RR: EAGER: Data Science Literacy for All of Linguistics

像其他社会和行为科学一样，语言科学本质上是数据驱动的，如果语言学要在未来成为一门强大、可靠和可重复的事业，对数据的适当关注是必不可少的。然而，今天许多语言学家仍然不熟悉处理数字数据的当代实践，最近的工作表明，语言学的大多数子领域迫切需要立即进行关于收集、构建、归档、共享、引用和评估语言数据集的标准和工具的教育。虽然一些语言学子领域（语言文档，计算语言学）已经开发出强大的数据处理方法，但对该学科其他领域的扩展仍然不足。该项目将从根本上迅速提高语言学家在语言数据管理方面的所有专业水平，从本科教育到研究生、职业生涯早期和中期培训以及以后。该项目旨在促进整个语言学学科的社会学变革，并将数据处理技能的价值带到语言学教育的前沿，从而促进劳动力发展和潜在的就业机会。更广泛的影响包括博士后学者在数据科学方面的研究机会，可下载的指导方针和指标，用于评估语言数据集的学术招聘，任期和晋升，以及语言数据管理的正式和非正式教育模块的开发和交付。该项目旨在使语言学作为一门数据驱动的社会科学，从对行为的观察中得出关于人类认知和社会结构的推论，能够很好地从可重复研究的原则中受益。目前，科学家产生的数字数据与实际存储或通过可持续存储库或其他方式访问的数据之间存在差距。该团队将通过增加语言科学内部的知识和资源来减少这种差距，这是通过减少结构和知识障碍来改变学科文化的努力的一部分。这些努力包括增加可访问数据管理实践的资源和奖励（如工作、任期和晋升）。项目活动包括几个层次的教育模块的快速发展：针对本科语言学专业的大规模开放在线课程（MOOC），以及在两年多的时间里在几个广泛参加的专业会议上为研究生和教师提供的研讨会。这将提供一些课程和教育模块，旨在培养语言学中可重复研究的数据处理和数据科学的最佳实践，目标群体包括初级学者和职业生涯中期的教师。该项目还将通过开放获取手册、在线格式和会议格式在整个学术语言社区广泛传播培训材料。该项目将数据工作作为一项智力成就，并将促进提高语言学家有效创建、管理、保存、策划和共享语言数据的能力和意愿的方法。

Like other social and behavioral sciences, linguistic science is inherently data-driven, and the proper care for that data is essential if linguistics is to be a robust, reliable, and reproducible endeavor well into the future. However, many linguists today are still unfamiliar with contemporary practices for handling digital data, and recent work has identified an urgent need for immediate education across most subfields of linguistics about standards and tools for collecting, structuring, archiving, sharing, citing and evaluating linguistic data sets. While some linguistics subfields (language documentation, computational linguistics) have developed strong methods for data handling, outreach to the rest of the discipline has been deficient. This project will radically and rapidly increase the literacy of linguistic scientists at all professional levels in the management of linguistic data, from undergraduate education, to graduate, early- and mid-career training and beyond. This project aims to foster sociological change across the entire discipline of linguistics, and to bring the value of data-handling skills to the forefront of linguistics education, enabling workforce development and potential employment opportunities. Broader impacts include research opportunities in the data sciences for a post-doctoral scholar, downloadable materials with guidelines and metrics for evaluating the scholarship of language data sets for hiring, tenure and promotion, and the development and delivery of formal and informal educational modules on linguistic data management. This project is designed to enable linguistics, as a data-driven social science in which inferences about human cognition and social structure are drawn from observations of behavior, is well positioned to benefit from principles of reproducible research. Currently, there is a disparity between how much digital data is produced by scientists and how much of that data has actually been deposited or made accessible through sustainable repositories or other means. The team will reduce this disparity by increasing knowledge and resources within the language sciences as part of efforts to change the discipline's culture by reducing structural and knowledge barriers. These efforts include increasing resources and rewards (such as jobs, tenure, and promotion) for accessible data management practices. Project activities include the rapid development of educational modules at several levels: a massive open online course (MOOC) aimed at undergraduate linguistics majors, and workshops for graduate students and faculty delivered at several widely-attended professional meetings over two years. This will provide a number of offerings and educational modules designed to foster best practices in data handling and data science for reproducible research in linguistics, targeting both junior scholars and mid-career faculty.The project will also disseminate training materials widely throughout the academic linguistic community, through an open-access handbook, online formats, and conference formats. This project takes seriously the contribution of data work as an intellectual achievement in its own right, and will promote methods for increasing the ability and willingness of linguists to effectively create, manage, preserve, curate, and share linguistic data.