Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, Oregon, United States of America.
Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, United States of America.
PLoS Biol. 2021 Mar 26;19(3):e3001129. doi: 10.1371/journal.pbio.3001129. eCollection 2021 Mar.
Decades of reductionist approaches in biology have achieved spectacular progress, but the proliferation of subdisciplines, each with its own technical and social practices regarding data, impedes the growth of the multidisciplinary and interdisciplinary approaches now needed to address pressing societal challenges. Data integration is key to a reintegrated biology able to address global issues such as climate change, biodiversity loss, and sustainable ecosystem management. We identify major challenges to data integration and present a vision for a "Data as a Service"-oriented architecture to promote reuse of data for discovery. The proposed architecture includes standards development, new tools and services, and strategies for career-development and sustainability.
几十年来，生物学中的还原论方法取得了惊人的进展，但由于各子学科的发展，以及每个子学科在数据方面都有其独特的技术和社会实践，这阻碍了多学科和跨学科方法的发展，而这些方法现在是解决紧迫的社会挑战所必需的。数据集成是使生物学重新整合，从而能够应对气候变化、生物多样性丧失和可持续生态系统管理等全球性问题的关键。我们确定了数据集成的主要挑战，并提出了一种面向“数据即服务”的架构愿景，以促进数据的再利用以实现发现。所提出的架构包括标准制定、新的工具和服务，以及职业发展和可持续性战略。
