Large Database to Explore Rise of Social Complexity

十多年来，考古学家一直在开发基于经验的模型，并解释复杂的，多原因和后果，现实世界的过程。该项目将通过测试一个创新模型来促进对国家和城市化起源的理解，该模型采用了最近开发的分析工具和异常丰富和庞大的数据集。这种新方法不是只关注一个州或一个城市，而是1）跟踪多个重要机构-州，城市，地区，当地社区，寺庙组织，市场和农业机构-因为这些机构在数千年的时间里不断变化和发展; 2）同时跟踪这些制度变化，跨越多个相邻的社会，有不同的文化，语言，和自然环境，但众所周知，保持了高水平的社会间的互动。调查人员将收集来自150多个城市的6000多个考古遗址的更新和旧的考古数据。这些遗址来自多个时期，包括狩猎采集者的岩石艺术、早期村庄、城镇、城市、防御工事、房屋、公共建筑、灌溉运河和农业梯田。这些信息最初由多个研究小组收集。这些研究采用了相同的基本方法，因而具有高度的可比性。该项目将建立并公开提供世界上最全面的考古数据集之一，可用于各种主题，包括人口统计学，文化生态学，工艺专业化和经济实践，战争，新石器时代革命，社区，城市化，农业，弹性，政治演变，崩溃，普通生活，财富不平等和宗教机构的发展。该项目将以可用的格式对信息进行存档和整理，以便不仅研究人员，而且教师、学生、当地社区、文化遗产利益攸关方等都能获得这些信息，核心研究假设是：1）城市化、国家和其他重要的社会制度由于社会间的相互作用而随着时间的推移而协调发展，但2）由于土壤和水等关键农业变量的变化以及这些资源的社会管理方式的差异，每个地区的社会发展不同。模型的构建将使用多标量（网站，本地，区域，多区域）的方法，以及最近的考古应用的制度分析和集体行动理论。收集和管理信息档案需要将旧数据（超过100，000页的野外记录，人工制品描述，地图和照片）提升到现代标准，特别是在地理参考领域，以提高其可用性，可访问性，实用性和科学研究，教育和管理目的的价值。该项目创建的在线档案将有利于K-12和大学水平的教学，通过提供真实世界情况的数据集和模块，用于教学基本概念，如数字，科学方法，空间和时间尺度，连续性和随时间的变化，以及统计学，人口统计学，地理信息系统和生态学的更高级应用。最后，这项工作将吸引学者，研究生和本科生参加培训，创建档案，并使用这些资源，特别是那些来自代表性不足的群体。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

For over a decade archaeologists have been developing empirically based models and explanations for complex, multiple-cause-and-consequence, real-world processes. This project will advance understanding of the origins of the state and urbanism by testing an innovative model that employs recently developed analytical tools and an unusually rich and large dataset. Instead of focusing exclusively on one state or city, this new approach 1) tracks multiple important institutions—states, cities, districts, local communities, temple organizations, markets, and agricultural institutions—as these varied and developed over a span of millenia; and 2) simultaneously tracks these institutional changes across multiple, neighboring societies that had differing cultures, languages, and natural environments yet are known to have maintained a high level of inter-societal interaction. The investigators will assemble newer and older archaeological data on more than 6000 archaeological sites from over 150 municipalities. The sites are from multiple time periods and include hunter-gatherer rock art, early villages, towns, cities, fortifications, houses, public architecture, and irrigation canals, and agricultural terraces. This information was originally gathered by multiple research groups. The studies had the same basic underlying methodology, permitting a high degree of comparability. This project will build and make publicly available one the most comprehensive archaeological datasets in the world useful for a variety of topics including demography, cultural ecology, craft specialization and economic practices, warfare, the Neolithic Revolution, communities, urbanism, agriculture, resilience, political evolution, collapse, ordinary lives, wealth inequality, and the development of religious institutions. The project will archive and curate the information in useable formats so that it will be available not just to researchers but to teachers, students, local communities, cultural heritage stakeholders, etc., for years to come.The central research hypothesis is that 1) urbanism, the state, and other important social institutions developed concordantly over time because of inter-societal interaction, but 2) differently in each regional society because of variation in the key agricultural variables of soil and water and differences in the way these resources were socially managed. Model construction will use a multiscalar (site, local, regional, multiregional) method, and recent archaeological applications of institutional analysis and collective action theory. Assembling and curating the information archive requires bringing older data (over 100,000 pages of field notes, artifact descriptions, maps, and photographs) up to modern standards, especially in the area of georeferencing, to enhance its availability, accessibility, utility, and value for scientific research, educational, and management purposes. The online archive created by this project will benefit instruction at K-12 and University levels, by providing datasets and modules of real-world situations for use in teaching basic concepts such as number, scientific method, spatial and temporal scales, and continuity and change over time, and more advanced applications in statistics, demography, GIS, and ecology. Finally, this work will engage scholars, graduate students, and undergraduates in training, creation of the archive, and use of these resources, particularly those from underrepresented groups.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.