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4/29/10 www.insemtives.eu 1 INSEMTIVESIncentives for SemanticsWP 1 Roberta Cuel, UNITN, Katharina Siorpaes, UIBK, and Markus Rohde, USI
Overview 4/29/10 www.insemtives.eu 2
Challenge and motivation Bringing technical infrastructures and social opportunity structures together Some tasks in semantic content creation require the human in the loop, thus: How increase motivation of end users? How should tools/ Technologies be designed to foster human contribution? 4/29/10 www.insemtives.eu 3
Aims and outcomes Analysis of semantic content creation tasks.  Identification of human-driven semantic content creation tasks. Defining incentive models for semantic content creation tasks.   Specifying a methodology for semantic content creation including incentives-related considerations and participatory design.  4/29/10 www.insemtives.eu 4
Work plan view 24 12 18 30 36 6 0 D1.1.1 Analysis of content authoring processes (initial version) D1.1.2 Analysis of content authoring processes (final version)  Task 1.1Analysis of semantic content authoring processes  UIBK  D1.2.2 Methodology for semantic content authoring (last vers) D1.2.1 Methodology for semantic content authoring (first vers) UIBK Task 1.2Methodology for semantic content authoring D1.3.2 Incentive models and PD  guidelines  (final vers) D1.3.1 Incentive models and PD  guidelines   USI/UNITN Task 1.3Incentives framework
Research approach and methods User-centered approach and practice orientation Literature Review (Psychology, Economics, Design Science)  Requirements Analysis: State of the art Usability lab tests Expert walkthroughs Generalization from use case studies Semi-structured interviews Focus group discussions and Workshops Field experiments  and fine tuning  4/29/10 www.insemtives.eu 6
AR process model Action Research: Evolutionary, cyclic process model 4/29/10 www.insemtives.eu 7
Methods (examples) 4/29/10 www.insemtives.eu 8 Usability Test Usability Test Expert Walkthrough Video: User Interview
Semantic content creation 4/29/10 www.insemtives.eu 9 Gomez-Perez et al., 2004
Human intelligence in semantic content creation 4/29/10 www.insemtives.eu 10 Katharina Siorpaes and Elena Simperl: Human Intelligence in the Process of Semantic Content Creation, World Wide Web Journal (WWW), Springer, December 2009.
Human intelligence in semantic content creation: examples Aligning ontologies Deciding whether two concepts are related  Type of relationship Validating results from automatic methods Training sets for algorithms Video annotation High level semantics Watching and interpreting the video (topic, sentiment, location, etc.)  4/29/10 www.insemtives.eu 11
Where can the human really be expected to contribute? Expressivity of annotations ( WP2 on models) Which content? Corpora that are annotated/aligned … Post-processing: validation Training sets: for text annotation algorithms, alignment  Entertaining games Complexity of tasks Space of possible decisions Too easy vs. too difficult Interesting content (i.e. YouTube videos vs. eCl@ss and UNSPSC ontologies) Last but not least: game design  4/29/10 www.insemtives.eu 12
Which variables affect performance of users? Relevant task-related variables that might affect the performance of the users of semantic annotation tools: Goal of the annotation or ontology population exercise Task, or more typically, an ordered collection of tasks into which the annotation exercise can be divided Social structure, a stylized and simplified set of social relationships among the subjects participating in the exercise Nature of good, a stylized description, in game-theoretical terms, of the relationship between what good is produced and who consumes it Required skills of the agents to complete the annotation task. 4/29/10 www.insemtives.eu 13
Which tools can be used to foster participation? Annotation Task Matrix A multidimensional tool for semantic annotation task analysis that allows for a description of an annotation task along all of relevant dimensions simultaneously Usability/ sociabilityrequirements User Experience Design/ Design for Fun Guidelines/ Methodsfor PD Community Support 4/29/10 www.insemtives.eu 14
