Merge pull request #47 from microbiomedata/46-update-fair-documentati…

…on-for-renewal

Update FAIR documentation for renewal

content/home/src/explanation/fair_data.md

@@ -4,7 +4,7 @@
 
 The NMDC is committed to adhering to [FAIR Guiding Principles](https://www.nature.com/articles/sdata201618) with regard to data management best practices. As part of this commitment, the NMDC has established the [FAIR Microbiome Implementation Network](https://www.go-fair.org/implementation-networks/overview/fair-microbiome/) (IN), a consortium interested in microbiome research that has agreed upon a set of objectives and common vision for implementing FAIR principles in the context of microbiome data science.
 
-The FAIR Microbiome IN seeks to align and synergize the efforts of the NMDC with that of the [GO FAIR]( community, leveraging the [GO FAIR](https://www.go-fair.org/) open and inclusive [ecosystem of Implementation Networks](https://www.go-fair.org/implementation-networks/overview/) for the microbiome research community (e.g., [Chemistry IN](https://www.go-fair.org/implementation-networks/overview/chemistryin/), [Metabolomics IN](https://www.go-fair.org/implementation-networks/overview/metabolomics/), Biodiversites INs). The purpose of the FAIR Microbiome IN is to work with microbiome research communities to:
+The FAIR Microbiome IN seeks to align and synergize the efforts of the NMDC with that of the [GO FAIR](https://www.go-fair.org/) community, leveraging the [GO FAIR](https://www.go-fair.org/) open and inclusive [ecosystem of Implementation Networks](https://www.go-fair.org/implementation-networks/overview/) for the microbiome research community (e.g., [Chemistry IN](https://www.go-fair.org/implementation-networks/overview/chemistryin/), [Metabolomics IN](https://www.go-fair.org/implementation-networks/overview/metabolomics/), Biodiversites INs). The purpose of the FAIR Microbiome IN is to work with microbiome research communities to:
 
 * Formalize core and domain-specific microbiome ontologies that promote discovery and reuse, and
 * Establish training on the NMDC data models that allow for broader dissemination of knowledge and compliance for both humans and machines.