1. Mashup Mindset Moving Mashups to Next Level Tom Reamy Chief Knowledge Architect KAPS Group Knowledge Architecture Professional Services http://www.kapsgroup.com

2. 2 Agenda  Introduction  Mashups: Essential Features & Current State – What’s new, what’s not  Mashups in Context: Creating Value – Content Aggregation, Facets, Business Value  Moving Mashups to the Next Level – Semantic Infrastructure and Complexity Theory  Conclusion

3. 3 KAPS Group: General  Knowledge Architecture Professional Services  Virtual Company: Network of consultants – 12-15 – Partners – Convera, Inxight, FAST, etc.  Articles and Presentations: Knowledge Architecture, Taxonomy Boot Camp, Enterprise Search, Complexity Theory, Intranets  Consulting, Strategy, Knowledge architecture audit  Taxonomies: Enterprise, Marketing, Insurance, etc.  Services: – Taxonomy development, consulting, customization – Technology Consulting – Search, CMS, Portals, etc. – Metadata standards and implementation – Knowledge Management: Collaboration, Expertise, e-learning – Information Architecture, Web Development

4. 4 Essential Features of Mashups What is Mashup?  “A mashup is a website or application that uses content from more than one source to create a completely new service.”  Uses a public interface, RSS feed, or API.  Original use was music – combining tracks from different sets and artists. (Bastard Pop or Bootys)  Example – CraigsList and Google Maps to create a dynamic map of rentals by neighborhoods

5. 5 Essential Features of Mashups  Simple API – Anyone can create one  Content from 2 or more sites – Issues of info quality, control  Current emphasis on presentation – visual maps – Simple 2 dimension maps  Content structure, data – Issues of compatibility – Every mashup a unique job  Self Service – embed variety of mashups

6. 6 Current State of Mashups Is this a Revolution?  “Much the way blogs revolutionized online publishing, mashups are revolutionizing web development by allowing anyone to combine existing data from sources…in innovative ways.”  Focus on technology is misplaced – Structure and standards as important as API  Not another revolution! – Mapping data has been around a long time – Most Mashups are simple & limited value

7. 7 Current State of Mashups Is this a Revolution?  It’s not a Mashup, it’s an integration of content. – Music – based on standard musical structures – Richer, standard structures allow art form integration  90% of Mashup examples use Google Maps. – Maps are based on a standard Taxonomy / Partonomy  Mashups need taxonomies and metadata. – Crime watch – map crime database with neighborhoods – need geography taxonomy and crime database needs metadata that refers to same geographical units.

8. 8 Current State of Mashups Is this a Revolution?  Talis Library Mashup Competition: Criteria – coolness ease of use ease of deployment utility portability/ relevance to other libraries overall  Mashups are still in the realm of cool  Irrational Exuberance! – How to create more than cool mashups: Mashups in Context

9. 9 Mashups in Context Content Aggregation  Using content from 2 or more sites = Content Aggregation  Traditional content aggregation offers more than more mashups  Text mining, alerts, dynamic categorization  Information not data  Richer, semantic relationships  Content from 100’s or 1,000’s of sites  Mash ups are still largely about presentation

10. 10 Mashups in Context Faceted Navigation / Dynamic Classification  Mashups are variant of Faceted navigation – dynamically mapping two dimensions together.  Facets are orthogonal dimensions of metadata attributes – A place is not an event is not a person  Facet structure can be range (price), alphabetical, hierarchical (taxonomy)  Faceted navigation is dynamic intersection of two or more facets (map dimensions, filter search results)  A terrorism taxonomy mapped to a geography partonomy = a map of terrorist activities by region and range of activities within each region

11. 11 Mashups in Context Questions of Value  Business of Mashups – E-commerce Sites – another mechanism for targeted advertising  Mashups within the Enterprise – Combine Internet content with internal content  Mashups and Library – Talis Competition – open up Library content to variety of users – Maps of libraries – “Map” of library catalog? – Amazon Library Service

12. 12 Platform for Mashups Integrated Semantic Solutions  Integrated: To move beyond individual mashups to a platform for integration of variety of dynamic sources  Semantics: Taxonomy, metadata, controlled vocabularies, Personas, Facets, Natural Categories  Semantic Infrastructure - allows the meaningful integration of content with a minimal technological element (XML) – Deeper integration – knowledge, not just data – Combination of technology (API’s) and semantics  Platform to add unstructured content to Mashups

