AD Workbench

Powering breakthroughs in Alzheimer’s and related dementias research

AD Workbench – a secure, cloud-based data sharing and analytics environment – is the interoperability layer of the AD Data Initiative technical suite and its flagship product offering. Easy to use and available at no cost, AD Workbench empowers researchers around the world to share, access and analyze data across platforms.


We can accelerate progress towards new and better treatments and diagnostic tools for Alzheimer’s and related dementias by connecting researchers with the data they need. To get there, a global coalition of partners collaborated to build the AD Workbench. Download a detailed look at our flagship product offering.

The AD Workbench data sharing and analytics environment allows researchers to:

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Data Sharing Principles

The AD Workbench (ADWB) is guided by three main principles: increasing data sharing, easing data access, and developing new tools and analytics for researchers to use and share.

  • By increasing the interoperability of participating data platforms;
  • By adding new data platforms and datasets as quickly as possible;
  • By offering incentives to academic and industry researchers who choose to share resources and data.
  • To search available data;
  • To manage the datasets they find;
  • To navigate data use agreements (DUAs);
  • To request access to new datasets;
  • To work from a library of existing analytics tools and scripts;
  • To see the usage and quality of available datasets on a clear, transparently presented dashboard.
  • By providing a place for researchers to use and share their own code and save their work;
  • By allowing users to allocate workloads to virtual machines, providing them with elasticity in computing power;
  • By sponsoring hackathons and other organized challenges that expand the community of users.
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Different types of researchers and members of the AD and science communities will interact with the ADWB in different ways, which include users

A user with a specific question can utilize a set of common analytical tools that are available for quick data exploration. ADWB workspaces also include a suite of R shiny apps to assist users with further data analysis.

A user who plans to analyze existing datasets using their own code can also utilize the available analytical tools for quick data exploration. The R code used to load the data and generate plots is available for export and further analysis, and users can upload their own code or develop their own mini-apps that can be shared more broadly with others in the community. Jupyter notebooks will soon be embedded in the workspaces. For more computing power or specific software, users can configure available virtual machines.

A user who plans to bring new data to do multimodal or pooled analysis can directly upload datasets and CSV files for analysis utilizing the tools and mini-apps available in the workspaces.