Taking “Use Case” Inventory of Available Open Shared Visuals for Teaching and Learning From Searches in the Federated Creative Commons Search (Old)

Abstract

In instructional design, there are a number of common “use cases” for acquiring open-source shared visuals and images: breaking up gray text, driving attention, sparking the imagination, illustrating concepts, providing examples, explaining phenomena, representing reality, depicting models, and others. The instating of licensure and open-source releases has meant that there are literally hundreds of millions of such visuals available online, with varying levels of releases (with variations on the following dimensions: editability, [non]crediting, [non]commercial usages, [non]required sharing, all the way up to full release into the public domain with no restrictions). The federated Creative Commons Search (old) enables exploration and acquisition across a range of web-based platforms for digital images based on text search. When pursuing actual images for particular usage, the abundance of shared imagery suddenly becomes small-set and limited. This work explores this phenomenon and provides some ideas for mitigation.