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Area of Science:

Microbial ecology and bioinformatics.
Environmental science and biodiversity research.

Background:

The 'omics revolution provides unprecedented data on microbial biomass and biodiversity.
Current research generates vast amounts of sequence, protein, and metabolite data.

Purpose of the Study:

To address the need for a collaborative framework for developing and exchanging predictive ecosystem models in microbial ecology.
To outline a strategic plan for a Genomic Software Institute (GSI) to facilitate this framework.

Main Methods:

Discussing the requirements for a data and metadata framework, including transparency, interoperability, validation, curation, and search capabilities.
Highlighting the need for APIs for modeling and analysis tools.
Emphasizing community interaction and leveraging existing efforts like the Genomic Standards Consortium (GSC).

Main Results:

Identifying the lack of a standardized framework as a key impediment to macro-scale microbial ecology research.
Proposing the establishment of a Genomic Software Institute (GSI) to foster a collaborative environment.
Outlining essential components for a successful framework, including data standards and accessible tools.

Conclusions:

A community-driven framework is crucial for advancing microbial ecology by enabling the development and sharing of predictive ecosystem models.
The proposed Genomic Software Institute (GSI) aims to consolidate efforts and provide necessary infrastructure for data analysis and modeling.
Enhanced collaboration and standardized practices are essential to fully leverage 'omics data for understanding global microbial biodiversity and function.