Division of Biology and Biological Engineering 156-29, California Institute of Technology, Pasadena, CA 91125, USA.
Informatics and Bio-computing Platform, Ontario Institute for Cancer Research, Toronto, ON M5G0A3, Canada.
Database (Oxford). 2018 Jan 1;2018. doi: 10.1093/database/bay013.
Large volumes of data generated by research laboratories coupled with the required effort and cost of curation present a significant barrier to inclusion of these data in authoritative community databases. Further, many publicly funded experimental observations remain invisible to curation simply because they are never published: results often do not fit within the scope of a standard publication; trainee-generated data are forgotten when the experimenter (e.g. student, post-doc) leaves the lab; results are omitted from science narratives due to publication bias where certain results are considered irrelevant for the publication. While authors are in the best position to curate their own data, they face a steep learning curve to ensure that appropriate referential tags, metadata, and ontologies are applied correctly to their observations, a task sometimes considered beyond the scope of their research and other numerous responsibilities. Getting researchers to adopt a new system of data reporting and curation requires a fundamental change in behavior among all members of the research community. To solve these challenges, we have created a novel scholarly communication platform that captures data from researchers and directly delivers them to information resources via Micropublication. This platform incentivizes authors to publish their unpublished observations along with associated metadata by providing a deliberately fast and lightweight but still peer-reviewed process that results in a citable publication. Our long-term goal is to develop a data ecosystem that improves reproducibility and accountability of publicly funded research and in turn accelerates both basic and translational discovery.
研究实验室产生的大量数据，加上编目所需的努力和成本，成为将这些数据纳入权威社区数据库的一个重大障碍。此外，许多公共资助的实验观测结果由于编目而无法被发现，仅仅是因为它们从未被发表过：研究结果通常不符合标准出版物的范围；当实验者（例如学生、博士后）离开实验室时，由学员生成的数据被遗忘；由于出版偏见，结果从科学叙述中被省略，某些结果被认为与出版无关。虽然作者最有能力编目自己的数据，但他们面临着陡峭的学习曲线，以确保适当的参考标签、元数据和本体论正确地应用于他们的观察结果，这项任务有时被认为超出了他们研究和其他许多职责的范围。要让研究人员采用新的数据报告和编目系统，需要研究界所有成员在行为上发生根本性的变化。为了解决这些挑战，我们创建了一个新颖的学术交流平台，通过微出版从研究人员那里捕获数据，并直接将其交付给信息资源。该平台通过提供一个刻意快速、轻量级但仍经过同行评审的过程，激励作者发表他们未发表的观察结果以及相关的元数据，从而产生可引用的出版物。我们的长期目标是开发一个数据生态系统，提高公共资助研究的可重复性和问责制，并反过来加速基础研究和转化发现。
数据库 URL：www.micropublication.org。
