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description: The "Storytelling in Grant Writing" workshop introduced participants to the power of narrative in crafting compelling grant proposals, emphasizing emotional engagement and data-driven storytelling.
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slug: blog_storytelling_in_grant_writing
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authors: [Ajith Akuthota]
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tags: [announcement, workshop, open source software, research software]
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hide_table_of_contents: false
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---
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Julie Turner presented the "Storytelling in Grant Writing" workshop, offering valuable insights into how narratives enhance grant proposals. The event highlighted strategies for combining emotional connection with data to create compelling grant narratives—an approach particularly relevant to researchers and developers working on open source and research software projects.
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The workshop was facilitated by **Jenna Gorlewicz, Associate Dean**, who emphasized the importance of storytelling in communicating research vision effectively in grant applications. In her follow-up, Jenna noted that storytelling is an essential component of sharing the vision of research, making it a powerful tool for grant proposals across disciplines, including open source and research software development.
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**What:** Storytelling in Grant Writing Workshop
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**Who:** Presented by Julie Turner
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**When:** Wednesday, Oct 23, 11:00 a.m.–12:00 p.m.
### **Why Storytelling Matters for Open Source and Research Software**
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Julie emphasized the unique challenges faced by researchers and developers seeking funding for open source and research software projects:
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-**Justifying Community Impact:**
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Open source software thrives in collaborative environments where community engagement is critical. Storytelling can highlight how the software meets specific community or research needs, fostering a deeper connection with grant reviewers.
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-**Balancing Metrics with Narrative:**
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While data-driven results are essential, integrating personal stories—like how a bioinformatics API empowers researchers in underfunded labs—can make a proposal more memorable.
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-**Illustrating Long-Term Benefits:**
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For research software, storytelling helps convey broader impacts, such as advancing scientific discoveries or making computational tools accessible globally.
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### **Workshop Highlights**
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1.**Introducing Characters and Context**
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- Showcase developers, researchers, or end-users behind the software.
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- Create a vivid picture of the problem the software solves, emphasizing real-world relevance.
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2.**Building Tension in the Proposal**
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- Highlight challenges in sustaining open source and research software without institutional funding.
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- Use conflict—such as the limitations of proprietary tools—to justify the need for open, scalable alternatives.
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3.**Crafting the Narrative**
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-**Orientation:** "This software was born out of a need for accessible computational tools in underserved regions."
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-**Complication:** "However, without sustainable funding, maintaining quality and usability for the community is challenging."
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-**Resolution:** "With grant support, we will extend functionality, provide training, and ensure long-term impact."
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### **Real-World Applications**
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The workshop’s lessons directly apply to open source and research software. For example:
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- A **collaborative bioinformatics tool** that accelerates genomic research. A strong narrative could highlight its potential for advancing cancer research in resource-constrained labs.
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- A **climate modeling software** where storytelling underscores the urgency of accessible tools to address global environmental challenges.
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### **Additional Insights from the Associate Dean**
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Jenna Gorlewicz emphasized that storytelling is integral to all grant applications. It plays a vital role in sharing the research vision, a necessity for connecting with funders. She also highlighted resources available for researchers, including:
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-**Research Lunch and Learn series:** Monthly sessions, such as the November session on *Using the PI Dashboard for Managing Grants*.
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-**External proposal review resources:** Providing feedback to refine submissions.
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-**Mentorship programs:** Facilitating guidance for early-career researchers navigating grant writing.
Copy file name to clipboardExpand all lines: docs/project_dads/about.md
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title: DADS
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---
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<!-- A header image is optional; if used should be no greater than 200x600 -->
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<!-- -->
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## Overview
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The goal of this project is to create a flexible, web-based, search-driven user interface for a database of arithmetic dynamical systems. The web-based interface to access the data will be search-driven making tasks such as locating examples with specific properties or examining the collective statistics of certain sets of dynamical systems as simple as possible. This data will be able to be exported for further analysis. This type of searchable rich data set will save researchers countless hours of computation as well as provide a means to identify previously unknown patterns and connections. The application allows users to find and filter dynamical systems, with different statistics of the filtered results calculated.
- Louis Rolwes (alumni) [<imgsrc="/img/github.svg"alt="github"width="25"height="25" />](https://github.com/lRolwes)
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- Thomas McGuigan (alumni) [<imgsrc="/img/github.svg"alt="github"width="25"height="25" />](https://github.com/thomasmcg77)
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-**Start Date:** Mar, 2023
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-**Adoption Date:** Mar, 2023
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-**Technologies Used:**
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-**Technologies Used:**
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- React
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- Flask
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- PostgreSQL
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### User Guide
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Upon launching the web application the users are taken to the Home page of the application where they see information about the application. User needs to click on "Dynamical Systems" page which loads all the systems in the page in a table. User can apply filters based on dimension, degree, class and other attributes. User can also click on a row and can get more information about the selected row. On the right side, user can see a few statistics of the filtered results.