13. 13 Taxonomies, Metadata, and Mashups  Taxonomies are an Infrastructure Resource – Search and Browse Categorization & related content – Text mining, Alerts, Competitor Intelligence – And Mashups  Metadata – Mashups based on metadata – content structure – Need Taxonomy and Standards – generalize Mashups – Standard format – People, companies, events

14. 14 Mashups and Standards  Geography is early application because there are existing standards and/or easy to develop  Need other standard or easy to map content structures – To allow more than two content sources – To allow exchange of more meaningful information  Facets are relatively easy to develop – Dimensions – Location, people, companies, jobs, rental properties, events (crime to festivals)  Publish Content structures and format rules, not just API

15. 15 Mashups and Ontologies  Ontology – model of the relationships of a dimension – example a business  Develop rules to govern interactions of content sources  Example of Maps, People (LinkIn), Payscales, Location  Next – build in some intelligence – know how much VP in industry X usually makes – flag any that are higher than average?  IBM – “Ultimate mashup” – creating a mashup application with intelligence – users can add and remove web services – System can use semantic reasoning to understand services and their relationships (RDF and OWL)

16. 16 Mashups and Folksonomies Evolving “standard” taxonomies  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

17. 17 Advantages of Folksonomies  Simple (no complex structure to learn)  Lower cost of categorization  Open ended – can respond quickly to changes  Quality – “compare favorably with professional”?  Relevance – SME generated, close to content  Aboutness – qualitative judgments  Multiple dimensions – “communities” of like minded taggers  Better than no tags at all

18. 18 Disadvantages of Folksonomies  They don’t work very well – polysemy, synonyms, etc.  Compare favorably with no tags, not controlled vocabularies  No structure, no conceptual relationships – Flats lists do not a onomy make  Jargon – SME’s talking to themselves or each other  SME’s are not info professional – different skill  Based on popularity only, no quality control  Wikipedia article – very shallow, “wrong”? – not a taxonomy at all  Fatal flaw – how improve tags – none of the schemes work – (and then a miracle – users care about tags)

19. 19 Complexity Theory (abridged) History  An interdisciplinary method – Applied to math, model systems, economics, ecology, etc.  Initial Hype Period – 1980’s-1990’s – Chaos theory, Catastrophe theory, AI, etc.  Current – half way between hype and practical – Beware articles that focus on one aspect – self-organizing  Santa Fe Institute, social research  The Center for Complex Systems Research

20. 20 Complexity Theory (abridged) Examples  Complex Systems (not complicated) – Large number of independent relatively dumb elements interact according to a small set of rules. – Self-organizing – Local rules, local interactions – global order emerges  Definition by Example – Ant Colonies – clear tunnels with no idea of how to clear a tunnel – Neighborhoods – create a structure with no central planning  Complexity – need right level of structure and disorder  No evolution without: – Initial complex structure – Evolutionary mechanisms – feedback with consequences

21. 21 Complexity Theory and Folksonomies Evolutionary Mechanisms  Initial structures – folksonomies, Tag Clouds  Rules and evolutionary mechanisms – Feedback with consequences – you die – Define success within and for a category – more than popularity  Rank everything – content & categories, taggers and categorizers  Software – reverse relevance, auto taxonomy  Social Community – focus like Wikipedia, multiple roles

22. 22 Mashups and Evolution Mashups, Feedback, and Evolution  Social Features – easy to build – Large numbers with evolutionary mechanisms  Evolve better structures – Standard taxonomies – Process of refining taxonomies / folksonomies  Evolve better mashups – Feedback about quality of mashups – Embed feedback into mashup – evolve higher life form  Talis Library mashup competition – Also community to provide ongoing ranking – Need a Del.icio.us for Mashups

23. 23 Summary  Mashups – dynamic content from 2 or more sources  Need simple API – enables social collaboration  Use & build on content aggregation & faceted navigation  Need content structure – metadata, standard taxonomies, ontologies  If not available – evolve folksonomies into standard taxonomies – feedback and power of social networks (WIKI)  Same mechanism can evolve better mashups

24. 24 Conclusions  Mashups are not mashed up. – Could we have a new name? Unlikely.  Mashups are not revolutionary, they are evolutionary – Ease of development can be positive and negative – Evolution is one way to accentuate the positive.  Mashups can be useful – Need semantic infrastructure. – Emphasis on structure, metadata, standards  Infrastructure is cool!  No Really.

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