. En folkefiende Dr. Steven R. Newcomb First edition* (1882) of Henrik Ibsen’s An Enemy of the People, presented to the Inventor of Topic Maps, * IBSEN, HENRIK: En folkefiende. Kbh. 1882. (4) + 219 + (1) s. Orig., dek. helshirtingbd., rødt. Helt gullsn. Og for øvrig så mener jeg at Norges nasjonale kunnskapsbase må baseres på emnekart! Topic Maps Norway / Emnekart 2006