In the talk, illustrated through the slides below, Felice made the argument that images and figures are first class intellectual objects — and should be considered just as important as words in publication, learning, and thinking.
In her abstract, Felice summarizes as follows:
Visual representation of all kinds are becoming more important in our ever growing image-based society, especially in science and technology. Yet there has been little emphasis on developing standards in creating or critiquing those representations. We must begin to consider images as more than tangential components of information and find ways to seamlessly search for accurate and honest depictions of complex scientific phenomena. I will discuss a few ideas to that end and show my own process of making visual representations in sciences and engineering. I will also make the case that representations are just as “intellectual” as text.
The talk presented many visual representations from a huge variety of scientific domains and projects. Across these projects, the talk returned to a number of key themes.
When you develop a visual representations it is vital for you to identify the overall purpose of the graphic (for example, whether it is explanatory or exploratory); the key ideas that the representation should communicate about the science; and the context in which the representation will be viewed.
There are a number of components of visual design that are universal across subject domain, including: composition, abstraction, coloring, and layering. And small, incremental refinements in the representation can dramatically improve the quality of the representation.
The process of developing visual representations engages both students and researchers in critical thinking about science; and this process can be used as a mechanism for research collaboration.
Representations are not the science, they are communications of the science; and all representations involve design and manipulation. Maintaining scientific integrity requires transparency about what is included, what is excluded, and what manipulations were used in preparing the representation.
In my observation, information visualization is becoming increasingly popular, and tools for creating visualizations are increasingly accessible to a broad set of contributors. Universities would benefit from supporting students and faculty in visual design for research, publication, and teaching; and in supporting the discovery and curation of collections of representations.
Library engagement in this area is nascent, and there are many possible routes for engagement. Library support for scientific representations is often limited — especially compared to the support for pdf documents or bibliographic citations. I speculate that there are at least five productive avenues for involvement.
Libraries could provide support for researchers in curating personal collections of representations; in sharing them for collaboration; and in publishing them as part of research and educational content. Further researchers have increasing opportunities to cycle between physical and virtual representations of information, thus support for curating information representations can dovetail with library support for making and makerspaces.
Library information systems seldom incorporate information visualization effectively in support of resource discovery and navigation. New information and visualization technologies and methods offer increased opportunities to make library more accessible and more engaging.
Image-based searching is another area that demonstrates that search is not a solved problem. Image-based search provides a powerful means of discovering content that is almost completely absent from current library information systems.
Libraries have a role in helping researchers to engage in evolving systems of credit and attribution. For example, the CredIT taxonomy (which we helped to develop, and which is being adopted by scholarly journals such as Cell and PLOS) provides a way to formally record attribution for those who contribute scientific visualizations.