Is the Cloud Right for My Research?

When set up, used, and managed to complement your research goals, cloud services can often improve efficiency and facilitate reproducible science.

Using cloud resources can be useful for:

  • Establishing a research program/project
  • Receiving award funding
  • Creating a funding opportunity announcement
  • Creating a request for proposals
  • Using on-premise resources for computation, analysis, and storage currently

Program management staff, awardees, and academic administrators receiving funding should carefully consider whether Cloud services would benefit their program/project needs. Determining if cloud is right for your research typically requires involvement from multiple people within your organization, including but not limited to your project management staff, research collaborators, and your institutional leaders.

If you manage a research program, consider these key questions to inform your decision-making process:

  • Is the cloud a part of your long-term data management strategy?
  • How is your data managed and structured?
  • Is the data generated by your program/project FAIR?
  • Which data domains do you want to move to the cloud?
  • Are there any other data domains you need access to?
  • Are they available in the cloud?
  • What collaboration goals do you have for your program/project?
  • Does the data need to be shared broadly?
  • Do you have geographically dispersed teams that require access to your data?
  • What analytical tools does your research program/project use currently or are there other tools needed?
  • If your research is in progress, are the tools your program/project rely on today “cloud-ready” (i.e., configured or configurable) to work effectively in the cloud?
  • Are additional virtual tools and services, such as artificial intelligence and machine learning, needed to support your program/project research in an on-demand format?
  • Do you anticipate variability (i.e., spikes and valleys) in terms of computational and storage needs over the course of your program/project?
  • Do you have a budget for transitioning to and accessing the cloud, and for using cloud services and tools?
  • Is there someone on your team who can support the administration, provisioning, and management of data in the cloud, along with serving as the accountable party to monitor usage and ensure proper information security controls are in place?
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    If you are an awardee of NIH funding, consider these key questions to inform your decision-making process:

    • How is your award structured?
    • Do your funding stipulations allow for cloud services?
    • How is your data managed and structured?
    • Is your data FAIR?
    • What are your research requirements related to processing, sharing, analyzing, and storing data?
    • What are your collaboration goals?
    • Does your data need to be shared broadly?
    • Do you have geographically dispersed collaborators that require access to your data?
    • Is there a lack of applicable and available on-premise infrastructure that meets the needs of your program/project?
    • Would your research benefit from access to other datasets that may be located on the cloud?
    • Are there any other data domains you need access to?
    • Are they available in the cloud?
    • If your research is in progress, are the tools you rely on today “cloud-ready” (i.e., configured or configurable) to work effectively in the cloud?
    • Are additional virtual tools and services, such as artificial intelligence and machine learning, needed to support your research in an on-demand format?
    • Do you anticipate variability (i.e., spikes and valleys) in terms of computational and storage needs over the course of your program/project?
    • Is cloud a part of your longer-term data management strategy?
    • Do you have a budget for transitioning to and accessing the cloud, and for using cloud services and tools?
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      There are some additional items about cloud resources to keep in mind as you evaluate the cloud for your research, including:

      • Resources (data, tools, etc.) in the cloud are not guaranteed to be available indefinitely and require continued funding and support. Therefore, the cloud should not be seen as a replacement for contributing data to a proper data repository or archive.
      • Data download costs (“egress fees”) from the cloud can become very expensive for large data volumes and should be considered if you want to allow unrestricted access to the data. When choosing a commercial provider, be sure to compare providers’ egress fees in the event that you want to move data out of the cloud.
      • Cost and capacity of commercial provider services and tools are very different from local, on-premise services and tools. Cloud services scale with your needs and you pay for what you use; this can be more costly than local resources, depending on your usage and associated cost models. For example, local resources often have a larger upfront cost than cloud but lower marginal cost; and have a maximum capacity, whereas cloud resources can scale based on demand.
      • Data uploaded into the cloud are not automatically FAIR. Effort is required to make them FAIR prior to upload, and doing so will allow other researchers to more easily use the data.
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