Structure of the Presentation● Visualization and integrated disciplines● Goals of visual analytics● Aspects of visual analytic, relevant to our PG● Tools and frameworks for visual analytics● What can be implemented?
Goals of Visual Analytics● presentation of data in an understandable way● analysis of large datasets● derivation of relevant data from large datasets● discovering hidden information, patterns, trends● providing instruments for interaction with data
Considered aspects of Visual Analytics● Space and time visualization● Plagiarism visualization● Visualization of social networks● Visualization of scientific collaboration● Perception and cognitive aspects
Temporal and Geospatial Visualization● Geospatial data is different from usual statistical data.● Toblers first law: "everything is related to everything else, but near things are more related than distant things".● Data is often uncertain: errors, missing values, deviations.● Hierarchical scale of time; different types of time: linear and cyclic, branching and multiple perspectives. 
Perception and Cognition● "Visual perception is the means by which people interpret their surroundings and for that matter, images on a computer display".● "Cognition is the ability to understand this visual information, making inferences largely based on prior learning".● "Knowledge of how we ’think visually’ is important in the design of user interfaces." 
OpenGL● "OpenGL (for Open Graphics Library) is a software interface to graphics hardware."● Interface: a set of several hundred procedures and functions● Enables specifying the objects and operations for producing high-quality graphical images 
OpenGL: Visualization of Contacts in Twitter 
Gephi● graph and network visualization● allows to work with complex and large data sets● extensive functionality: importing, visualizing, spatializing, altering, manipulating and exporting● extensibility: tools and fitures can be added 
Gapminder ● Designed to make world census data available to a wider audience ● Two-dimentional chart, use of colour and size ● Allowes the user to explore the change of the variables over time 
Geospatial and Temporal Visualization ● Nodes represent research institutions ● Thickness of connection lines depends on number of co-authorships ● Enabling change of time dinamically and observe changes ● Filtering 
Visualization of Plagiarism ● Each page is a little square ● Depending on percentage of plagiarised content each page has a colour from green to red ● Opportunity to see percentage of plagiaism of a chosen page, its0% 100% contents and used sources
Bibliographic Coupling ● If paper cite the same sources, they are connected with an arc ● Thickness depends on number of common citings ● Alternative visualization: similarity between papers
References1. D.A. Keim, J. Kohlhammer, G. Ellis, and F. Mansmann. Mastering the Information Age - Solving Problems with Visual Analytics. Florian Mansmann.2. http://www.guardian.co.uk/3. http://www.facebook.com/4. Erik Duval Till Nagel. Interactive exploration of geospatial network visualization. 2011.5. http://maps.google.com/6. Mark Segal and Kurt Akeley. The opengl graphics system: A specication, 2011.7. http://uglyhack.appspot.com/twittergraph/8. https://gephi.org/9. http://de.guttenplag.wikia.com/wiki/GuttenPlag_Wiki10.http://www.gapminder.org/
A particular slide catching your eye?
Clipping is a handy way to collect important slides you want to go back to later.