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

这项研究将运用在生物学中获得的协调机制知识，更好地理解和改进利用信息和通信技术进行对等生产的协调。对等生产已经成为一股重要的经济力量。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，促进对等生产的方式可能会对支持发明的基础设施产生广泛的影响，进而对经济产生影响。更普遍的是，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、伙伴关系、非营利组织和政府机构产生影响。这项研究不仅将寻求加深对对等生产的理解，而且还将建立工具和界面，以寻求提高在线社区的集体创造力。模型、数据集和伴随的模拟将有两个目的：作为明确的知识形式供其他研究人员重用，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，开源和对等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。对等生产被描述为耻辱，因为协作通常不是通过明确的计划对话发生的，而是通过由先前的交互触发的交互发生的，所有这些交互都集中在主要的技术工件、某种形式的文本或源代码上。这项工作将分三个阶段进行：(1)进行研究，检查交互率如何影响对等生产网络（如维基百科）的生产率；(2)首先通过观察研究，然后通过实验，将数学生物学的动态模型应用于对等生产；(3)测试对等生产的替代接口，并将研究结果应用于其他协同编辑环境。

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.