- Organize your data into the fewest logical units. Many tables of the same structure and content should be compiled into a single table. Spatial data files (e.g. shape files) of a common theme or scope should be zipped up in their respective folders.
- Run quality control checks on your data to ensure they are ready for publication. Keep track of these steps so others know what has been done to these data.
- Tell us about our data.
- If EDI will be creating EML with you, then fill out the EDI metadata template and send it to us. You will also need to send us your data. Detailed instructions are here.
- If you will be creating EML on your own then send this file once completed. We have created the EMLassemblyline R code package to help you with this process.
- Send us your data and metadata. It will be placed in a queue for processing**.
- If EDI is creating EML with you, then send Kristin and Colin your data and the completed metadata template (email@example.com, firstname.lastname@example.org).
- I you are creating EML, send Kristin and Colin your data and EML once completed.
- EDI will then process your dataset and work with you to resolve any issues that may arise. Once your dataset passes validation it will be uploaded to a staging environment for your viewing. Once you’ve approved the dataset we will move it to publication and provide you with the dataset DOI and a recommended citation. Once published you should update your ORCID and CV with this new scientific product. Data publications are valuable!
*If you’re an information manager we may be able to set you up with a PASTA user account. This enables you to validate and upload data packages on your own.
**There are 2 queues. One for datasets we are creating EML for, and a second for datasets in which you have created EML. The processing rate of the first queue is slower than the second, because creating EML from scratch takes longer than simply validating an already constructed EML file.