While open access publishing is effectively broadening access to scientific research, the problem of making sense of the volumes of new information being published remains at large. Traditional curation methods like peer-reviewed journals are failing to keep pace, resulting in unprecedented information overload and knowledge fragmentation. We contend that making sense of science requires open access to diverse sources of scholarly sensemaking data. Sensemaking data are the digital traces of sensemaking processes, including explicit annotations (tags, votes, ratings) and commentary made by researchers, as well implicit behavioral data generated through app usage (reference managers, etc). Crucially, sensemaking data is currently scattered and siloed across a multitude of apps and formats, and increasingly enclosed by platforms for profit. We propose Open Source Sensemaking, an interoperable and decentralized annotation network, enabling researchers to record, own and share their sensemaking data, thus contributing to collective sensemaking while remaining resilient to platform capture.