“interface is the message”                     on the path to a usable & personal Semantic Web                            ...
o utline            front-end to semantics: how do we interact with SemWeb Apps?            personalization: what do we ne...
why interfaces?            invisible computers            multitude of interaction modes            context-sensitive apps...
take ho me message             combine content semantics with user context             integrate seamlessly physical & web...
“interface is the message”                          Aaron Koblin: Artfully visualizing our humanity, TED Talk, 2011Wednesd...
FRONT-END TO SEMANTICS                          how do we interact with the SemWeb Apps?Wednesday, June 1, 2011           ...
do SemWeb apps really d iffer?Wednesday, June 1, 2011                      7
semantics: what’s special?            explicit semantics (often from open sources, e.g. LOD) used            for system de...
credits: Dan BrickleyWednesday, June 1, 2011    9
RDF dataWednesday, June 1, 2011              10
interaction w ith semanticsWednesday, June 1, 2011                         11
http://twitpic.com/il1w/full   ©	  BBC	  MMVIIIWednesday, June 1, 2011                                                   12
http://www.bbc.co.uk/programmes/b00c06n2.rdfWednesday, June 1, 2011                                 13
converting vocabulariesWednesday, June 1, 2011                        14
PERSONALIZATION                              what do we need to adapt to us?Wednesday, June 1, 2011                       ...
the user matters            when we consider interaction & interfaces, then the user plays a            key role          ...
user profile            Definition: A ‘user profile’ is a data structure that represents a            characterization of a...
user characteris tics                Personal data                Friend and relations                Experience          ...
user mo del            Definition: The ‘user model’ contains the definitions and rules            for the interpretation o...
user mo deling            Definition: ‘user modeling’ is the process of creating user            profiles following the de...
stereotyping            Stereotyping is one example of user modeling.            A user is considered to be part of a grou...
user-adaptive system            Definition: A ‘user-adaptive system’ is a system that adapts itself to a            specif...
user adaptation            User-adaptation is often used for personalization, i.e. making a            system appear to fu...
examples: user adaptation            Device-dependence            Accessibility (disabilities)            Location-depende...
adaptive hyperme d ia            Well-studied example of adaptation is ‘adaptive hypermedia’: a            hypertext’s con...
DESIGNING INTERFACESWednesday, June 1, 2011               26
d ialog principles [Grice]            Be cooperative            Be informative            Be truthful            Be releva...
UI principles [Shnei der mann]            Strive for consistency            Enable frequent users to use shortcuts        ...
usability heuristics [Nielsen]            Visibility of system status            Match between system and real world      ...
all abo ut the user’s perspective            modeling the user: what are user’s preferences, interests, history,          ...
user’s context d is tribute d            switching between one context and another            doing things not only for hi...
PERSONALIZED INTERACTION                          sWednesday, June 1, 2011           32
interaction mo des            search, e.g. keyword, faceted            browse, story lines, narratives through collections...
typical examples            recommendation systems, e.g. movies, music, art            user statistics and analysis, e.g. ...
reco m mender systems            Definition: A ‘recommender system’ is a system that recommends to            a user, base...
reco m mender systems            movies & TV programs, e.g. Netflix, MovieLens, TiVo, personalized TV            guides   ...
consi derations            Collection of activities/context/attention data            Derive interests from this data     ...
user profiles & stats            overview of user preferences, e.g. settings, privacy            overview of user interests...
Wednesday, June 1, 2011   39
Wednesday, June 1, 2011   40
social networking            professional networks & events, e.g. LinkedIn, Mendeley            people, organizations, e.g...
EXAMPLE APPLICATIONS                          Interfaces & Personalization on SemWebWednesday, June 1, 2011               ...
the big guysWednesday, June 1, 2011                  43
Wednesday, June 1, 2011   44
Wednesday, June 1, 2011   45
Wednesday, June 1, 2011   46
Wednesday, June 1, 2011   47
The Recommendation and Like plugins let users share any content            they like back to their profile.Wednesday, June...
The Activity Feed plugin shows users what their friends are doing on            your site through likes and comments.Wedne...
Wednesday, June 1, 2011   50
activity streams                                         http://xmlns.notu.be/aair/Wednesday, June 1, 2011                ...
weig hte d interest                                   http://xmlns.notu.be/wiWednesday, June 1, 2011                      ...
