Research Software Development Support Program

*** Please note: The deadline for this call has now passed. Thank you to all the applicants and for your interest. The below information is being left up for reference.***

Purpose

This program will help researchers refine existing software tools to improve usability and robustness or build new tools, disseminate research software beyond the research space in which it is created, and enhance existing functionality.

The Research Software Development Support Program provides research groups access to a professional research software developer. The research software developer will work alongside the research group on a part-time (up to a 0.5 FTE) basis for 2 to 6 months.

Please note:

  1. There is no direct funding available through this program, but rather access to time with the Data Sciences Institute Research Software Development Team.
  2. Researchers who have submitted an application for a previous support period may simply send an email to softwaredev.dsi@utoronto.ca indicating they would like to be considered again. A second application is not necessary.

  1. Eligible applicants include all professorial staff eligible to hold research funding at the University of Toronto (U of T) orexternal funding partners and must satisfy the additional eligibility criteria below. 
  2. Each PI and any co-PIs must have a budgetary appointment at U of T or at a DSI External Funding Partner. For U of T, budgetary appointments are continuing, full-time academic appointments with salary commitments from a University of Toronto academic unit.  
  3. Applicants must be a member of the DSI.
  4. Researchers can be Co-PIs on only one submitted application.
  5. Only open-source projects will be considered.

Interested researchers can apply to this program by completing this short application form (Please note: This form was created for use with Adobe Acrobat. Opening the form with other software, like Mac's Preview, may result in it not responding correctly.) that:

  • Describes the problem requiring support from the Research Software Development Team (1/4 page). 
  • Describes the scope of the required software, how it is intended to be used, and how it might be used by other groups. Explain why existing software is not sufficient (1/2 page).
  • Explains the current status of the software to be developed, including an estimate of the number of current users and an estimate of the number and range of intended users after working with the Research Software Development Team (1/4 page).
  • Proposes a strategy for engaging with and supporting the Research Software Development Team to ensure a successful outcome within the intended timeframe (1/4 page).
  • We would like to encourage cross-disciplinary interactions to increase the impact of this program. Please describe how the software could be re-used outside of your discipline and include a plan for such re-use if possible (e.g., describe a specific data set from another discipline that would be usable by the software, include a co-applicant and corresponding use case from another discipline) (1/4 page).

Please email the application form as a PDF document to softwaredev.dsi@utoronto.ca by October 21, 2022, at 12 pm noon EST. The file should be named [Last name, First name DSI ResSoftware].

Researchers are invited to meet with the DSI’s Research Software Developer to discuss their projects before submitting their applications. This will likely be more important for researchers less familiar with software development and less important for those with good software development experience and ongoing software projects. Please reach out to the developer directly at conor.klamann@utoronto.ca to schedule a meeting. To make this meeting as productive as possible, applicants are encouraged to complete the research software development checklist ahead of time. This checklist also contains information that may be useful to include in the application.

Applications will be assessed by a member of the DSI Executive, the software developer team, and additional UofT staff with software development expertise using the criteria outlined below.

  • Quality of supported research project
  • Quality of the technology choices required for the software project, and requirement for new software compared to using existing solutions
  • Project scope, timelines, and goals are clear and appropriate for the resources of the call
  • Impact and re-use potential of the software for research
  • Fit with research software developer team skills
  • Quality of plan to engage with the research software developer team (e.g., defining requirements, involvement with software development and testing process)

Highly ranked applications may be invited to discuss their proposals in more detail with the selection committee who will then pick the three or six projects that they consider to be the best fit for the program. During the assessment process, information about the application may be posted publicly at https://github.com/UTorontoDataScience/research-software-development-support/issues to facilitate project tracking and selection in a transparent manner. 

  • October 21, 2022: Applications are due at 12 pm noon EST
  • November 18, 2022: Applicants may be invited to discuss their proposals if more information is necessary.
  • Projects will begin after December 7, 2022.

  • The Project and related findings must be presented in oral or poster format at the DSI Research Day in the year or in the immediately subsequent year the award is made.
  • As a reporting requirement, it is expected that applicants respond promptly to surveys, questionnaires, or inquiries from the DSI on topics such as papers submitted to or accepted for publication in peer-reviewed journals, oral and poster presentations given at seminars, scientific meetings, or conferences and competitive applications submitted to external agencies for funding. Applicants will be notified of submission dates and format requirements for this reporting.

For further information:

Professor Gary Bader, Associate Director, Data Management, Research Software, Advanced Research Computing, Data Sciences Institute, hosted an information session on research software development support on November 11, 2021. The webinar’s recording and slides are available  here as are the PDF Slides.

For more information, please contact: conor.klamann@utoronto.ca

News:

With the help of the DSI’s software development support program, Dr. Gregory Schwartz and his team at the University Health Network, are working on a suite of tools designed for clustering and visualizing single-cell data, to better understand heterogeneity and drug resistance in cancer.

Read the full story.

Past Recipients:

Alan Moses from the Department of Cell & Systems Biology, Faculty of Arts & Science, and Julie Forman-Kay from The Hospital of Sick Children are working to create a software program to help the research community with intrinsically disordered regions.

Dorothea Kullmann from the Department of French, Faculty of Arts & Science will work with the DSI to develop a database consisting partly of late medieval manuscripts.

Eunice Eunhee Jang from the Department of Applied Psychology and Human Development, OISE is working on curriculum-based learning tools that assess and track children’s emergent literacy and language development. 

Ewan Dunbar from the Department of French, Faculty of Arts & Science is working to create a web interface that allows speech researchers to upload audio files and download “speech features” useful for speech processing.

Gregory Schwartz, University Health Network, and his team identified rare cancer cells which may contribute to disease progression. He is working to better understand cellular heterogeneity, by developing a suite of tools for clustering and visualizing single-cell data called TooManyCells.

Laura C. Rosella, Dalla Lana School of Public Health and Birsen Donmez, Department of Mechanical and Industrial Engineering, Faculty of Applied Science and Engineering are working to apply Human Factors Engineering methods to build a user-friendly decision support tool for the Chronic Disease Population Risk Tool (CDPoRT).

Read the full story.