1. Semantic Infrastructure for KM 2.0 A new approach to folksonomies and other knowledge representations Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

2. 2 2.0 Themes  “Tags are great because you throw caution to the wind, forget about whittling down everything into a distinct set of categories and instead let folks loose categorizing their own stuff on their own terms." - Matt Haughey - MetaFilter  “It’s MySpace meets YouTube meets Wikipedia meets Google – on steroids.”  “It’s ignorance meets egotism meets bad taste meets mob rule – on steroids.” – The Cult of the Amateur – Andrew Keen  “Things fall apart; the center cannot hold; Mere anarchy is loosed upon the world,… The best lack all conviction, while the worst Are full of passionate intensity.” - The Second Coming – W.B. Yeats

3. 3 Agenda  Introduction  Essentials of Folksonomies – Advantages, Disadvantages, and Dangers of Folksonomies  Improving the Quality of Folksonomies – Facets and Flickr – Del.icio.is – Topics, Popularity and Findability  Semantic Infrastructure Solution – Elements of Semantic Infrastructure / KM 2.0 – Evolving Folksonomies – Ontologies and Natural categories  Conclusion

4. 4 KAPS Group  Knowledge Architecture Professional Services (KAPS)  Consulting, strategy recommendations  Knowledge architecture audits  Partners – Convera, Inxight, FAST, and others  Taxonomies: Enterprise, Marketing, Insurance, etc. – Taxonomy customization, ontology development  Intellectual infrastructure for organizations – Knowledge organization, technology, people and processes – Search, content management, portals, collaboration, knowledge management, e-learning, etc.

5. 5 Essentials of Folksonomies?  Wikipedia: A folksonomy is an Internet-based information retrieval methodology consisting of collaboratively generated, open-ended labels that categorize content such as Web pages, online photographs, and Web links.  A folksonomy is most notably contrasted from a taxonomy – done by users, not professionals,  Example sites – Del.icio.us and Flickr (not really – no feedback)  It is just metadata that users add  Key – social mechanism for seeing other tags

6. 6 Advantages of Folksonomies  Simple (no complex structure to learn) – No need to learn difficult formal classification system  Lower cost of categorization – Distributes cost of tagging over large population  Open ended – can respond quickly to changes  Relevance – User’s own terms  Support serendipitous form of browsing  Easy to tag any object – photo, document, bookmark  Better than no tags at all  Getting people excited about metadata!

7. 7 Disadvantages of Folksonomies - Quality  They don’t work very well for finding  No structure, no conceptual relationships – Flats lists do not a onomy make  Issues of scale – popular tags already showing a million hits  Limited applicability – only useful for non-technical or non- specialist domains  Either personal tags (other’s can’t find) or popularity tags – lose interesting terms (Power law distribution) – Most people can’t tag very well – learned skill  Errors – misspellings, single words or bad compounds, single use or idiosyncratic use

8. 8 Dangers of Folksonomies  Unwisdom of Crowds – “We find that whole communities suddenly fix their minds upon one object, and go mad in its pursuit; that millions of people become simultaneously impressed with one delusion, and run after it, till their attention is caught by some new folly more captivating than the first.” – From witch hunts to tulipomania to stock market crash Extraordinary Popular Delusions and the Madness of Crowds  Tyranny of the majority – Popularity drowns quality – Narrowing of choices, lost content

9. 9 Better Folksonomies:  Will social networking make tags better?  Not so far – example of Del.icio.us – same tags  Quality and Popularity are very different things  Most people don’t tag, don’t re-tag  Study – folksonomies follow NISO guidelines – nouns, etc – but do they actually work – see analysis  Most tags deal with computers and are created by people that love to do this stuff – not regular users and infrequent users – Beware true believers!

10. 10 Flickr Facets

11. 11 Flickr Facets  Basic Facets – over 90% of content – Place – Amsterdam to Beach – 40% – Events, Date, People, Things / Animals, Color  Subject Matter – less than 1%  Works on lower level scales: – Artparade, tourofbritain, stgilesfair, hideoutblockparty (last weeks)  Faceted navigation – extremely powerful, easy to use to find  How to develop automatic facets? – Design facet system – one time cost, some monitoring – Entity Extraction, suggested placement

12. 12 Del.icio.us Tags  Design blog software music tools reference art video programming webdesign web2.0 mac howto linux tutorial web free news photography shopping blogs css imported education travel javascript food games  Development inspiration politics flash apple tips java google osx business windows iphone science productivity books toread helath funny internet wordpress ajax ruby research humor fun technology search opensource  Photoshop media recipes cool work article marketing security mobile jobs rails lifehacks tutorials resources php social download diy ubuntu freeware portfolio photo movies writing graphics youtube audio online

