The reuse of research software is central to research efficiency and academic exchange. The application of software enables researchers with varied backgrounds to reproduce, validate, and expand upon study findings. Furthermore, the analysis of open source code aids in the comprehension, comparison, and integration of approaches. Often, however, no further use occurs because relevant software cannot be found or is incompatible with existing research processes. This results in repetitive software development, which impedes the advancement of individual researchers and entire research communities. In this article, the DataDesc ecosystem is presented, an approach to describing data models of software interfaces with detailed and machine-actionable metadata. In addition to a specialized metadata schema, an exchange format and support tools for easy collection and the automated publishing of software documentation are introduced. This approach practically increases the FAIRness, i.e., findability, accessibility, interoperability, and so the reusability of research software, as well as effectively promotes its impact on research.

翻译：研究软件的重用对于科研效率和学术交流至关重要。软件的应用使不同背景的研究人员能够再现、验证并拓展研究结果。此外，对开源代码的分析有助于理解、比较和整合研究方法。然而，由于相关软件难以被发现或与现有研究流程不兼容，往往无法实现进一步使用。这导致重复性软件开发，阻碍了单个研究人员乃至整个研究团体的进步。本文提出了DataDesc生态系统，这是一种通过详细且机器可操作的元数据来描述软件接口数据模型的方法。除专门的元数据模式外，还引入了便于软件文档收集和自动发布的交换格式与支持工具。该方法实际提升了研究软件的FAIR性（即可发现性、可访问性、互操作性及可重用性），并有效促进了其对科研的影响力。