ABI Innovation: Authors in the driver's seat: fast, consistent, computable phenotype data and ontology production

现代进化论研究需要来自生命树多个分支的生物体特征数据，但这些数据大多是计算机无法使用的“遗留”格式。训练有素的博士后科学家被雇佣来手动转换他们。据估计，仅一年的英文生物医学期刊出版物就需要30多年的全日制博士后才能转换。这一手动过程从根本上来说是有问题的，原因有三：第一，它不会阻止以传统格式继续出版角色描述。其次，它占用了训练有素的科学家的时间，阻止他们做出新的、更重要的发现。第三，它没有解决不同科学家转换的数据存在巨大差异(约40%)的根本原因，导致数据用处较少。该项目将研究一种从根本上解决问题的变革性方法，使生物多样性作品的作者能够在发表时直接产生可计算的数据，而不需要随后的出版后数据转换。科学家将能够以新的格式直接使用公布的数据，以解决当今人类面临的重大保护、环境或医学挑战。本研究具有从根本上解决表型数据生产问题的巨大潜力。它承认作者在写描述性作品时做出(隐含的)本体论承诺，他们最有资格解释作品。将为作者提供一个低障碍、高效、开放的协作平台，以使用与从事类似分类群工作的其他作者共同建立的本体，以他们所希望的方式准确地描述字符，而不是将作者限制在任何“标准化”术语上。这一过程使作者更了解社区中的术语用法，并帮助社区(包括年轻一代的科学家)在最佳实践上趋同。其结果将是，包括在描述性工作中的所有字符术语都被记录/定义在特定于分类单元的本体中，从而使描述在语义上清晰，并为软件获取可计算的字符数据做好准备。该项目将要开发的软件平台将在本体中暴露作者之间的分歧和基于使用的术语状态，并通过移动友好的应用程序通知作者更新和冲突。考虑到用户的动机和归因因素，该项目将从人类社会行为和软件可用性的角度来设计、实施和评估该方法，使用开放在线协作研究和尖端可用性测试技术的最新结果(例如，通过眼球跟踪和瞳孔放大来测量用户的压力水平)。该项目的成功可推广到其他领域，并将从根本上改变表型特征被记录和用于生物学研究的方式。该项目的结果将在http://github.com/orgs/biosemantics/projects.上找到。

Modern evolutionary research requires organism character data from multiple branches of the Tree of Life, but the majority of such data are in a "legacy" format that computers can not use. Highly trained postdoc scientists are employed to manually convert them. By one estimate, one year's worth of English biomedical journal publications alone would take a full-time postdoc over 30 years to convert. This manual process is fundamentally problematics for three reasons: First, it does not stop the continued publication of character descriptions in the legacy format. Second, it takes time away from highly trained scientists and preventing them from making new and more important discoveries. Third, it does not address the fundamental causes of large differences (~ 40%) in the data converted by different scientists, resulting in less useful data. This project will investigate a transformative approach that solves the problem at its root, by enabling authors of biodiversity works to directly produce computable data at the time of publication, eliminating the need for subsequent post-publication data conversion. Scientists will be able to direct use the published data in the new format to address grand conservation, environmental, or medical challenges facing humankind today. This research has great potential to solve the phenotype data production problem at its root. It recognizes that authors make (implicit) ontological commitments when writing a descriptive work and that they are best qualified to interpret the work. Instead of limiting authors to any "standardized" terminology, authors will be provided with a low-barrier, efficient, open-collaboration platform to describe characters as accurately as they wish using an ontology built collectively with other authors working on similar taxa. This process makes authors more aware of term usage in the community and helps the community (including younger generation of scientists) converge on best practices. The result will be that all character terms included in the descriptive work are documented/defined in the taxon-specific ontology and the descriptions are consequently made semantically clear, and ready for software to harvest computable character data. The software platform to be developed by this project exposes disagreements among authors and usage-based term status in the ontology, and notifies authors of updates and conflicts via a mobile-friendly app. Taking into account user motivation and attribution factors, the project will design, implement, and evaluate the approach from both human social behavior and software usability perspectives, employing recent results from open online collaboration research and cutting-edge usability test techniques (e.g., measuring user stress levels via eye-tracking and pupil dilation). The success of the project is generalizable to other domains and will fundamentally change the way phenotypic characters are documented and used in biological research. The results of the project will be found at http://github.com/orgs/biosemantics/projects.