Selected findings (TID) Usability/ Sociabilityrequirements Inconsistantnavigationandcolourscheme High complexity, littlehelpandadaptability Lackingvisibility/ awarenessofusers‘ contribution Relevant incentive/ motivation variables Employees use their own media channels to communicate, instead of official ones Users contribute only if they benefit themselves -> “critical mass”-problem (incentives to contribute to public good) Task variety and goals should be challenging Methodological problem of limited access 4/29/10 www.insemtives.eu 15
Selected findings(seekda!) Usability/ sociabilityrequirements Redundanciesandexternalcontent (ads) Lackingcustomizationaccordingtousers‘ needs Riskofinappropriateusergeneratedcontent (descriptions) Relevant incentive/motivation variables Contribution processes to public goods Community effects and expertise: „Facebook“ for web servicedevelopers Methodologicalproblems: Limited usersandMissingbusiness model 4/29/10 www.insemtives.eu 16
Selected findings (PGP) Usability/ SociabilityRequirements Intuitive and self-descriptive icons Ambiguous wording (descriptions, error messages) Target group specific design (children, parents, teachers) Lacking visibility/ awareness of user behaviour (buy items) Lacking adaptability (skip intro, sound/ volume control) Relevant incentive/motivation variables Contribution to personal goods (virtual words) Skill level: low but can improve using educational games  Methodological problem of end user access 4/29/10 www.insemtives.eu 17
Outlook Final analysis of semantic content authoring processes Include additional considerations such as complexity of tasks, corpora, etc.  Include findings from case studies and tools (games!) Final methodology for semantic content authoring Revisions based on experiences from case studies Final incentive models and PD guidelines  Outcome will be a concrete “cookbook” 4/29/10 www.insemtives.eu 18

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WP1 1st Review

  • 1. 4/29/10 www.insemtives.eu 1 INSEMTIVESIncentives for SemanticsWP 1 Roberta Cuel, UNITN, Katharina Siorpaes, UIBK, and Markus Rohde, USI
  • 3. Challenge and motivation Bringing technical infrastructures and social opportunity structures together Some tasks in semantic content creation require the human in the loop, thus: How increase motivation of end users? How should tools/ Technologies be designed to foster human contribution? 4/29/10 www.insemtives.eu 3
  • 4. Aims and outcomes Analysis of semantic content creation tasks. Identification of human-driven semantic content creation tasks. Defining incentive models for semantic content creation tasks. Specifying a methodology for semantic content creation including incentives-related considerations and participatory design. 4/29/10 www.insemtives.eu 4
  • 5. Work plan view 24 12 18 30 36 6 0 D1.1.1 Analysis of content authoring processes (initial version) D1.1.2 Analysis of content authoring processes (final version) Task 1.1Analysis of semantic content authoring processes UIBK D1.2.2 Methodology for semantic content authoring (last vers) D1.2.1 Methodology for semantic content authoring (first vers) UIBK Task 1.2Methodology for semantic content authoring D1.3.2 Incentive models and PD guidelines (final vers) D1.3.1 Incentive models and PD guidelines USI/UNITN Task 1.3Incentives framework
  • 6. Research approach and methods User-centered approach and practice orientation Literature Review (Psychology, Economics, Design Science) Requirements Analysis: State of the art Usability lab tests Expert walkthroughs Generalization from use case studies Semi-structured interviews Focus group discussions and Workshops Field experiments and fine tuning 4/29/10 www.insemtives.eu 6
  • 7. AR process model Action Research: Evolutionary, cyclic process model 4/29/10 www.insemtives.eu 7
  • 8. Methods (examples) 4/29/10 www.insemtives.eu 8 Usability Test Usability Test Expert Walkthrough Video: User Interview
  • 9. Semantic content creation 4/29/10 www.insemtives.eu 9 Gomez-Perez et al., 2004
  • 10. Human intelligence in semantic content creation 4/29/10 www.insemtives.eu 10 Katharina Siorpaes and Elena Simperl: Human Intelligence in the Process of Semantic Content Creation, World Wide Web Journal (WWW), Springer, December 2009.
