Organizing Algorithms
The application of machine learning algorithms in libraries and information organizations is a topic of growing importance to the information science community. The inverse, though, is much less discussed. This poster explores current applications of best practices in information organization to algorithm environments. As the number of low-technical users of algorithms and their associated output continues to grow, adherence to standards of information organization is becoming increasingly important. Current standards, such as generous tools and FAIR data principles, are discussed to evaluate current algorithm environments. GitHub and Hugging Face serve as primary examples to show how current platforms meet and fall short of these standards. I find several opportunities for improvement in the organization of information on these platforms, including leveraging contributions from existing open-source communities.