Wednesday, June 1, 2011   53
EXAMPLE 1                          what do Gerrit Dou and Rembrandt have in common?                                http://...
enriched Rijksmuseum collectionWednesday, June 1, 2011                  55
mili<a          teacher	  of:	  Ferdinand	  Bol	                                                                          ...
goal & central role of UMWednesday, June 1, 2011                       57
personalized experience        Personalized	  Web	  Access    Online	  Tour	  Wizard   Personalized	  Mobile	  Tour       ...
semantic recommendationsWednesday, June 1, 2011                    59
semantic recommendationsWednesday, June 1, 2011                    60
semantic recommendationsWednesday, June 1, 2011                    60
semantic recommendationsWednesday, June 1, 2011                    61
semantic recommendationsWednesday, June 1, 2011                    61
personalized toursWednesday, June 1, 2011                        62
personalized toursWednesday, June 1, 2011                        62
Interactive Museum Guide                                     h"p://chip-­‐project.org	  Wednesday, June 1, 2011           ...
Interactive Museum GuideWednesday, June 1, 2011                     64
event-based browsingWednesday, June 1, 2011                          65
dynamic adaptation            For each artwork in the museum:            Related works            Include in the tour ( & ...
EXAMPLE 2                              professionals vs. lay users on Web 2.0                            semantic annotati...
Autocompletion with multiple                  vocabularies   http://slashfacet.semanticweb.org/wordnet/search   http://sla...
Wednesday, June 1, 2011   69
Wednesday, June 1, 2011   70
Wednesday, June 1, 2011   70
Wednesday, June 1, 2011   71
Wednesday, June 1, 2011   71
Wednesday, June 1, 2011   72
Wednesday, June 1, 2011   72
EXAMPLE 3                            semantic television                            http://notube.tvWednesday, June 1, 201...
Wednesday, June 1, 2011   74
Wednesday, June 1, 2011   75
Wednesday, June 1, 2011   76
Wednesday, June 1, 2011   77
watching TV in a group                          for more details check out our blog at http://notube.tvWednesday, June 1, ...
watching TV in a group                          for more details check out our blog at http://notube.tvWednesday, June 1, ...
watching TV in a groupWednesday, June 1, 2011                            80
watching TV in a group            Environment                           Age              Interact with the second         ...
observations                          for more details check out our blog at http://notube.tvWednesday, June 1, 2011      ...
observations                          for more details check out our blog at http://notube.tvWednesday, June 1, 2011      ...
second screen & TV                            functionalities            shared virtual space     synchronization with sec...
CONTINUOUS EVALUATIONWednesday, June 1, 2011           85
CHIP users            Target users’ characteristics                small groups with 2-4 persons and a male taking the lea...
Wednesday, June 1, 2011   87
contextual analysis                    Context                            ual obse                                     rva...
do main explorationWednesday, June 1, 2011                         89
usability testingWednesday, June 1, 2011                       90
Wednesday, June 1, 2011   91
Wednesday, June 1, 2011   91
Wednesday, June 1, 2011   92
Wednesday, June 1, 2011   93
resultsWednesday, June 1, 2011             94
Wednesday, June 1, 2011   95
Wednesday, June 1, 2011   95
http://www.cs.vu.nl/intertain/Wednesday, June 1, 2011                                    96
take ho me message             combine content semantics with user context             integrate seamlessly physical & web...
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ESWC2011 Summer School: Front-end to the Semantic Web

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This talk was given by Lora Aroyo at the ESWC2011 Summer School

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ESWC2011 Summer School: Front-end to the Semantic Web

  1. 1. “interface is the message” on the path to a usable & personal Semantic Web Lora Aroyo VU University Amsterdam @laroyoWednesday, June 1, 2011 1
  2. 2. o utline front-end to semantics: how do we interact with SemWeb Apps? personalization: what do we need to adapt to users? example applications: what good & bad is out there? evaluation: why is continuous evaluation so important?Wednesday, June 1, 2011 2
  3. 3. why interfaces? invisible computers multitude of interaction modes context-sensitive apps networked devices: bridges between virtual & physical worlds GUI become central constantly increasing competitionWednesday, June 1, 2011 3
