To be sustainable and useful, scientific data should be FAIR. These goals can only be achieved by definition and adoption of metadata standards and implementation of tools and services that support these standards. Unfortunately, the diversity of scientific (meta)data leads to a large gap between the scope and pace of large-scale standardization efforts and the day-to-day work of domain researchers. This poster gives an overview of Metador - a metadata-centered framework emphasizing the I and R in FAIR trying to address these issues using an incremental, bottom-up approach. It is based on a lightweight technical meta-standard for packaging JSON-serialized metadata objects alongside the research data in archives, a simple API implementing this standard, and a plugin-based metadata schema system. On top of this, it provides automatic generation of dashboards for compatible data archives that can be embedded in different settings. In future work, we plan to develop Metador into an open ecosystem of reusable plugins and integrating it with existing popular tools and services.