Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Are they associated in some other way? Such relationships between the mapped terms are often not documented, leading to incorrect assumptions and making them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Also, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. The Simple Standard for Sharing Ontological Mappings (SSSOM) addresses these problems by: 1. Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. 2. Defining an easy to use table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data standards. 3. Implementing open and community-driven collaborative workflows designed to evolve the standard continuously to address changing requirements and mapping practices. 4. Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases, and survey some existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable, and Reusable (FAIR). The SSSOM specification is at http://w3id.org/sssom/spec.
翻译:尽管在制订科学信息描述和交换标准方面取得了进展,但在不同数据库中同一或类似物体的不同表达形式之间缺乏便于使用的绘图标准,这对数据整合和互操作性构成重大障碍。绘图往往缺乏正确的解释和应用元数据;例如,两个条件等同或仅相关?它们是否相近?它们是否以某种其他方式联系?所绘制的术语之间的关系往往没有记录,导致错误的假设,使其难以用于需要高度精确度的情景(例如诊断或风险预测)。此外,缺乏关于如何进行制图的描述,使得难以将制图,特别是经调整和自动化的地图结合起来和加以协调。《分享在线绘图简单标准标准》(SS)解决这些问题的方式有:1. 采用一个机器可读和可扩展的词汇来描述造成不准确、不准确和不完善的元数据的元数据;2. 界定一种容易使用基于表格的格式,这种格式可以纳入现有的数据管道,而不需要进行内部分析或相互核对的地图;3. 将OLO/Reserverial3 用于不断更新的SLA标准/SLLA 和SLLD 与不断更新的系统定义。