1. Comparison Swivel and Many Eyes
Task Force Visualisation
Eurostat 19/11/2008
Gunter Schäfer
19-November-2009

2. What are Swivel and Many Eyes?
They follow the principle of Internet 2.0
Sharing of information (data, graphs and other visualisations)
Users are invited to contribute new data and modify the presentation
Invitation to comment, to rate and to re-interpret the data
Discussion groups on meaning of data, learning from others
No natural authority to determine content

3. Origin of the systems Swivel Many Eyes
Commercial initiative (from California)‏
Main ‘public body’ with additional separate payable option of ‘professional edition’
Public part has function of attracting attention
Commercial data access is restricted by comparisons with public data possible
Many Eyes
Research initiative (IBM Visual Communication Lab)‏
Long-term objectives not clear
No ‚business plan‘
Research on communication on data

4. Technology Swivel Many Eyes Ajax and Java script
‚Browser friendly‘ but limited functionality and interaction
Open source graphics library called ‚Ploticus‘
Limited range of visualisations (4 major ones)‏
Many Eyes
Java run time environment
Add-on required for most browsers
Potential compatibility issues.
Larger variety of graphical visualisation techniques (about major ones)‏

5. Visualisation techniques
Swivel
Limited range of visualisations
Vertical and horizontal bar charts
Line charts
Scatter plots
Many Eyes
Larger variety of graphical visualisation techniques (about major ones), e.g.
Zoomable maps
Stacked line graphs,
Block histograms
Bubble charts
Pie charts
Visualisations are more interactive

6. Approaches to content Swivel Large numbers of datasets
Automated generation of visualisations (hundreds of graphs per dataset)‏
Automated correlations
Many Eyes
Aim for many datasets
Visualisation only by users
More verity in types of visualisations

7. Critical issues Metadata is strongly neglected
Are single-type visualisations sufficient to show complex situations?
No concept of quality of available data: high quality beside low quality
Structuring, navigation and finding of relevant information
No updating of information, no information on validity of data
No filtering of input (governance)
Selection and deletion?

8. Questions to be posed Early pilots or serious applications?
Will Swivel and Many Eyes survive and find a larger user community?
Who are users and what do they intend with the applications?
Should the ESS institutions get involved at all?
What type of involvement of ESS could be imagined?
What could be benefits for the ESS?

9. Thank you for your attention