SGER - Research Methods for Contemporary History of Computing

这是一项发展和测试新方法的提案，用于当代计算史的研究。这些都是探索性的，是为了克服现有研究方法中固有的“自上而下”的偏见而提出的，这些研究方法主要（甚至完全）从该领域的先驱或领军人物那里收集信息。这些被提议的研究方法将以几种不同但互补的方式，为更广泛和更多样化的计算发展参与者提供见解、信息和文档。当NSF的FastLane系统作为学术网络基础设施的早期模型进行广泛的历史研究时，考虑到这些新的研究方法。与《FastLane》的8到10名“核心”NSF设计师一起制作传统的口述历史是很容易想象的。但是，研究工具根本无法对大量不同的FastLane用户（例如，NSF遗留员工、赞助项目管理人员和主要研究人员）进行可行的研究。传统的口述历史研究需要耗费大量时间，需要数百名用户参与，这需要一个超大规模的研究团队。此外，有一个紧迫的问题是，NSF是否成功地设计了一个系统，可以鼓励——而不是挫败——来自没有一流计算资源的大学（特别是HBCU和epscr州立大学的PI）的PI提交的提案。从众多PI和SPA员工那里收集大量不同的数据集对于解决后一个问题是必要的。这些新的研究问题需要新的研究工具和方法。更广泛的影响本项目中提出的研究工具具有重大潜力，可以改变计算史以及密切相关的当代科学、技术、工程和医学史（STEM）领域的现有研究方法和实践。这两个工具——一个基于网络的访谈平台和一个互补性的“wiki”网站，用来引出和记录参与者的不同观点——是开发潜在的变革性研究方法的有希望的尝试。研究STEM领域的学者们越来越意识到，要正确理解科学技术的进步，就需要调查机构和组织的动态，包括研究普通成员的成就、态度和观点，而不仅仅是研究少数领导人物。通过收集更大、更多样化的定性数据集，这些新颖的研究工具和方法甚至可以改变公众对科学和工程的更广泛理解。

This is a proposal to develop and test new methods for conducting research in the history of contemporary computing. These are exploratory in nature, and are proposed in an effort to overcome the "top down" bias inherent in existing research methods that collect information preponderantly (or even exclusively) from pioneering or leading figures in the field. These proposed research methods will, in several distinct but complementary ways, provide insight, information, and documentation on a much wider and more diverse set of participants in the evolution of computing.Consideration of these new research methods was prompted when planning for a wide-ranging historical study of NSF's FastLane system as an early model of scholarly cyberinfrastructure. Doing traditional oral histories with the eight to ten "core" NSF designers of FastLane was easy to envision. But research tools were simply not available to make a feasible study of the large and diverse set of FastLane users (e.g., NSF legacy staff, staff of sponsored projects administrations, and principal investigators). Doing traditional time-intensive oral histories with hundreds of users would require an unrealistically oversize research team. Moreover, there is a pressing question whether NSF succeeded in designing a system that could encourage - rather than frustrate - proposal submissions by PI's from universities that did not possess top-notch computing resources (especially PI's at HBCU and EPSCoR-state universities). Collecting a large and diverse set of data, from numerous PI's and SPA staff, is necessary to address this latter issue. These new research questions demanded new research tools and methods.Broader ImpactThe research tools proposed in this project have significant potential to transform existing research methods and practices in the history of computing, as well as in the closely related field of contemporary history of science, technology, engineering and medicine (STEM). The two tools - a web-based interview platform and a complementary 'wiki' site set up to elicit and record participants' varied perspectives - are promising attempts to develop potentially transformative research methods. Scholars studying the STEM domain have become increasingly aware that a proper understanding of advances in science and technology requires investigating the dynamics of institutions and organizations, including research on the achievements, attitudes, and perspectives of rank-and-file members, and not merely study of a small number of leading figures. By making possible the collection of larger and more diverse sets of qualitative data, these novel research tools and methods could even transform the broader public understanding of science and engineering.