How Could End-Users Identify Interesting Resources?

Madrid, 14.06.2013 Martin Voigt

Attract them visually!

Titel der Präsentation Folie Nr. 2 von XYZ How to find interesting resources? | Martin Voigt 2

Structure

Motivation and problems

Iterative development of a user interface

Concept and implementation of a back-end

Conclusion

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Growing amount of data

Motivation

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[Key2012]

How to get insights from the data?

Motivation

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How to get insights from the data?

Information Visualization!

Motivation

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Motivation

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InfoVis for Semantic Web data?

Problem

End-users have no idea about creating effective InfoVis and have no programming skills.

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Overall concept of VizBoard

Semantic-assisted InfoVis-Process [Voigt2013]

How to find interesting resources?

objective vs. subjective interestingness [Silberschatz1996]

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Data UploadData Pre-Selection

Data & VisSelection

Visualization Configuration

Perception & Internalization

Data Augmentation

Visualization Recommendation

Visualization Integration

Knowledge Externalization

Data Reduction

Human Interaction

System Interaction

31 5 7 9

2 4 6 8 10

Data UploadData Pre-Selection

Data & VisSelection

Visualization Configuration

Perception & InternalizationU

Human Interaction

31 5 7 9

Main problems to solve

1st: Interactive, understandable user interface

2nd: Backend techniques to identify relevant resources

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Structure

Conclusion

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User Interface Concept

Prerequisites - Visualization

node link diagrams vs. nested views

insufficient screen estate interaction required

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Prerequisites - Interaction

use widely adapted techniques

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User Study - Setup

Task Load Index to track efforts, e.g., mental or temporal

10 tasks based on “Visual Information-seeking Mantra” [Shneiderman1996]

Questionnaire for additional feedback

10 students with less/no SemWeb knowledge

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User Study – Results

+ node link to get to know the data structure

+ navigation history and bookmarking helpful

- too much information shown

- too many options

- SW knowledge required

functionality vs. user satisfaction

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Structure

Conclusion

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Structure

Conclusion

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Assisting Backend

Implementation

• Java Jersey REST WS

• Jena TDB

• RMonto & RapidMiner

• JGraphT

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Data Repository

Storage, Filtering, Recommendation

Augmentation

Data Access

Analyzer

Storage

Annotator

RESTful API

Pivoting

Filter

upload get | filter

Structure

Conclusion

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Sum it up!

End-user need assistances to identify interesting SemWeb resources (in big datasets)

Approach using objective measures, understandable visualizations, and easy interaction

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Sum it up!

SWIs for end-users should be task-specific as possible

less is more: interaction, information, SW intrinsics

Visualizing huge SW datasets in browsers is cumbersome

Current tasks

Subjective interestingness

Planning an advanced user study

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Thanks for listening. Questions?

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References

[Cyganiak2011] Cyganiak, R. & Jentzsch, A.: Linking Open Data cloud diagram. http://lod-cloud.net/, 2011

[Key2012] Key, A.; Howe, B.; Perry, D. & Aragon, C.: VizDeck: self-organizing dashboards for visual analytics. Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, ACM, 2012, 681-684

[Shneiderman1996] Shneiderman, B.: The eyes have it: a task by data type taxonomy for information visualizations. Visual Languages, 1996. Proceedings., IEEE Symposium on, 1996, 336-343

[Silberschatz1996] A. Silberschatz, A. & Tuzhilin, A.: What makes patterns interesting in knowledge discovery systems. Knowledge and Data Engineering, IEEE Transactions on, 8(6):970 -974, dec 1996.

[Voigt2013] M. Voigt, S. Pietschmann, K. Meißner: A Semantics-Based, End-User-Centered Information Visualization Process for Semantic Web Data. Semantic Models for Adaptive Interactive Systems, Springer, 2013

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How Could End-Users Identify Interesting Resources?

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