The collection and classification of data into meaningful categories is a key step in the process of knowledge making. In the life sciences, the design of data discovery and integration tools has relied on the premise that a formal classificatory system for expressing a body of data should be grounded in consensus definitions for classifications. On this approach, exemplified by the realist program of the Open Biomedical Ontologies Foundry, progress is maximized by grounding the representation and aggregation of data on settled knowledge. We argue that historical practices in systematic biology provide an important and overlooked alternative approach to classifying and disseminating data, based on a principle of coordinative rather than definitional consensus. Systematists have developed a robust system for referring to taxonomic entities that can deliver high quality data discovery and integration without invoking consensus about reality or “settled” science.

中文翻译：

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协调异议作为共识分类的替代方法：来自生物本体论系统学的见解。

将数据收集和分类为有意义的类别是知识创造过程中的关键步骤。在生命科学中，数据发现和集成工具的设计依赖于这样一个前提，即用于表达数据主体的正式分类系统应以分类的共识定义为基础。在这种方法上，以开放式生物医学本体铸造基金会的现实主义程序为例，通过将数据的表示形式和聚集基础放在已确定的知识上，可以最大程度地提高进步。我们认为，系统生物学的历史实践基于协调而不是定义共识的原则，为分类和传播数据提供了一种重要且被忽视的替代方法。