CHS: Small: Collaborative Proposal: Understanding and Improving Implicit Coordination in Peer Production Networks

这项研究将应用在生物学中获得的协调机制的知识，以更好地理解和改善使用信息和通信技术的同行生产的协调。同行生产已成为一种重要的经济力量。它产生的知识基础设施是教育和研究机构许多方面的基础。因此，促进同行生产的方式可能会对支持发明的基础设施产生广泛影响，进而对经济产生影响。更普遍地说，协作编辑被用于大多数管理知识的行业，因此这方面的进展可能会对公司、合作伙伴、非营利组织和政府机构产生影响。这项研究不仅将寻求增加对同行生产的理解，而且还将建立旨在提高在线社区集体创造力的工具和界面。模型、数据集和伴随的模拟将出于两个目的而构建：作为其他研究人员重复使用的明确形式的知识，以及作为教育材料。调查将通过一系列观察性研究和实验进行，以探索通过生物学领域的研究发现的协调机制如何为人类行为提供有用的见解。最近的研究表明，开源和同行生产网络中的协调至少可以部分地用污名化来解释，这是生物学家发现的一个过程，在这个过程中，工作的痕迹成为产生更多工作的条件或信号。 同伴生产被描述为是耻辱的，因为协调通常不是通过明确的计划对话发生的，而是通过以前的互动触发的互动，所有这些都集中在主要的技术工件上，某种形式的文本或源代码。 这项工作将分三个阶段进行：（1）进行研究，研究互动率如何影响维基百科等同行生产网络的生产力;（2）将数学生物学的动态模型应用于同行生产，首先通过观察研究，然后通过实验，以及（3）测试同行生产的替代接口，并将研究结果应用于其他协作编辑环境。

This research will apply knowledge about coordination mechanisms that was gained in biology to better understand and to improve coordination in peer production using information and communication technologies. Peer production has emerged as an important economic force. It produces knowledge infrastructure that underlies many aspects of educational and research institutions. Thus, ways of furthering peer production may have broad impacts on the infrastructure that supports invention, and in turn on the economy. More generally, collaborative editing is used in most industries that manage knowledge, and so progress on this front may have impacts in corporations, partnerships, non-profits, and government institutions. The research will not only seek an increased understanding of peer production but also will build tools and interfaces that seek to improve the collective creativity of online communities. Models, data sets, and accompanying simulations will be built for two purposes: as explicit forms of knowledge for reuse by other researchers, and as materials for education. The investigation will proceed through a set of observational studies and experiments, to explore how coordination mechanisms that have been discovered through studies in the field of biology may provide useful insights into human behavior. Recent studies have indicated that coordination in open source and peer production networks can be explained at least in part by stigmergy, a process discovered by biologists in which the traces of work become conditions or signals that generate more work. Peer production is described as being stigmergic because coordination often happens not through explicit planning conversations, but through interactions triggered by previous interactions, all centered on the primary technical artifact, some form of text or source code. The work will proceed in three phases: (1) performing studies that examine how interaction rates affect productivity in peer production networks such as Wikipedia; (2) applying dynamic models from mathematical biology to peer production, first through an observational study and then through an experiment, and (3) testing alternative interfaces for peer production and applying the findings to other collaborative editing environments.