Genomics data is accumulating in public repositories at an ever-increasing rate. Large consortia and individual labs alike continue to probe animal and plant tissue and cell cultures, generating vast amounts of data using established and novel technologies.
In this collection, we will elicit opinions and perspectives from researchers in the field on the opportunities and challenges of reusing public genomics data. Our contributors will be uniquely positioned to comment on successfully integrating the public data into research programs and highlight the areas of active research that make this kind of work possible.
Limitless opportunities exist for use and reuse of genomics data. Researchers worldwide are sifting through large datasets and published studies to test novel hypotheses and reanalyze the data using innovative methodologies. Some focus on curating small but similar datasets to increase the power of their analysis. Some combine data types of the same model to study the different aspects of their biology simultaneously. Others work on making the vast amounts of data usable and accessible. This is not to say there are no challenges associated with these efforts. The need for curation, processing, and accessibility are just a few examples of the many challenges ahead.
This topic strongly welcomes, but is not limited to, submissions in the form of Opinion and Perspective articles. We welcome articles that focus on, but are not limited to, the following themes:
• Which data do we have in mind?
For example: Large scale consortia datasets, curated data from published studies, datasets optimized and shared for reuse
• How are public datasets put to use?
For example: To test novel ideas, to apply different methodologies, to curate data to increase analysis power, to combine more than one type of data, to make data accessible and available in different formats
• Who contributes to the efforts of reusing public datasets?
For example: people who curate datasets from data repositories to build models and make them available in databases and applications; people who process large datasets and make the output available for easy access by others; people who manage data and annotation hubs complementing data repositories; where data are presented in accessible ready-to-use formats; people who write software that connect to data repositories to improve access through tools like ‘R’; people who advocate and encourage research using public data and work to highlight successful applications
Genomics data is accumulating in public repositories at an ever-increasing rate. Large consortia and individual labs alike continue to probe animal and plant tissue and cell cultures, generating vast amounts of data using established and novel technologies.
In this collection, we will elicit opinions and perspectives from researchers in the field on the opportunities and challenges of reusing public genomics data. Our contributors will be uniquely positioned to comment on successfully integrating the public data into research programs and highlight the areas of active research that make this kind of work possible.
Limitless opportunities exist for use and reuse of genomics data. Researchers worldwide are sifting through large datasets and published studies to test novel hypotheses and reanalyze the data using innovative methodologies. Some focus on curating small but similar datasets to increase the power of their analysis. Some combine data types of the same model to study the different aspects of their biology simultaneously. Others work on making the vast amounts of data usable and accessible. This is not to say there are no challenges associated with these efforts. The need for curation, processing, and accessibility are just a few examples of the many challenges ahead.
This topic strongly welcomes, but is not limited to, submissions in the form of Opinion and Perspective articles. We welcome articles that focus on, but are not limited to, the following themes:
• Which data do we have in mind?
For example: Large scale consortia datasets, curated data from published studies, datasets optimized and shared for reuse
• How are public datasets put to use?
For example: To test novel ideas, to apply different methodologies, to curate data to increase analysis power, to combine more than one type of data, to make data accessible and available in different formats
• Who contributes to the efforts of reusing public datasets?
For example: people who curate datasets from data repositories to build models and make them available in databases and applications; people who process large datasets and make the output available for easy access by others; people who manage data and annotation hubs complementing data repositories; where data are presented in accessible ready-to-use formats; people who write software that connect to data repositories to improve access through tools like ‘R’; people who advocate and encourage research using public data and work to highlight successful applications
