This Research Topic in Frontiers in Computational Neuroscience collects visions for a future system of open evaluation. Because critical arguments about the current system abound, these papers will focus on constructive ideas and comprehensive designs for open evaluation systems. Design decisions include: Should the reviews and ratings be entirely transparent, or should some aspects be kept secret? Should other information, such as paper downloads be included in the evaluation? How can scientific objectivity be strengthened and political motivations weakened in the future system? Should the system include signed and authenticated reviews and ratings? Should the evaluation be an ongoing process, such that promising papers are more deeply evaluated? How can we bring science and statistics to the evaluation process (e.g. should rating averages come with error bars)? How should the evaluative information about each paper (e.g. peer ratings) be combined to prioritize the literature? Should different individuals and organizations be able to define their own evaluation formulae (e.g. weighting ratings according to different criteria)? How can we efficiently transition toward the future system?
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