As our ability to collect long-term acoustical signals grows we face the challenges of analyzing large datasets, ensuring our findings are reproducible, and sharing our work with collaborators. In this talk, we will give an overview of frameworks and tools that can facilitate those tasks. We will show how the Jupyter Notebook environment serves as a hub for quick prototyping, literate programming, interactive analysis and visualization, and a gateway to cloud computing. We will provide examples of processing of larger-than-memory ocean acoustic recordings from the comfort of our own laptop. We will further outline best practices for sharing code and data, and discuss the needs and approaches to achieve scalable, reproducible, and open acoustic research.