Scientific and Ethical Implications of the Emerging Data Sciences for the Interpretive Social Sciences: An Interdisciplinary Workshop: Arlington, VA - Fall 2019

该研讨会探讨了开放科学倡议的科学和伦理影响，并呼吁为理解社会科学定性研究中的“数据”而提高研究透明度。在以前NSF资助的项目的基础上，参与者将考虑到数据管理的最新发展，包括对数据收集、共享和分析的检查，考虑数据的演变和相互竞争的意义。这将通过召集开放科学的支持者和对可能和适当管理质量数据有不同观点的学者，包括伦理学家、社会科学家、联邦和私人资助机构的代表以及公共政策学者来实现。与会者将探索广义上的新兴数据科学如何推动解释性社会科学的优先事项，并重塑我们对它们的理解。它还将确定更好地体现社会科学方法多元化的关键挑战，包括对“数据”的相互竞争的描述以及对管理定性研究结果的相关影响。讲习班的成果将为科学政策和资助界在人种学/人文科学领域的科学和数据管理方面的决策提供信息。这个研讨会考虑了广泛的、通常是由技术驱动的数据管理方法的后果，以及依赖数据的行业对定性社会科学研究日益增长的影响。研讨会的一个主要目标是系统地阐明推动开放科学和数据管理在哪里以及如何与定性社会科学研究相兼容，以及在哪里可能不兼容。在这样做的过程中，研讨会将研究社会科学中不同的“数据”概念的含义，并邀请人们讨论这些通常未被承认和低估的差异如何在相互竞争的意义生成过程中发挥作用，包括如何收集、分类、解释和归档数据，以及每个过程的伴随伦理影响。这一奖项反映了NSF的法定使命，并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，被认为值得支持。

This workshop explores the scientific and ethical implications of open science initiatives and calls for research transparency for understandings of "data" in qualitative social science research. Building on prior NSF-funded projects, participants will consider evolving and competing meanings of data given recent developments in data management, including examinations of data collection, sharing, and analysis. This will be accomplished by drawing together proponents of open science and scholars with diverse perspectives about possible and appropriate management of qualitative data, including ethicists, social scientists, representatives from federal and private funding agencies, and public policy scholars. Participants will explore the ways emerging data sciences, broadly conceived, are driving priorities for the interpretive social sciences and reshaping our understanding of them. It will also identify key challenges to better representing the methodological pluralism of the social sciences, including competing accounts of "data" and associated implications for managing qualitative research results. Workshop outcomes will inform decision-making in the science policy and funding communities regarding science and data management in the ethnographic/humanistic social sciences. This workshop considers consequences of widespread, often technologically-enabled approaches to data management and the rising influence of data-reliant industries for qualitative social science research. A primary workshop goal is to systematically articulate where and how the push towards open science and data management is compatible with qualitative social science research and where it might not be. In so doing, the workshop will examine the implications of different conceptualizations of "data" across the social sciences, and invite discussion of how these often unacknowledged and underplayed differences figure in competing processes of sense-making, including how data are collected, classified, interpreted, and archived, and the concomitant ethical implications of each of these processes.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.