  4. 4. take ho me message combine content semantics with user context integrate seamlessly physical & web worlds identify relevance to user to rank & select information to present continuous feedback cycle: to and from user you need to deal with GUI on configuration level perform continuous user testing use real world dataWednesday, June 1, 2011 4
  5. 5. “interface is the message” Aaron Koblin: Artfully visualizing our humanity, TED Talk, 2011Wednesday, June 1, 2011 5
  6. 6. FRONT-END TO SEMANTICS how do we interact with the SemWeb Apps?Wednesday, June 1, 2011 6
  7. 7. do SemWeb apps really d iffer?Wednesday, June 1, 2011 7
  8. 8. semantics: what’s special? explicit semantics (often from open sources, e.g. LOD) used for system decisions and results use facetted presentation, searching and browsing of information use typically classifications, typologies or other structures of concepts integrate data from different sources aggregate dataWednesday, June 1, 2011 8
  9. 9. credits: Dan BrickleyWednesday, June 1, 2011 9
  10. 10. RDF dataWednesday, June 1, 2011 10
  11. 11. interaction w ith semanticsWednesday, June 1, 2011 11
  12. 12. http://twitpic.com/il1w/full ©  BBC  MMVIIIWednesday, June 1, 2011 12
  13. 13. http://www.bbc.co.uk/programmes/b00c06n2.rdfWednesday, June 1, 2011 13
  14. 14. converting vocabulariesWednesday, June 1, 2011 14
  15. 15. PERSONALIZATION what do we need to adapt to us?Wednesday, June 1, 2011 15
  16. 16. the user matters when we consider interaction & interfaces, then the user plays a key role for good interface design, a good characterization of the user is needed first, some concept from theory and literatureWednesday, June 1, 2011 16
  17. 17. user profile Definition: A ‘user profile’ is a data structure that represents a characterization of a user (u) at a particular moment of time (t) So, a user profile represents what (from a given (system) perspective) there is to know about a user. The data in a user profile can be explicitly given by the user or have been derived.Wednesday, June 1, 2011 17
  18. 18. user characteris tics Personal data Friend and relations Experience System access Browsing history Knowledge (learning) Device data Location data PreferencesWednesday, June 1, 2011 18
  19. 19. user mo del Definition: The ‘user model’ contains the definitions and rules for the interpretation of observations about the user and about the translation of that interpretation into the characteristics in a user profile. So, a user model is the recipe for obtaining and interpreting user profiles.Wednesday, June 1, 2011 19
  20. 20. user mo deling Definition: ‘user modeling’ is the process of creating user profiles following the definitions and rules of the user model. This includes the derivation of new user profile characteristics from observations about the user and the old user profile based on the user model. So, user modeling is the process of representing the user.Wednesday, June 1, 2011 20
  21. 21. stereotyping Stereotyping is one example of user modeling. A user is considered to be part of a group of similar people, the stereotype. Question: What could be stereotypes for conference participants (when we design the conference website)?Wednesday, June 1, 2011 21
  22. 22. user-adaptive system Definition: A ‘user-adaptive system’ is a system that adapts itself to a specific user. Often, a user-adaptive system (or adaptive system, in short) uses user profiles to base its adaptation on. So, designing an adaptive system implies designing the user modeling.Wednesday, June 1, 2011 22
  23. 23. user adaptation User-adaptation is often used for personalization, i.e. making a system appear to function in a personalized way. Question: What user profile characteristics would be useful in personalizing the conference’s registration site? Question: How would you obtain those characteristics?Wednesday, June 1, 2011 23
  24. 24. examples: user adaptation Device-dependence Accessibility (disabilities) Location-dependence Adaptive workflow Question: Can you give concrete examples for interface adaptation, both the adaptation effect as the prior user modeling necessary?Wednesday, June 1, 2011 24
  25. 25. adaptive hyperme d ia Well-studied example of adaptation is ‘adaptive hypermedia’: a hypertext’s content and navigation are then adapted to the user’s browsing of the hypertext.Wednesday, June 1, 2011 25
  26. 26. DESIGNING INTERFACESWednesday, June 1, 2011 26
  27. 27. d ialog principles [Grice] Be cooperative Be informative Be truthful Be relevant Be perspicuous (be clear)Wednesday, June 1, 2011 27
  28. 28. UI principles [Shnei der mann] Strive for consistency Enable frequent users to use shortcuts Offer informative feedback Design dialog to yield closure Offer simple error handling Permit easy reversal of actions Support internal locus of control Reduce short-term memory loadWednesday, June 1, 2011 28
