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An essential primitive for an efficient research ecosystem is\emph{partial-progress sharing} (PPS) -- whereby a researcher sharesinformation immediately upon making a breakthrough. This helps preventduplication of work; however there is evidence that existing reward structuresin research discourage partial-progress sharing. Ensuring PPS is especiallyimportant for new online collaborative-research platforms, which involve manyresearchers working on large, multi-stage problems.  We study the problem of incentivizing information-sharing in research, undera stylized model: non-identical agents work independently on subtasks of alarge project, with dependencies between subtasks captured via an acyclicsubtask-network. Each subtask carries a reward, given to the first agent whopublicly shares its solution. Agents can choose which subtasks to work on, andmore importantly, when to reveal solutions to completed subtasks. Under thismodel, we uncover the strategic rationale behind certain anecdotal phenomena.Moreover, for any acyclic subtask-network, and under a general model ofagent-subtask completion times, we give sufficient conditions that ensure PPSis incentive-compatible for all agents.  One surprising finding is that rewards which are approximately proportionalto perceived task-difficulties are sufficient to ensure PPS in all acyclicsubtask-networks. The fact that there is no tension between local fairness andglobal information-sharing in multi-stage projects is encouraging, as itsuggests practical mechanisms for real-world settings. Finally, we show thatPPS is necessary, and in many cases, sufficient, to ensure a high rate ofprogress in research.

Re-incentivizing Discovery: Mechanisms for Partial-Progress Sharing in Research