This document discusses challenges and considerations for open data sharing and collaborative analysis. It addresses issues such as [1] balancing top-down and bottom-up hypothesis generation, [2] distinguishing relevant patterns from false correlations, and [3] expanding the space of hypotheses evaluated beyond standard datasets and tools. The document also questions [4] when to abandon hypotheses as non-informative or indeterminate, and [5] how to establish rules for sharing data and crediting contributions in an open collaboration environment.