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Digital HUAC: MVP Post

Over the course of this project so far, and in relation to the feedback that we’ve been receiving, we have scaled up and down our goals and expectations. It has been both humbling and empowering to consider everything we can do within the constraints of a single semester project. When asked to brainstorm our minimum viable product (MVP) this week, over a conference call we all agreed on the following:

– a central repository with basic search functionality that stores our corpus of 5 transcripts.

– a database that can be scaled.

What does this mean, and how does it differ from our current project goals?

We are attempting to generate a platform that connects a relational database to a robust search interface and utilizes an API to allow users to extract data. We envision Digital HUAC to be the start of a broader effort to organize HUAC transcripts and allow researchers and educators access to their every character. By allowing advanced searches driven by keywords and categories, we seek to allow users to drill down into the text of the transcripts.

Our MVP focuses on storing the transcripts in a digital environment that returns simple search results: in absence of a robust search mechanism, users would instead receive results indicating, for example, that a sought after term appeared in a given transcript and not much more.

Our MVP must lay out a model for a scalable database. We are still very much figuring out exactly how our database will operate, so it is hard to fully commit to what even a pared-down version of this would look like. But we know that the MVP version must work with plain text files as the input and searchable files as the output.

Generating an MVP has been a useful thought experiment. It has forced us to hone in on the twin narrative and technical theses of this project: essentially, if everything else was stripped away, what must be left standing. For us, this means providing basic search results and a working model of a relational database that, given appropriate time and resources, could be expanded to accommodate a much greater corpus.