We explore how astronomers take observational data from telescopes, process them into usable scientific data products, curate them for later use, and reuse data for further inquiry. Astronomers have invested heavily in knowledge infrastructures - robust networks of people, artifacts, and institutions that generate, share, and maintain specific knowledge about the human and natural worlds. Drawing upon a decade of interviews and ethnography, this article compares how three astronomy groups capture, process, and archive data, and for whom. The Sloan Digital Sky Survey is a mission with a dedicated telescope and instruments, while the Black Hole Group and Integrative Astronomy Group (both pseudonyms) are university-based, investigator-led collaborations. Findings are organized into four themes: how these projects develop and maintain their workflows; how they capture and archive their data; how they maintain and repair knowledge infrastructures; and how they use and reuse data products over time. We found that astronomers encode their research methods in software known as pipelines. Algorithms help to point telescopes at targets, remove artifacts, calibrate instruments, and accomplish myriad validation tasks. Observations may be reprocessed many times to become new data products that serve new scientific purposes. Knowledge production in the form of scientific publications is the primary goal of these projects. They vary in incentives and resources to sustain access to their data products. We conclude that software pipelines are essential components of astronomical knowledge infrastructures, but are fragile, difficult to maintain and repair, and often invisible. Reusing data products is fundamental to the science of astronomy, whether or not those resources are made publicly available. We make recommendations for sustaining access to data products in scientific fields such as astronomy.
翻译:我们探索天文学家如何从望远镜中获取观测数据,如何将这些数据处理成可使用的科学数据产品,如何将其加工成可使用的科学数据产品,如何将其整理成可再利用的数据。天文学家对知识基础设施进行了大量投资,这些知识基础设施包括:由人、文物和机构组成的强大网络,以及产生、分享和保持关于人类和自然世界的具体知识的机构。根据十年的访谈和人种学,本篇文章比较了三个天文学群体如何采集、处理和归档数据,以及对于谁。斯隆数字天空调查是一个任务,它拥有专门的望远镜和仪器,而黑洞小组和化天文组(包括化名词组)则以大学为基础,由调查人员牵头开展合作。 研究结果分为四个主题:这些项目如何开发和维护其工作流程;它们如何获取和储存其数据;它们如何在一段时间内使用和再利用数据产品。我们发现天文学家在被称为管道的软件中为其研究方法编码困难。 我们的人工智能测量系统经常帮助定位望远镜、删除文物、校正仪器,并且完成大量验证工作。这些数据的观察工作可能使这些基本数据产品成为新的科学产品。