NSF Workshop: Towards an Open Source Model for Data and Metadata Standards

Award ID: 2334483

Recent progress in machine learning and artificial intelligence promises to advance research and understanding across a wide range of fields and activities. In tandem, an increased awareness of the importance of open data for reproducibility and scientific transparency is making inroads in fields that have not traditionally produced large publicly available datasets. Data sharing requirements from publishers and funders, as well as from other stakeholders, have also created pressure to make datasets with research and/or public interest value available through digital repositories. However, to make the best use of existing data, and facilitate the creation of useful future datasets, robust, interoperable and usable standards need to evolve and adapt over time. The open-source development model offers significant potential benefits to the process of standard creation and adaptation. In particular, development and adaptation of standards can take advantage of long-standing socio-technical processes that have been key to managing the development of open-source software, and allow incorporating broad community input into the formulation of these standards. This workshop aims to create interdisciplinary connections across a wide range of research fields, thereby providing fertile ground for exchange of knowledge and the creation of new and broadly useful knowledge about the application of the open-source model to data and metadata standards. Furthermore, the synthesis that will be generated will be useful for policy makers and funders in determining worthwhile avenues for policy and funding investment to best make use of the open-source production and governance principles in support of broad societal goals. By adhering to open-source standards for formal descriptions (e.g., by implementing schemata for standard specification, and/or by implementing automated standard validation), processes such as automated testing and continuous integration, which have been important in the development of open-source software, can be adopted in defining data and metadata standards as well. Similarly, open-source governance provides a range of stakeholders a voice in the development of standards, potentially enabling use-cases and concerns that would not be taken into account in a top-down model of standards development. On the other hand, open-source models also carry unique risks that need to be taken into account. The goal of this workshop is to discuss examples where an open-source model for standards development has had significant impact on the practice within a field. Importantly, the workshop will also discuss cases where this model has not worked in the past, and cases where this model is not a good fit. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Peter Atherton