Code 4 Coll Dev
"More than just deciding what to buy, modern collection development for libraries occupies an increasingly complex space, a space structured by forces like predatory vendor pricing, institutional pressures on research and teaching, the high cost of physical storage, and the migration from print to digital media. As we strive to navigate this space with collaborative, transparent, and data-savvy decisions about our collections, we need tools and processes adequate to the task. This presentation addresses this need by way of a question: What can collection development learn from software development? At the George Washington University, we have been using code libraries like pandas (for Python) and D3 (for Javascript) to harvest, analyze, and visualize data about our collections in ways that promote improved workflows and decision-making. For instance, a lightweight data warehouse and dashboard allows stakeholders to track allocations and expenditures, providing functionality not available in our ILS (source code at https://github.com/dolsysmith/voyager-dashboard). Likewise, agile methods supply a framework for iterative and collaborative work on collection development projects, breaking the mold of relatively solitary acquisition under a horizon of diminishing returns, in order to make more strategic investments of money and staff time. Examples from our use of these tools and methods will highlight how synergies between collection development and software development can help us tackle the challenges and leverage the opportunities libraries face in the twenty-first century."