  29. 29. usability heuristics [Nielsen] Visibility of system status Match between system and real world User control and freedom Consistency and standards Error prevention Recognition rather than recall Flexibility and efficiency of use Aesthetic and minimalist design Help users recognize, diagnose and recover from errors Help and documentationWednesday, June 1, 2011 29
  30. 30. all abo ut the user’s perspective modeling the user: what are user’s preferences, interests, history, activities, etc. modeling the user’s context: e.g. location, time, device which of all the data available is relevant for this user in this context also called context-awareWednesday, June 1, 2011 30
  31. 31. user’s context d is tribute d switching between one context and another doing things not only for him/herself, e.g. buying present for a girlfriendWednesday, June 1, 2011 31
  32. 32. PERSONALIZED INTERACTION sWednesday, June 1, 2011 32
  33. 33. interaction mo des search, e.g. keyword, faceted browse, story lines, narratives through collections annotations of multimedia, e.g. (collaborative) tagging, professional annotation of text, images and video, tagging games explanations, hints, user feedback, e.g. explanation of recommendation results, explanation of autocompletion suggestionsWednesday, June 1, 2011 33
  34. 34. typical examples recommendation systems, e.g. movies, music, art user statistics and analysis, e.g. user usage data, profile, group profiles, etc. social networkingWednesday, June 1, 2011 34
  35. 35. reco m mender systems Definition: A ‘recommender system’ is a system that recommends to a user, based on her individual interests, items that the user could find interesting. Examples: music, movies, people, restaurants Types: collaborative (reason about similar users), content-based (reason about similar items) Problems: new users, new items, sparsity, gray sheepWednesday, June 1, 2011 35
  36. 36. reco m mender systems movies & TV programs, e.g. Netflix, MovieLens, TiVo, personalized TV guides music, e.g. LastFM, Pandora, iTunes Genius food & tourism, e.g. guides adapted to location, current time, preferences news, e.g. Google reader, news filters e-shopping, e.g. Amazon’s recommendations advertisement, e.g. Facebook personalized ads art, museums, e.g. personalized search, personalized museum guidesWednesday, June 1, 2011 36
  37. 37. consi derations Collection of activities/context/attention data Derive interests from this data Recommender-specific problems, e.g. cold start, over-specialization Surface items of interest in the ‘long tail’ Cross-domain recommendations Multi-person recommending Granular control for usersWednesday, June 1, 2011 37
  38. 38. user profiles & stats overview of user preferences, e.g. settings, privacy overview of user interests, e.g. ranking of interests, links to content overview of user/group activities, e.g. per topics, per activity, per date, over a period, overall comparative views between users, e.g. LastFM, livingSocial movies user similarity, Twitter similar users to you different views/visualization over the same set of user dataWednesday, June 1, 2011 38
  39. 39. Wednesday, June 1, 2011 39
  40. 40. Wednesday, June 1, 2011 40
  41. 41. social networking professional networks & events, e.g. LinkedIn, Mendeley people, organizations, e.g. Facebook, MySpace Twitter social bookmarking, e.g. Delicious, StumbleUpon, Diggit GetGlue Books, e.g. LibabryThingWednesday, June 1, 2011 41
  42. 42. EXAMPLE APPLICATIONS Interfaces & Personalization on SemWebWednesday, June 1, 2011 42
  43. 43. the big guysWednesday, June 1, 2011 43
  44. 44. Wednesday, June 1, 2011 44
  45. 45. Wednesday, June 1, 2011 45
  46. 46. Wednesday, June 1, 2011 46
  47. 47. Wednesday, June 1, 2011 47
  48. 48. The Recommendation and Like plugins let users share any content they like back to their profile.Wednesday, June 1, 2011 48
  49. 49. The Activity Feed plugin shows users what their friends are doing on your site through likes and comments.Wednesday, June 1, 2011 49
  50. 50. Wednesday, June 1, 2011 50
  51. 51. activity streams http://xmlns.notu.be/aair/Wednesday, June 1, 2011 51
  52. 52. weig hte d interest http://xmlns.notu.be/wiWednesday, June 1, 2011 52
  53. 53. Wednesday, June 1, 2011 53
  54. 54. EXAMPLE 1 what do Gerrit Dou and Rembrandt have in common? http://www.chip-project.orgWednesday, June 1, 2011 54
  55. 55. enriched Rijksmuseum collectionWednesday, June 1, 2011 55
  56. 56. mili<a teacher  of:  Ferdinand  Bol   teacher  of:  Nicolaes  Maes self-­‐portrait teacher  of:  Gerrit  Dou style:  Baroque place:  Amsterdam,   1625  to  1650Wednesday, June 1, 2011 56
  57. 57. goal & central role of UMWednesday, June 1, 2011 57
  58. 58. personalized experience Personalized  Web  Access Online  Tour  Wizard Personalized  Mobile  Tour Interactive tours Semantic Search Interactive user modeling On-the-fly adaptation Museum tour maps Recommendations of artworks & art topics Synchronized user Historic timeline profileWednesday, June 1, 2011 58
