Freshwater practitioners rely on biological monitoring to assess stream condition, yet the broader adoption of diatom-based assessment remains limited by challenges of accessibility, standardization, and scalability. Diatoms are used as bioindicators because they integrate cumulative ecosystem responses to environmental change over time. However, applying diatom-based indices at broad spatial scales often requires specialized taxonomic expertise, substantial analytical capacity, and access to compatible data infrastructures, constraining their implementation beyond research contexts. Recent syntheses of biomonitoring practice highlight the need for open, interoperable data and transferable assessment frameworks that translate biological information into decision-relevant metrics (Yates et al., 2025). The National Ecological Observatory Network (NEON) provides long-term, open-access, taxonomically standardized diatom data that directly respond to these challenges. The National Diatom Multi-Metric Index (MMI) developed by Carlisle et al. (2022) offers a standardized framework for converting diatom community data into ecologically interpretable measures of stream condition that also respond to these challenges to support practitioners. In this pilot study, we evaluate whether NEON diatom data can be operationalized within the Carlisle et al. national MMI framework to assess stream condition across the conterminous United States. Using this approach, we generate a national map of diatom-based stream condition across NEON aquatic sites. This work assesses whether integrating an existing national diatom MMI with an open-access ecological data infrastructure can reduce barriers to implementation and support more scalable applications of diatom-based biomonitoring. This pilot study represents the first stage of a longer-term effort toward refining diatom-based MMIs at smaller regional scales using NEON data to increase MMI performance and, in future phases, integrating social data alongside biological assessments. Incorporating the social context has the potential to enhance interpretability and relevance for identifying disparities in monitoring coverage and restoration prioritization. Ultimately, this work contributes to ongoing efforts to develop accessible biomonitoring tools that support ecologically and equitably informed freshwater decision-making.