数据及其内容：数据集开发和在机器学习研究中的应用综述
Data and its (dis)contents: A survey of dataset development and use in machine learning research
摘要：
数据集在机器学习研究的进步中发挥了基础性作用。它们构成了我们设计和部署模型的基础，也是我们进行基准测试和评估的主要媒介。此外，我们收集、构建和共享这些数据集的方式也为该领域追求的问题和算法开发中探索的方法提供了信息。然而，最近从广泛的角度开展的工作揭示了数据集收集和使用方面的主要做法的局限性。在本文中，我们调查了许多关于我们在机器学习中收集和使用数据的方式的问题，并主张对数据进行更谨慎和彻底的理解，以解决该领域的一些实际和伦理问题。
英文摘要：
Datasets have played a foundational role in the advancement of machine learning research. They form the basis for the models we design and deploy, as well as our primary medium for benchmarking and evaluation. Furthermore, the ways in which we collect, construct and share these datasets inform the kinds of problems the field pursues and the methods explored in algorithm development. However, recent work from a breadth of perspectives has revealed the limitations of predominant practices in dataset collection and use. In this paper, we survey the many concerns raised about the way we collect and use data in machine learning and advocate that a more cautious and thorough understanding of data is necessary to address several of the practical and ethical issues of the field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
