Ben Gincely uses the study of his field to approach a much broader, and transdisciplinary issue than my topic of automatic waste sorting. In investigating neural engineering, Gincely investigates an issue in not only a vitally applicable realm, but one in which further research is demanded. The nature of this topic seems to be reflected in the approach to his problem statement, which has a greater emphasis on providing the scientific context of neural engineering, than the societal context I provided in my own annotated bibliography.
The XML content of Gincely’s citations had a higher degree of complexity than my own. He leveraged the title ‘level’ attribute, in addition to providing untagged text.
Of note for the annotation content, Gincely opened each of his entries with more in-depth research on the people and institutions behind each source. Additionally he managed to maintain a smoother transitional effect between sections, aided by the choice of not forcing every element attribute variant into each entry. This is primarily seen in his forgoing of the summary ‘interpretation’ and relevance ‘value statement’ attributes.
Lastly of note on semantics: Whereas in my work I used inconsistent (and in some cases incomplete) citation styles, Gincely’s work was of more proper formatting. Unfortunately I hadn’t thought to look at the provided examples earlier on in the project, however in hindsight I should have corrected myself to fit a description closer to Gincley’s. Additionally, the flow of Gincely’s annotations provided for a more fluid reading experience, however I am unsure that I would have been able to accomplish the same without breaching the 200 word limit.