  • 11. Human intelligence in semantic content creation: examples Aligning ontologies Deciding whether two concepts are related Type of relationship Validating results from automatic methods Training sets for algorithms Video annotation High level semantics Watching and interpreting the video (topic, sentiment, location, etc.) 4/29/10 www.insemtives.eu 11
  • 12. Where can the human really be expected to contribute? Expressivity of annotations ( WP2 on models) Which content? Corpora that are annotated/aligned … Post-processing: validation Training sets: for text annotation algorithms, alignment Entertaining games Complexity of tasks Space of possible decisions Too easy vs. too difficult Interesting content (i.e. YouTube videos vs. eCl@ss and UNSPSC ontologies) Last but not least: game design 4/29/10 www.insemtives.eu 12
  • 13. Which variables affect performance of users? Relevant task-related variables that might affect the performance of the users of semantic annotation tools: Goal of the annotation or ontology population exercise Task, or more typically, an ordered collection of tasks into which the annotation exercise can be divided Social structure, a stylized and simplified set of social relationships among the subjects participating in the exercise Nature of good, a stylized description, in game-theoretical terms, of the relationship between what good is produced and who consumes it Required skills of the agents to complete the annotation task. 4/29/10 www.insemtives.eu 13
  • 14. Which tools can be used to foster participation? Annotation Task Matrix A multidimensional tool for semantic annotation task analysis that allows for a description of an annotation task along all of relevant dimensions simultaneously Usability/ sociabilityrequirements User Experience Design/ Design for Fun Guidelines/ Methodsfor PD Community Support 4/29/10 www.insemtives.eu 14
  • 15. Selected findings (TID) Usability/ Sociabilityrequirements Inconsistantnavigationandcolourscheme High complexity, littlehelpandadaptability Lackingvisibility/ awarenessofusers‘ contribution Relevant incentive/ motivation variables Employees use their own media channels to communicate, instead of official ones Users contribute only if they benefit themselves -> “critical mass”-problem (incentives to contribute to public good) Task variety and goals should be challenging Methodological problem of limited access 4/29/10 www.insemtives.eu 15
  • 16. Selected findings(seekda!) Usability/ sociabilityrequirements Redundanciesandexternalcontent (ads) Lackingcustomizationaccordingtousers‘ needs Riskofinappropriateusergeneratedcontent (descriptions) Relevant incentive/motivation variables Contribution processes to public goods Community effects and expertise: „Facebook“ for web servicedevelopers Methodologicalproblems: Limited usersandMissingbusiness model 4/29/10 www.insemtives.eu 16
  • 17. Selected findings (PGP) Usability/ SociabilityRequirements Intuitive and self-descriptive icons Ambiguous wording (descriptions, error messages) Target group specific design (children, parents, teachers) Lacking visibility/ awareness of user behaviour (buy items) Lacking adaptability (skip intro, sound/ volume control) Relevant incentive/motivation variables Contribution to personal goods (virtual words) Skill level: low but can improve using educational games Methodological problem of end user access 4/29/10 www.insemtives.eu 17
  • 18. Outlook Final analysis of semantic content authoring processes Include additional considerations such as complexity of tasks, corpora, etc. Include findings from case studies and tools (games!) Final methodology for semantic content authoring Revisions based on experiences from case studies Final incentive models and PD guidelines Outcome will be a concrete “cookbook” 4/29/10 www.insemtives.eu 18

Editor's Notes

  1. I would delete community support is required.. Because it doesn’t happen in all the cases
  2. I propose to maintain explaining that there are many field that are doing these type of analysis:Field and lab experiments / psychologist studies / social and behaviors / organizatioal studies on incentives and human resource management within the companies In alternative you can deleted adding this content in slide 20
  3. There are 2 pictures on usability … ???
  4. Roberta: Katharina I suggest to delete the reference to your paper because we have already in the slide of outcomes
  5. Instead of explaining what they are I would present some examples
  6. I propose to delete it
  7. I propose this slide