13. 13 Del.icio.us - Topics, not Facets  High level topics - photography, news, education  Get related terms by popularity, not conceptual – Photography Synonyms - photo, photos Related – art, design, images, camera Related Facet – howto, tutorial, photoshop  Popularity is not quality – Dominance of computer terms – Tyranny of the majority – design (1 MIL), interior design – 3,909  Top 25 – same set, slight order shift – social inertia – New terms - important – iphone, ipod,.net, ebooks,facebook – Dropped terms – adult, babes, britney, naked, sex, sexy

14. 14 Del.icio.us - Folksonomy Findability  Too many hits (where have we heard that before?) – Design – 1 Mil, software – 931,259, sex – 129,468  No plurals, stemming (singular preferred) – Folksonomy – 14,073, folksonomies – 3,843, both – 1,891 – Blog-1.7M, blogs – 516,340, Weblog- 155,917, weblogs – 36,434, blogging – 157,922, bloging – 697 – Taxonomy – 9.683, taxonomies – 1,574  Personal tags – cool, fun, funny, etc – Good for social research, not finding documents or sites – How good for personal use? Funny is time dependent

15. 15 Del.icio.us - Improving the Quality  Bundle tags – if used? – Types of relationships – ubuntu – tutorial, howto, reference, tips, install  Ontology Clusters – grow with people and software  Taxonomy Clusters – software – Linux - ubuntu  Add broad general taxonomy of most popular tags – Tags as natural categories – build up and down – Start – evolve a simple 2 level taxonomy – People assign tags to a category, build numbers  Evolve quality of tags and emerging structure of tags – Preferred term = popular (Blog/blogs – Books/book) – Add mechanisms – rank tags, taggers, categories

16. 16 Enterprise Environment – KM 2.0  From internet to intranet – we’ve done this before – Remember early Intranets built on Internet model?  Smaller content repositories, more coherent  More precise targets – specific documents (the official version) not web sites  More formal – from documents to publishing procedures  More control of publishing – corporate policy  More options for tagging – part of CM system, policy, dedicated editor team, reward system

17. 17 Semantic Infrastructure Solution  What won’t work: – Recommendations about count-non-count nouns or singular – plural – Link to online dictionary or Wikipedia – extra work, whole focus is on ease of tagging – any help has to be immediate and integrated - or done by a central group  New Relationship of Center and Crowd – Not top down or bottom up – Interpenetration of opposites  Integrated Solution: Content Structures, People, Technology, Policies and Procedures

18. 18 Semantic Infrastructure: People  KM 2.0 (or 3.0?) – KM always concerned with social aspects of knowledge  New relationship of center and users – more sophisticated support, more freedom, more suggestions, more user input – - New roles – for users (taggers, part of variety of communities – both distributed and central) – New roles for central – create feedback system, tweak the evolution of the system, Develop initial candidates  Communities of Practice – apply to tagging, ranking – Community Maps – formal and informal – Map tags to communities – more useful suggestions – Use tags to uncover communities (see tech SNA)

19. 19 Semantic Infrastructure - Technology  Enterprise Content Management – Place to add metadata – of all kinds, not just keywords – Policy support – important, part of job performance – Add tag clouds to input page – More sophisticated displays Tag clouds mapped to community map Tag clusters, taxonomy location  Semantic Software – Inxight, Teragram etc. – Suggest terms based on text, on tag clouds  Social Networking – add semantics – SNA – apply to people and tags  KM – platforms, COP’s – social tags

20. 20 Semantic Infrastructure: Putting it all together Complexity Theory and Folksonomies: Feedback  Ranking Methods – Explicit – people rank directly Categories, tags, taggers Good tags, best bets for terms or categories? – Implicit – software evaluation, reverse relevance  Ranking Roles – Taggers – everyone (rewards, make it easy and fun) – Meta-taggers – everyone (but levels of meta-taggers) – Editors – tagging system, integration with taxonomy, resolve disputes, Wikipedia model

21. 21 Content Structures – Best of Both Worlds  Start and end with a formal taxonomy / Ontology – Findability vastly superior – Communication with others – share tags – Take advantage of conceptual relationships  Tagging experience – folksonomies plus – Users can type any word – system looks it up – plurals, synonyms, preferred terms, spelling variations – Software suggestions – based on content of bookmark, document and on popular user tags – natural level not top down – New terms flagged and routed to central team  Facets – for both things and documents (faceted taxonomy) – Software suggests facet values, user override – Cognitively simpler task than own value, complex hierarchy

22. 22 Conclusions: Semantic Infrastructure for KM 2.0  Folksonomies can help – but they need help to evolve better quality  Fundamental contradiction of ease of tagging and findability will limit usefulness of Internet folksonomies  Enterprise (Intranets, KM) is where the benefits will happen  Semantic Infrastructure solution (people, policy, technology, semantics) and feedback is best approach  Evolve folksonomies, taxonomies, ontologies – not central, top-down design  Intelligent Design + Darwin = new job – Taxonomy Gods

23. Questions? Tom Reamy tomr@kapsgroup.com KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com