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Evaluating Interaction Patterns for Linked Data

This research evaluates interaction patterns for linked data, proposing adaptation to enhance user experience by automating IA components through ontologies. Rhizomer's patterns compared to IMDb, indicating improved task completion rates but constrained user interaction. Suggestions for enhancement explored.

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Evaluating Interaction Patterns for Linked Data

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  1. Evaluating Interaction Patterns for Linked Data Rosa Gil, Antonio López-Muzás, Josep Maria Brunetti, Juan Manuel Gimeno, Roberto García HCI & Data Integration Research Group Universitat de Lleida, Spain

  2. Introduction • Proposal: adapt data interaction patterns [Shneiderman] and Information Architecture components [Morville] • Data structure (ontologies): automate IA components • Rhizomer: Interaction Patterns  IA Components • Overview navigation bars • Main classes (topics) and their organisation • Zoom & Filter  facets • Main properties and values, filter • Usability evaluation with end-users • Compare IMDb vs. Rhizomer on LinkedMDB • Can the LinkedData version improve user experience?

  3. User Task:“Find three films where Woody Allen is director and also actor”.

  4. Look & Match

  5. Conclusions • Only one completed task in IMDb without help… and no one with Rhizomer • 83% completed the task faster with Rhizomer • Really, just 1 issue with Rhizomer: • users started from “actor” instead than from “film” • User interaction is currently too constrained underlying data structured • Explore alternatives: inverse property facets, facets for facet values, breadcrumbs…

  6. Thank you for your attention More details: http://rhizomik.net/rhizomer Contact: Roberto Garcia (roberto@rhizomik.net) HCI & Data Integration Research Group Universitat de Lleida, Spain

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