Doctoral Dissertation Research: Socio-Technical Practices in the Context of Marcellus Shale Water-Quality Science

概述这个STS博士论文改进补助金将资助研究，以检查对更大，更复杂的环境信息系统的驱动器和当地对污染行业的知识需求之间的紧张关系。计算技术使大数据系统的开发能够分析自然和建筑环境;而非科学家越来越多地参与收集当地社区污染的证据。因此，当普通公民通过参与式环境科学寻求地方授权时，他们对数据收集工作的贡献有助于放大大数据在科学知识主张中的重要性。知识价值该研究是一项研究，志愿者水监测小组应对纽约和宾夕法尼亚州天然气开采的污染威胁。该研究将跟踪五个能力建设组织，这些组织在制定志愿者监测协议、汇总数据和确定如何在公共数据门户中使用数据方面发挥重要作用。该研究解决了几个问题，如解释监测实践的多样性，数据汇总策略，以及能力建设组织使用的数据共享实践，并解释水监测社区在创建标准，共享，水质数据库时所面临的困难。为了回答这些问题，本研究采用了混合方法，包括对多个利益相关者群体成员的定性访谈，以及对能力建设组织之间举行的战略会议的参与观察。这项研究将有助于STS文献的公民科学和越来越多的大数据informations.Broader影响的研究机构。这项研究的结果将有可能影响技术实践和民间社会团体的信息管理战略。它将通过向参与研究的能力建设组织、志愿者团体和其他利益相关者团体提供知识，为志愿水监测社区做出重大贡献。这项研究还将为监管机构和研究科学家的做法提供信息，他们正在寻求有效的方法与即将上线的新信息系统进行互动，以支持公民科学团体。

OverviewThis STS Doctoral Dissertation Improvement Grant will fund research to examine the tension between the drive toward bigger and more complex environmental information systems and local needs for knowledge about polluting industries. Computing technologies have enabled the development of big-data systems to analyze natural and built environments; whereas, non-scientists are increasingly involved in gathering evidence of pollution in their local communities. Thus, while lay citizens seek local empowerment through participatory environmental science, their contributions to data gathering efforts serve to amplify the importance of big data in making scientific knowledge claims.Intellectual MeritThe research is a study volunteer water monitoring groups that respond to pollution threats from natural gas extraction in New York and Pennsylvania. The study will follow five capacity building organizations that play an important role in developing volunteer monitoring protocols, aggregating data, and determining how data will be used in public data portals. The study addresses several issues, such as explaining the diversity of monitoring practices, data aggregating strategies, and data sharing practices that are used by capacity building organizations, and explaining the difficulties water monitoring communities have faced in creating a standard, shared, water-quality database. To answer these questions, the research uses mixed-methods including qualitative interviews with members of multiple stakeholder groups, and participant observation of strategy sessions held between capacity building organizations. The study will contributes to STS literature on citizen science and a growing body of research on big-data informatics.Broader ImpactsThe results of this research will have potential to impact technical practices and information management strategies of civil society groups. It will make significant contributions to volunteer water-monitoring communities by contributing knowledge to capacity building organizations, volunteer groups, and other stakeholder groups that participate in the study. The study will also inform the practices of regulators and research scientists who are seeking effective ways to interact with new information systems that are coming online to support citizen science groups.