Launched in 2020, MTNA's Rich Data Services (RDS) (https://www.richdataservices.com) offers a comprehensive solution for the concurrent publication of data and metadata as a service through a modern REST API. The platform comes equipped with three web applications to enable the ability to manage content, interactively access record level data, and rapidly create aggregated tables.

The RDS API provides the foundation needed to build rich web or desktop based data applications, access data directly from analytical and development environments like R, Python, SAS, Stata, C++, or Java, or for machine learning purposes. Open source libraries and multiple forms of documentation are available to developers and data scientists to rapidly leverage the API.

The RDS Open Data Packaging service further caters to the needs of users who prefer to work with the (meta)data offline. This provides the option to download the data in various text formats, alongside with scripts/syntax files, PDF documentation, or DDI metadata, enabling immediate reuse and minimizing wrangling.

From its inception, RDS leveraged DDI for loading metadata and as an export option. The latest version adds DDI-C and schema.org endpoints on each data product, providing easy access to metadata in standard formats. These latest features further facilitate alignment on GOFAIR recommendations, linked data integration, metadata harvesting, or discovery through Google Data Search.

Finally, RDS is being increasingly recognized as a potential alternative to Nesstar Server. Popular amongst the DDI community, Nesstar has for over two decades been instrumental in the establishment of the standard, but unfortunately is no longer being actively maintained. Migration from Nesstar to RDS can mostly be automated and is a smooth and natural transition.

This short presentation will provide a refresher on what RDS can do for you, highlight the platform DDI aspects, and briefly demo the latest features and capabilities.