a visual workflow to explore the web of data for scholars
DESCRIPTION
As the Web evolves in an integrated and interlinked knowledge space thanks to the growing amount of published Linked Open Data, the need to nd solutions that enable the scholars to discover, explore and analyse the underlying research data emerges. Scholars, typically non-expert technology users, lack of in-depth understanding of the underlying semantic technology which limits their ability to interpret and query the data. We present a visual work how to connect scholars and scientificc resources on the Web of Data. We allow scholars to move from exploratory analysis in academic social networks to exposing relations between these resources. We allow them to reveal experts in a particular field and discover relations in and beyond their research communities. This paper aims to evaluate the potential of such a visual work ow to be used by non-expert users to interact with the semantically enriched data and familiarize with the underlying dataset.TRANSCRIPT
A Visual Workflow to Explore the Web of Data for Scholars
Anastasia Dimou, Laurens De Vocht, Mathias Van Compernolle, Erik Mannens, Peter Mechant and Rik Van de Walle
Ghent University – iMinds – Multimedia
Big Scholar 2014, WWW14
Seoul, Korea, 8th April 2014
ResXplorer.org ewi.mmlab.be/academic
Exploring the Web of Scholars with Linked Data
Demanddiscover, explore and analyze the research data reuse and exchange resources
Exploring the Web of Scholars with Linked Data
Demanddiscover, explore and analyze the research data reuse and exchange resources
Linked Open Data
Exploring the Web of Scholars with Linked Data
Advantagea substantial role in the context of digital libraries and archivesideal to reveal links between resources
Exploring the Web of Scholars with Linked Data
Disadvantagelack of understanding of the semantic technologylimits scholars to optimally interpret and query the Web of Scholars
Visual representations for Linked Open Data
to observe multiple aspectsof the data while controlling
and coordinating its views
to additionally reveal the links between the data
Visual workflow for Linked Open Data
Visual workflow dynamic
Visual representation static
A visual workflow for resources represented
as Linked Open Datafor exploitation, discovery and analysis
of the Web of Data for scholarsusing information exploration techniques
Visual Workflow
Visual Workflow
Information Exploration:
Exploratory Data Analysis
The scholar gets familiar with the dataset
no explicit assumption regarding the dataset
the dataset itself reveals its underlying model and the relationships between its resources
ewi.mmlab.be/academic
Visual Workflow
Coordinated view
Most detailed resourcescannot be further decomposed
a certain resource or the links between two resources
Coordinates the narrowing and the broadening view
ResXplorer.org ewi.mmlab.be/academic
Visual Workflow
Information Exploration:
Exploratory Search
The scholar is familiar with the dataset
Scholars explore the dataset on their ownfind novel relations between resources
Views are not limited to the data of the dataset but relevant links to resources of other datasets are also revealed and visualized
ResXplorer.org
Evaluation of the Visual Workflow
Evaluation
Demo of the workflow for the evaluation
LOD Visualization Suite (LOD/VizSuite) implements the narrowing view
ResXplorerimplements the broadening view
ResXplorer.org ewi.mmlab.be/academic
Survey Results: Explorability
Survey Results: Complexity
User test results: Narrowing View
User test results: Broadening View
Conclusions
Novel visual workflow for exploring resources in the Web of Data
User interfaces based on graph visualizations offer unique, multifaceted experience
when combined with techniques for information explorationand enhanced with optimized search in Linked Data.
enables scholars to view and navigate through combined aspects of research data
to come up spontaneously with observations whose reasoning can be directly investigated
A Visual Workflow to Explore the Web of Data for Scholars
ResXplorer.org: http://resxplorer.org
LOD/VizSuite: http://ewi.mmlab.be/academic
Contact us
Anastasia Dimou [email protected] @natadimou
Laurens de Vocht [email protected] @laurens_d_v