The digital research studio is intended to provide resources for faculty and students interested in presenting their research in digital space. The digital toolbox contains tutorials for using digital tools. The digital bookshelf has some helpful readings and planning documents. We plan to add useful files to this space over time.
Digital Research Toolbox
Before you begin, you should establish accounts that can hold digital data. Pictures (e.g., Flickr), video (e.g., YouTube), digital documents (Google Docs), and the like. Your digital data must be “public” for these programs to access your data. For instance, if your Flickr photos are “private,” your software will not be able to “find” the data on the internet.
If you are using OMEKA, make sure that the data is “public” for the same reason. Even if you are using OMEKA, however, having these accounts will be indispensable for your work.
The resources in the toolbox are intended to help students and faculty using Omeka and other digital tools. The general philosophy for learning or teaching these tools proceed in two steps:
- Scaffold–introduce yourself or students to an approach that focuses on learning the intellectual value of the approach. Learners will focus most of their effort on the content and substantive task rather than the intricacies of complex software. Also, scaffold assignments. Begin with something that you or a student already have some mastery over (like one’s personal biography) and then move on to more complex material
- Scale up–move on to more complex software that allows for more flexibility, cross-platform integration, and attractive displays.
For instance, if you are interested in using maps to display digital data, begin with Story Map before moving on to Neatline.
Beginning with complex tasks and material may lead to frustration, failure, and “negative feedback.” It may seem like it “takes longer” to adopt this two-step approach, you and/or your students will save time by learning valuable tools during the scaffolding stage that help to iron out wrinkles once you scale up to a more complex presentation of your data.