  59. 59. semantic recommendationsWednesday, June 1, 2011 59
  60. 60. semantic recommendationsWednesday, June 1, 2011 60
  61. 61. semantic recommendationsWednesday, June 1, 2011 60
  62. 62. semantic recommendationsWednesday, June 1, 2011 61
  63. 63. semantic recommendationsWednesday, June 1, 2011 61
  64. 64. personalized toursWednesday, June 1, 2011 62
  65. 65. personalized toursWednesday, June 1, 2011 62
  66. 66. Interactive Museum Guide h"p://chip-­‐project.org  Wednesday, June 1, 2011 63
  67. 67. Interactive Museum GuideWednesday, June 1, 2011 64
  68. 68. event-based browsingWednesday, June 1, 2011 65
  69. 69. dynamic adaptation For each artwork in the museum: Related works Include in the tour ( & recalculate the map/tour) Indicate relevance in terms of e.g. personal interest, position, recommended by friends, by Rijks, on view Rate to indicate interest At any point of the tour: Include/exclude artworks Adjust tour length Change navigation in and outside of the tour Save for other toursWednesday, June 1, 2011 66
  70. 70. EXAMPLE 2 professionals vs. lay users on Web 2.0 semantic annotation of Rijksmuseum prints http://e-culture.multimedian.nl/pk/annotate? semantic tagging: http://waisda.nlWednesday, June 1, 2011 67
  71. 71. Autocompletion with multiple vocabularies http://slashfacet.semanticweb.org/wordnet/search http://slashfacet.semanticweb.org/autocomplete/demos/Wednesday, June 1, 2011 68
  72. 72. Wednesday, June 1, 2011 69
  73. 73. Wednesday, June 1, 2011 70
  74. 74. Wednesday, June 1, 2011 70
  75. 75. Wednesday, June 1, 2011 71
  76. 76. Wednesday, June 1, 2011 71
  77. 77. Wednesday, June 1, 2011 72
  78. 78. Wednesday, June 1, 2011 72
  79. 79. EXAMPLE 3 semantic television http://notube.tvWednesday, June 1, 2011 73
  80. 80. Wednesday, June 1, 2011 74
  81. 81. Wednesday, June 1, 2011 75
  82. 82. Wednesday, June 1, 2011 76
  83. 83. Wednesday, June 1, 2011 77
  84. 84. watching TV in a group for more details check out our blog at http://notube.tvWednesday, June 1, 2011 78
  85. 85. watching TV in a group for more details check out our blog at http://notube.tvWednesday, June 1, 2011 79
  86. 86. watching TV in a groupWednesday, June 1, 2011 80
  87. 87. watching TV in a group Environment Age Interact with the second 15 - 35 years old screen as a group         Friend interaction at home Type of Activities Watching as a group quiz and betting games change camera view Synchronization information regarding the TV & Second Screen content of the program between second screens            textual captions between second screens & TV show content provider Type of Program SportsWednesday, June 1, 2011 81
  88. 88. observations for more details check out our blog at http://notube.tvWednesday, June 1, 2011 82
  89. 89. observations for more details check out our blog at http://notube.tvWednesday, June 1, 2011 83
  90. 90. second screen & TV functionalities shared virtual space synchronization with second voice dubbing screen subtitles “overlay” on top of the main related information TV-picture quizzes censoring voting & betting different camera views scene-grab & share group alerts social interaction live-chat parental advisory uncensored version different camera viewsWednesday, June 1, 2011 84
  91. 91. CONTINUOUS EVALUATIONWednesday, June 1, 2011 85
  92. 92. CHIP users Target users’ characteristics small groups with 2-4 persons and a male taking the leading role (67%) middle-aged people in 30-60 years old (75%) higher-educated (62%) no prior knowledge about the Rijksmuseum collection (62%) visit the museum for education (98%)Wednesday, June 1, 2011 86
  93. 93. Wednesday, June 1, 2011 87
  94. 94. contextual analysis Context ual obse rvations Define familiarity with the domain s Define familiarity with iew collections/vocabularies ter v r in Use Va Identify use cases lid ate Identify navigation patterns sks Model user’s ta Identify requirements for user groupsWednesday, June 1, 2011 88
  95. 95. do main explorationWednesday, June 1, 2011 89
  96. 96. usability testingWednesday, June 1, 2011 90
  97. 97. Wednesday, June 1, 2011 91
  98. 98. Wednesday, June 1, 2011 91
  99. 99. Wednesday, June 1, 2011 92
  100. 100. Wednesday, June 1, 2011 93
  101. 101. resultsWednesday, June 1, 2011 94
  102. 102. Wednesday, June 1, 2011 95
  103. 103. Wednesday, June 1, 2011 95
  104. 104. http://www.cs.vu.nl/intertain/Wednesday, June 1, 2011 96
  105. 105. take ho me message combine content semantics with user context integrate seamlessly physical & web worlds identify relevance to user to rank & select information to present continuous feedback cycle: to and from user you need to deal with GUI on configuration level perform continuous user testing use real world dataWednesday, June 1, 2011 97

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