A semantic layer promises to ensure consistency across data sources and tools by facilitating the creation of data models that define dimensions, measures, and metrics, providing secure and fast data experiences. To fully deliver on this promise, a semantic layer must support a broad range of data sources and applications, integrating seamlessly within an ever-evolving technological landscape. The development of an open standard for semantic layers could enhance consistency and interoperability among business intelligence tools, data science platforms, and analytics systems, reducing vendor lock-in and switching costs. This standard should cover the specification of objects, querying protocols, and metadata exchange protocols, with current approaches focusing on metrics-centric and dataset-centric models. The latter allows broader compatibility with existing tools by treating tables as first-class objects. Additionally, a semantic layer should support both SQL and GraphQL querying protocols to accommodate a wide array of data tools, although challenges remain in integrating semantic layers with front-end user interfaces of BI tools. Cube advocates for an open standard to foster collaboration and interoperability in the data community, aiming to support a diverse ecosystem of data sources and consumers.