This morning we discussed some steps to open up data. These suggestions were distilled from the Open Knowledge Foundation’s Open Data Handbook by instructor Jim Smith: https://www.dhdata.org/dhdata/datasets/1-how-to-open-up-data/index.html
One of the main points was that DH projects need to start small, and there should be a series of steps or stages for development, even in the smallest projects. Part of this idea of starting small includes limiting the size of the initial dataset. Small datasets can still be helpful to wider communities. If the dataset isn’t moving in the correct direction, its small size can allow for redirection before too much time has been invested.
The dataset for Theatre Finder (a DH project about historic theaters) is written in JSON, but it could be altered to be JSON-LD without destroying or having to rewrite the original database. Coding the dataset as JSON-LD would make the information in Theatre Finder much more usable, connecting it to the wider networks of linked data across the web. Theatre Finder is a good candidate for becoming an authority dataset, or ontology. Theatre Finder didn’t begin with this in mind, but the dataset information is comprehensive and is widely used.
It’s important to consider that database ontologies are generally created by the people who use and need the data on a regular basis. Before creating a dataset DH professionals need to ask the question, “who can and will use this data?” This question is important, because these groups will also be the ones to contribute to the dataset. Stability is also a factor of community involvement. Datasets are constantly changing, not just by adding information to them, but by also reconsidering definitions and vocabularies inline with social and cultural change.