CyberSEES: Type 1: Fostering Non-Expert Creation of Sustainable Polycultures through Crowdsourced Data Synthesis

Cyber​​SEES：第 1 类：通过众包数据合成促进可持续多元文化的非专家创造

• 批准号: 1442749
• 负责人: William Tomlinson
• 金额: $ 39.88万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-15 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1442749&HistoricalAwards=false
• 关键词: CyberSEES; Type; Fostering; Non; Expert

This project integrates research in computing and sustainability science with the goal of enabling a new approach to sustainable food security. The PIs propose to combine cyber-human systems and crowdsourcing research with the science of agroecology with two main research goals: 1) to develop an understanding of how online design tools may contribute to sustainability through enhanced local food production, and 2) to utilize the population of a plant species database as an instance of a class of problems amenable to intelligent crowdsourcing, and pioneer new knowledge in crowdsourcing optimization. As part of this project, the research team will design, build, deploy, and evaluate the Sustainable Polyculture Composer, an online software tool to aid in the design of small-scale plant-based agricultural ecosystems (e.g., back yard food forests). Long-term food security is central to sustainability. US food supply chains contribute to global change and are vulnerable to its impacts. Large numbers of small-scale, sustainable, local food production systems could help ensure food security in the face of global change, and could help reduce the environmental impacts of the US food supply. Unfortunately, many efforts at local food production (e.g., back yard gardens) require significant inputs such as water and fertilizer. Effective tools and techniques to encourage novices to begin growing their own food in sustainable ways are lacking. The work will contribute to long-term food security and offer lessons, concepts, methods, and software tools that may be transferable to other sustainability challenges. In addition, the computing research will provide an example that can be generalized to other efforts to more effectively integrate knowledge that is distributed across many people.

该项目整合了计算和可持续性科学的研究，旨在实现可持续粮食安全的新方法。PI建议将联合收割机网络人类系统和众包研究与农业生态学结合起来，主要研究目标有两个：1）了解在线设计工具如何通过提高当地粮食生产来促进可持续性，2）利用植物物种数据库的种群作为适合智能众包的一类问题的实例，并开拓众包优化方面的新知识。作为该项目的一部分，研究团队将设计、构建、部署和评估可持续多元文化Composer，这是一种在线软件工具，可帮助设计小规模基于植物的农业生态系统（例如，后院食物森林）。长期粮食安全是可持续性的核心。美国的食品供应链对全球变化做出了贡献，并容易受到其影响。大量小规模、可持续的地方粮食生产系统可以帮助确保全球变化中的粮食安全，并有助于减少美国粮食供应对环境的影响。不幸的是，当地粮食生产的许多努力（例如，后院花园）需要大量的投入，例如水和肥料。缺乏有效的工具和技术来鼓励新手开始以可持续的方式种植自己的食物。这项工作将有助于长期的粮食安全，并提供经验教训，概念，方法和软件工具，可以转移到其他可持续性挑战。此外，计算研究将提供一个可以推广到其他努力的例子，以更有效地整合分布在许多人身上的知识。