Opportunistic visualization with iVoLVER

Proposed as 'data analysis anywhere, anytime, from anything', Opportunistic Information Visualization (Opportu-Vis) [1] seeks to provide analytical support in scenarios where the data of interest is not explicitly available and has to be retrieved from digital artifacts that are not traditionally used as data sources. Examples include raster images, web pages, vector files, and photographs. This showpiece presents how iVoLVER, the Interactive Visual Language for Visualization Extraction and Reconstruction, provides support in such settings. We briefly describe the overall construction approach of the tool in scenarios where different digital artifacts are used to compose interactive visuals. All of this becomes possible by using the data extraction capabilities of iVoLVER together with the elements of its visual language.Postprin

Designing digital constructive visualization tools

The emergence of tools that support fast and easy creation of visualizations has made the benefits of Information Visualization (InfoVis) more accessible. The predominant design for visualization authoring tools often includes features such as automated mappings and visualization templates, which make tools effective and easy-to-use. These features, however, still impose barriers to non-experts (i.e., people with no formal training on visualization concepts). The paradigm of Constructive Visualization (ConstructiveVis) has shown potential to overcome some of these barriers, but it has only been investigated through the use of physical tokens that people manipulate to create representations of data. This dissertation investigates how the principles of ConstructiveVis can be applied in the design and implementation of digital constructive visualization tools. This thesis presents the results of several observational studies that uncover how tools that promote a constructive approach to visualization compare to more conventional ones. It also sheds light on what kind of benefits and limitations digital ConstructiveVis brings into non-experts' visualization design process. The investigations here presented lay the foundations for the design of better visualization tools that not only allow people to create effective visualizations but also promote critical reflection on design principles

Opportunistic visualization with iVoLVER

Proposed as 'data analysis anywhere, anytime, from anything', Opportunistic Information Visualization (Opportu-Vis) [1] seeks to provide analytical support in scenarios where the data of interest is not explicitly available and has to be retrieved from digital artifacts that are not traditionally used as data sources. Examples include raster images, web pages, vector files, and photographs. This showpiece presents how iVoLVER, the Interactive Visual Language for Visualization Extraction and Reconstruction, provides support in such settings. We briefly describe the overall construction approach of the tool in scenarios where different digital artifacts are used to compose interactive visuals. All of this becomes possible by using the data extraction capabilities of iVoLVER together with the elements of its visual language.</p