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Djsaab Thesis Proposal 080611 Slideshare
- 1. The Ontology of Tags PhD Dissertation Research Proposal David J. Saab 2008.06.12 Committee Members: Frederico Fonseca, Chair Andrea Tapia Michael McNeese Richard Doyle
- 2. Today... •What’s the Problem? •What’s the Solution? •What are the research contributions? •Core Concepts •Interrelationships •Integration •What the research context and methods? •What can we do better?
- 4. What’s the Problem? •Ontology •Theory of Being •“What is?” •Aristotelian origins •Ontologies •Ontology-as-category •Overspecified and Decontexualized •Not delivering semantic interoperability
- 6. Even the experts... . . . we found that we as representatives for different semantic technologies were talking different languages. We were explaining our technologies with different terms to mean the same thing and the same term to mean different things, and our models for addressing the issue of semantic interoperability were so different it was hard to get our message across to people who already identified deeply with their own way of thinking. We were supposed to be experts on semantic technologies, but we experienced a complete breakdown of semantic interoperability among ourselves. -SIM Report, A Comparative Study of Semantic Technologies, 2007
- 9. Experts’ solution... “...semantics must be made explicit, systematic, formal and standardized.”
- 10. Experts’ solution... •More structure •More syntactic rules •More logical formalisms •More standards for exchange •Less diversity •Single ontology
- 12. So what? •Lexical isn’t ontological •Language isn’t thought •Syntax isn’t semantics •Communication isn’t overly structured •Complexity isn’t diversity •Reality isn’t objective
- 14. Syntax vs. Semantics Syntax
- 15. Syntax vs. Semantics Syntax Norvig
- 16. Syntax vs. Semantics Limited Syntax Norvig
- 17. Syntax vs. Semantics Limited Semantics Syntax Norvig
- 18. Syntax vs. Semantics Limited Semantics Syntax l ica log l to ica On x Norvig Le
- 19. Syntax vs. Semantics Limited Semantics Syntax l ica log l to ica On x Norvig Le
- 20. Syntax vs. Semantics Limited Semantics Our Syntax Research l ica log l to ica On x Norvig Le
- 23. What’s the solution? •Ontology •Phenomenological •Hermeneutic •Culture •Emergent •Schematic •Junction point •Tags •Ontic flexibility •Connected to schemas
- 24. What’s the solution? •Ontology •Phenomenological Culture •Hermeneutic •Culture •Emergent Ontology •Schematic •Junction point •Tags •Ontic flexibility Tags •Connected to schemas
- 25. What’s the solution? •Ontology •Phenomenological •Hermeneutic •Culture •Emergent Schematic •Schematic Ontology •Junction point •Tags •Ontic flexibility •Connected to schemas
- 27. What’s our goal? •Capture a forever-evolving ontological target •Large-scale schematic patterns Schematic Ontology •Multiple cultural identities •Create co-evolving ontic representation of tags
- 28. What’s our goal? •Capture a forever-evolving Emergent ontological target Process •Large-scale schematic patterns Ontology •Multiple cultural identities Ontic •Create co-evolving ontic Representation representation of tags
- 30. What contributions? •Practical •Theoretical •Schematic ontology •Culture •Collaboration •Ontology guidelines •Tagging •Semantic •Hermeneutics interoperability •Intercultural communication
- 32. What’s next? •Core background concepts •Ontology •Culture •Tags •Theoretical interrelationships •Model details •Research context
- 34. Core Concept 1: Ontology •What does it mean to be? •Heidegger’s Phenomenology •Dasein •Ready-to-hand •Present-to-hand •Being-in-the-world •Being-in-the-world-with-others
- 35. Core Concept 1: Ontology •What does it mean to be? •Heidegger’s Phenomenology What becomes salient & what comes into •Dasein focus? •Ready-to-hand •Present-to-hand •Being-in-the-world •Being-in-the-world-with-others
- 37. Core Concept 2: Culture
- 38. Core Concept 2: Culture •Emergent •Intrapersonal schemas •Extrapersonal structures “…strongly connected networks of cognitive elements, having a bias in activation through repeated exposure to the same or similar stimulus, but not rigid and inflexible… clustered in experience”
- 39. Core Concept 2: Culture •Emergent •Intrapersonal schemas •Extrapersonal structures •Cultural schemas •Shared identities •Durable across generations •Applicable across contexts •Exhibit motivational force •Strengthening and weakening
- 41. Core Concept 3: Tags •Folksonomies Tagcloud academic analysis art categorization classification •Personalized semantics cognition cognitive conference culture data design emergence environment folksonomy GIS graph information infoviz •Non-hierarchical knowledge mapping maps metadata metaphor network neurophilosophy ontologies ontology philosophy rdf ref •Shared vocabularies reference representation research science search semantic semantic_web social social_networks software •Entry points structure tagcloud tagging tags taxonomy technology thesis tools visualization web
- 43. How are they integrated?
