An Assemblage of Open Source Software for Sharing Large Spatiotemporal Data and Promoting Open Science with BEHR

Sharing research data to support publication and promote reuse is challenging, especially large spatiotemporal data sets. These data are difficult to visualize and manipulate online, and thus have a high barrier to entry. Often data are packaged and loaded to a online repository offering little guidance on what the data contains or how it can be visualized. Here we describe application of open source web technologies to sharing the Berkeley High Resolution (BEHR) Tropospheric NO2 product, which is a retrieval of UV/Visible satellite observations over North America. We transformed the source Hierarchical Data Format (HDF) files, into an interactive web-based map. This new online system allows visitors to familiarize themselves with the data first prior to downloading it. In addition, we describe how these data can be seamlessly included within cloud based systems like Jupyter Notebook, affording researchers more advanced analysis capabilities in and out-side of the classroom.