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Upon launching the web application the users are taken to the Home page of the application where they see information about the application. User needs to click on "Dynamical Systems" page which loads all the systems in the page in a table. User can apply filters based on dimension, degree, class and other attributes. User can also click on a row and can get more information about the selected row. On the right side, user can see a few statistics of the filtered results.
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## Technical Information
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## Get Involved
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If you would like to contribute to this project, please visit our [GitHub page](https://github.com/oss-slu/dads) to create your own issues or pull requests.
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If you would like to contribute to this project, please visit our [GitHub page](https://github.com/oss-slu/dads) to create your own issues or pull requests.
MeltShiny is a software application that automates the analysis and visualization of DNA melting curves for researchers in chemistry, biology, and genetics. It is built on tools like MeltWin and MeltR, resulting an intuitive graphical user interface with robust data processing capabilities powered by R. MeltShiny removes the need for manual curve fitting with just a few clicks, researchers can upload their DNA melting data and automatically generate graphs and tables. Key benefits include automated outlier removal, compatibility with modern operating systems, and accessibility for non-programmers. By streamlining tedious tasks like handling file formats and filtering data, MeltShiny allows researchers to focus their time on scientific analysis and interpretation. Its simple yet powerful interface makes complex computational analysis of DNA thermodynamics accessible to scientists with varied technical skill levels.
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MeltShiny is a software application that automates the analysis and visualization of DNA melting curves for researchers in chemistry, biology, and genetics. It is built on tools like MeltWin and MeltR, resulting an intuitive graphical user interface with robust data processing capabilities powered by R. MeltShiny removes the need for manual curve fitting with just a few clicks, researchers can upload their DNA melting data and automatically generate graphs and tables. Key benefits include automated outlier removal, compatibility with modern operating systems, and accessibility for non-programmers. By streamlining tedious tasks like handling file formats and filtering data, MeltShiny allows researchers to focus their time on scientific analysis and interpretation. Its simple yet powerful interface makes complex computational analysis of DNA thermodynamics accessible to scientists with varied technical skill levels.
- Anthony Hampton (alumni) [<imgsrc="/img/github.svg"alt="github"width="25"height="25" />](https://github.com/adhampton110)
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-**Start Date:** July 2022
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-**Adoption Date:** July 2022
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### User Guide
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MeltShiny has some dependencies which will need to be installed for the program to run. R Package installer files have been included, with the names MeltShinyDependenciesInstaller.command and MeltShinyDependenciesInstaller.bat for MacOS and Windows, respectively. These files are found within the MacOS_Scripts and Windows_Scripts folders found within the MeltShiny application bundle.Note, that in order for the Windows version to work, you must add the R bin folder to your PATH variable. For MacOS, the script can be used without any additional work. Double clicking MeltShinyDependenciesInstaller.command or MeltShinyDependenciesInstaller.bat for Mac and Windows, respectively, will open up a terminal.
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MeltShiny is a web-based tool designed for researchers to easily analyze and visualize DNA melting curves.
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**Access the Web App**: Open the MeltShiny web app on any modern browser.
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**Upload Your Data**: Use the "Upload Data" section to upload files in .csv format.
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**Visualize Results**: Customize and generate graphs in the "Visualize Data" section to explore melting curves and other data.
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**Analyze and Export**: View detailed thermodynamic parameters in the "Analysis" section and export findings in preferred formats.
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**Get Help**: Visit the "Help" section for guides and support, or contact our team directly for assistance.
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MeltShiny streamlines complex DNA data analysis, allowing researchers to focus on scientific insights.
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## Installation
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MeltShiny requires specific dependencies to function correctly. Installation files for R packages are included in the application bundle:
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-**MacOS**: MeltShinyDependenciesInstaller.command (located in the MacOS_Scripts folder)
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-**Windows**: MeltShinyDependenciesInstaller.bat (located in the Windows_Scripts folder)
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**Important Notes:**
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-**Windows Users**: Ensure that the R bin folder is added to your PATH variable for proper execution.
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-**MacOS Users**: The script can be run directly without additional configuration.
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## Technical Information
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### Development Priorities
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- Latest R version required
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- Knowledge on Shiny server
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- Implement user-friendly UI
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- Require automated testing
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- Version Control and Collaboration
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-**Latest R version required** : Ensure compatibility with the most recent version of R.
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-**Knowledge on Shiny server** : Expertise in Shiny server setup and management.
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-**Implement user-friendly UI** : Develop a clean, intuitive interface for ease of use.
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-**Require automated testing** : Implement comprehensive testing to ensure reliability.
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-**Version Control and Collaboration** : Utilize version control systems and collaboration tools for effective project management.
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### Additional Details:
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-**Project Goals**: Improve user experience by continuously incorporating feedback from researchers and addressing emerging needs in DNA melting curve analysis.
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-**Future Enhancements**: Explore integration with additional data formats, enhance error-handling capabilities, and expand visualization options.
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-**Community Engagement**: Actively seek contributions from the open-source community to foster collaboration and innovation.
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