In standard computer programming, iteration is one of the first things you learn and is essential for building a successful program. While Digital Humanities projects (including Digital Collections) may not be your standard program, it is still incredibly important to implement the iterative process. This is clear from Paige Morgan’s advice on how to get a Digital Humanities project off the ground, as much of the advice she gives involves repeating your project multiple times. She writes, “Talk to people about your project. Write about it. Apply to give lightning talks and/or conference papers about what you want to do.” This technology free advice represents iterating through your idea multiple times in different formats, getting closer and closer to the end product you’re looking for (the same is true in an iterative loop in programming, your computer will execute a line of code as many times as it needs to until it gets to the answer you specify) When she writes “When you’re building these small prototype versions, be easy on yourself.” and “Know that the platform or tool which which you build your project may change. Don’t commit to one right away. Experiment.” both of these pieces of advice involve building your project multiple times, experimenting with the the platform and the feel of it, maybe the methodology.
The advice that Morgan gives in her blog is important to remember when building smaller projects as well and using out of the box platforms or software. It certainly is true for Omeka and Scalar. From my point of view, Omeka seems more straightforward in terms of learning the tool, but may require more iterations through the actual data or items to determine what it is that you want to portray with your Omeka site. What in your data will be an item? What will be a collection and what will be an exhibit? This summer I worked on The Humanities Moments Project at the National Humanities Center an exciting project that is run on Omeka. The center the describes the project and mission as the following:
By illustrating the importance of the humanities for people from all walks of life, the project seeks to reimagine the way we think and talk about the humanities.
By highlighting their transformative power, the Humanities Moments project illuminates how our encounters with the humanities fuel the process of discovery, encourage us to think and feel more deeply, and provide the means to solve problems as individuals and as a society.
In the case of this project, the individual moment is categorized as an item. Some of the items are than put into collections that indicate where they came from – say for example NHC Staff, that is readily visible from the backend but less so from the front. If one clicks on a moment that is in a collection it is visible at the bottom near the tags, and can be clicked on to see others in the collection. The exhibits are made up of items and represent a theme such as Teachers, but do not necessarily come in from the same place (and thus are not a collection). This could have been done a completely different way, and it’s entirely possible near the beginning of the project it was. It was only through iterating through possibilities and keeping the mission that I mentioned above in mind that they came to this schema.
The same iterative process applies to Scalar, although in my mind it applies more to learning the platform then it does to the project. Scalar’s interface is slightly more difficult to figure out and thus, unless you want to read all of the documentation, it is easier to experiment through the platform. To try and implement part of a collection into the site, but then continue to work through all of the feature that are available to transform that collection.
I don’t feel that I can make a judgement on which of the two platforms we’ve looked at, Omeka and Scalar, is better for a digital collection- I believe it’s truly vital to a digital humanities project, as Paige Morgan says, to iterate through multiple platforms and to be always trying something new to get your project as close as possible to the end goal. Maybe it’ll get to the perfect project, maybe it won’t, ultimately though one can only find out by iterating through continually.