- 44. How are they integrated? World
- 45. How are they integrated? Dasein Cultural
- 46. How are they integrated? Dasein Ready-to-hand Conceptualizations Cultural
- 47. How are they integrated? Dasein Ready-to-hand Active Conceptualizations Schemas Cultural Tag Present-to-hand Phenomenon
- 48. How are they integrated? Dasein Ready-to-hand Active Conceptualizations Schemas Cultural Tag Present-to-hand Phenomenon
- 50. How do we model culture?
- 51. How do we model culture? Schemas
- 52. How do we model culture? Uncertainty Avoidance Schemas Masculinity-Femininity Personality Traits Organizational Dimensions Culture Power Distance Individualism-Collectivism
- 53. How do we model culture? Uncertainty Avoidance Schemas Masculinity-Femininity Personality Traits Organizational Dimensions Culture Power Distance Individualism-Collectivism Sche mas er sonal Intrap
- 54. How do we model culture? Uncertainty Avoidance Schemas Struc ture Masculinity-Femininity Personality Traits Organizational Dimensions Entity Culture Phenomenon Power Distance n t Conte Individualism-Collectivism Sche mas er sonal Intrap
- 55. How do we model culture? Uncertainty Avoidance Schemas Struc ture Masculinity-Femininity Personality Traits Organizational Dimensions Entity Culture Phenomenon Power Distance n t Conte l Stru ctures Individualism-Collectivism e rsona Extrap Sche mas er sonal Intrap
- 56. How do we model culture? Culture Emergence Uncertainty Avoidance Schemas Struc ture Masculinity-Femininity Personality Traits Organizational Dimensions Entity Culture Phenomenon Power Distance n t Conte l Stru ctures Individualism-Collectivism e rsona Extrap Sche mas er sonal Intrap
- 57. How do we model culture? Culture Emergence Uncertainty Avoidance Schemas Struc ture Masculinity-Femininity Personality Traits Organizational Dimensions Entity Culture Semantic Tags Phenomenon Power Distance n t Conte l Stru ctures Individualism-Collectivism e rsona Extrap Sche mas er sonal Intrap
- 59. Organizational Culture Dimensions l O na Personality Traits rg io a at D C ni iz ure ns i m ul z a t an lt io en tur ion rg Cu ens O si e al im on D s ts Pe ai rs Tr on y al lit ity na Tr so ai P er ts St nt ru te Structure ct Content ur on e Individua C lism-Coll e gs ctivism Ta gs Semantic Tags Ta tiic n ic an nt m m a Se S m Se C e ur on u ct te Content Structure nt S tr on Ph Index Power Distance en en F Schemas Phenomenon Fact ct a n om Ph om Semantic Tags en F a c t no en en e ct Semantic Tags Fa Culture Fact om m Ph on Fa Entity Culture ct Fact Phenomenon Dimensions enno Organizational Dimensions eo Organizational Personality Traits Personality Traits Phenomenon Phenomenon Ph n St nt ru te ct Masculinity-Fem ininity on ur e C Schemas e Se Se m Content m Structure an an t tic tic Ta Ta gs gs e C Uncerta ur on Content Structure ct te inty Avo ru nt idance Index St Semantic Tags ts Pe ai rs Tr on ity al al ity on Tr rs ai ts Pe D l im O na io rg Cu ens at im an lt io D iz ure ns iz ure ns an lt io at io rg Cu ens O na Personality Traits l Dimensions Culture Organizational How do cultures interact?
- 61. What does a schematic ontology look like?
- 62. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship
- 63. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship
- 64. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship
- 65. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship
- 66. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship
- 67. What does a schematic ontology look like? Transport Wato Support Navigation Jebro Communities Waan Jerak Logistics (Sailing Canoe) Ship Marshall_Islands Marshall_Islands Marshall_Islands Marshall_Islands traditional Bikini patterns patterns people radiation land land food Nuclear_Testing navigation trees trees trees turbulence food land cultivation zone community medical pass radiation food supplies radiation trade winds Nuclear_Testing Nuclear_Testing landpeople transport ship islet amphibious vegetation Bikini Bikini slope atoll lagoon vegetation ocean atoll people traditional lens island atoll Marshall_Islands islands times islands reef atoll lens atoll traditional lens atoll Marshall_Islands ecosystem reef lens island land Irooj ocean coral islands coral coral sailing wato German canoe rights lagoon Jebro
- 69. Can we fuse schemas? trees Marshall_Islands Marshall_Islands food cultivation zone patterns food radiation vegetation atoll Nuclear_Testing medical lens ocean supplies Bikini people lens island atoll islet times coral amphibious transport islands land reef land wato lagoon sailing ecosystem reef canoe Irooj turbulence slope pass rights navigation community trade winds Jebro