Overview
The Lucy Family Institute (Lucy) adventurously collaborates on advancing data-driven convergence research, translational solutions, and education to ethically address society’s wicked problems. Within Lucy, the Applied Analytics for Emerging Technologies Lab (AETL) collaborates with iNDustry Labs to help accelerate economic and innovation impact in the South-Bend Elkhart region. As an applied research lab, AETL also aims to accelerate use-inspired research that leads to the application of analytics and drives the advancement of co-developed, innovative foundational research.
In response to discussions with internal and external partners, AETL is launching a Data Platform in Spring 2024 to reduce the barriers to access data and leverage advanced machine learning resources. Aimed at both research and industry data, the platform will streamline the data collection and analysis while providing secure hosting according to sensitive data standards and regulations.
Do you need a home for restricted or sensitive data for your research? Would you like to partner early with AETL to accelerate the impact of your data? If so, please respond to this Request for Information (RFI) to share your use cases as well as the current challenges and barriers you face in acquiring, hosting, storing, accessing, analyzing, and storytelling with data. A subset of RFI responders will be contacted to partner with AETL to develop and test the Data Platform with anticipated industry and research use cases benefiting the regional and wider community.
Eligibility
Primary submitters must be ND faculty or staff.
Key Dates
RFI responses are due on March 27, 2024 at 5:00 PM. Teams that propose specific use cases will be contacted for additional information following submission.
RFI Components
- Team: Primary information about the submitting author(s), including name(s), and department or affiliation, and contact information.
- Use Cases: What activities are you pursuing that could potentially be a candidate for the Data Platform? Please provide a one paragraph summary of your objectives and goals.
- Impact Statement: Who are the intended users? Who will your project impact?
- Access: Do you already have access to the dataset(s) that you would like to host? For example, has a Data Use Agreement already been signed by the University? Have you purchased access to the data? Are there any ongoing subscription costs or data access restrictions?
- Storage: How large are the dataset(s)? What level of security is needed? Are they publicly accessible? Do they contain any identifiable information? How long would you require active maintenance on data storage and access?
- IRB approval: If applicable, have you received IRB approval for your research study design? Is there anything that has prevented you from being able to do so?
- Data Curation: Would your use case benefit from having an AETL data administrator provide data curation services such as deidentification, data visualization, or building out a custom user interface?
- Computing: What types of computing resources do you need to accomplish your proposed research goals? How often do you expect to iterate on data or submit new data?
- Unstructured or Structured Data: Especially for machine learning use cases, is the applicable data unstructured, structured, or both?
- Cost sharing: Are there any cost-sharing or existing resources that you have access to for data acquisition, hosting, storage or curation?
- Other Barriers and Challenges: Are there any additional barriers and/or challenges that you have encountered that are not already addressed above?
Questions?
Please direct any questions to the AETL Managing Director, Rick Johnson (rick.johnson@nd.edu)
