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Welcome to the NOAA Omics Data Management Guide!
Management of data generated in research is critical to ensure fidelity of the scientific enterprise and maximum utility of research funding. Management of omics data presents additional challenges because of its large datasets, new and diverse technologies generating those datasets, and the many types of data and environmental data involved.
The motivation of this guide is to facilitate finding the data produced by every omics project and ensuring that it is usable by future researchers.
The focus of this guide is to help omics users decide which data goes to which repositories (NCEI, NCBI, etc.), and how to deposit their data so that it will be FAIR (findable, accessible, interoperable, and reusable), including following community standards for raw data, processed data, and contextual metadata and environmental data.
The wiki is organized into the following pages:
| Topic | Description |
|---|---|
| Motivation | The advantages of good data management for NOAA's mission, including machine readability and compliance with US Government mandates |
| Data Types | Where to submit and how to format different types of omics data (decision trees) |
| Metadata | Standards, formatting and refining, templates, etc. |
| Quality Control | How to ensure and document data quality |
| Storage & Sharing | Where and how to store, share, and transfer datasets, including IT requirements |
| Finding | How to find NOAA and other data, and how to make your data findable (keywords, persistent identifiers, cross-listing) |
| Publishing | Standard language for publications, timing of publishing |
| Additional Topics | Protocol sharing, ... |
| Additional Resources | External guides on how to format metadata, submit raw data to repositories, and submit sequence-based data to OBIS |
The advantages of good data management for NOAA's mission, including machine readability and compliance with US Government mandates.
- FAIR data principles