> For the complete documentation index, see [llms.txt](https://c-comp.gitbook.io/data-management-handbook/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://c-comp.gitbook.io/data-management-handbook/overview.md).

# Overview

The [Center for Chemical Currencies of a Microbial Planet](https://ccomp-stc.org/) (C-CoMP) shares data, metadata, data products, protocols, code, and software according to FAIR Data Principles (Wilkinson et al. 2016) to implement our open science objectives.

Data diversity is one of the strengths and challenges of C-CoMP’s open science approach. C-CoMP generates observational, experimental, simulated, and derived data in both standard and non-standard formats using a variety of different methodologies and sample sources. 

For example, all of the following are included within the C-CoMP data landscape: 

* oceanographic field data (e.g. salinity, depth)
* microbial abundances
* bulk chemical measurements (e.g. phosphate concentrations, DOC concentrations)
* genomic sequences (e.g. amplicon-based sequencing, metagenomics, metatranscriptomics)
* Numerical modeling outputs
* Metabolite concentrations (LC-MS and NMR)
* Protein abundances (LC-MS)

For data to be findable, accessible, interoperable, and reusable (FAIR), data must be well-described using standardized parameters, organized, stored on publicly accessible repositories, and structured in human and machine-readable open formats to facilitate data integration efforts. 

To address this challenge, C-CoMP has created this data management handbook, using input from the C-CoMP community and the Biological and Chemical Oceanography Data Management Office (BCO-DMO) and guidance from FAIR Data Principles and the [Research Data Management Service Group at Cornell University](https://data.research.cornell.edu/), to support C-CoMP’s open science policy and provide efficient, data stream dependent instructions for storing, organizing, naming, and submitting data to publicly accessible repositories.


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