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Module 5: Open Results

Welcome to Open Results! This module focuses on giving you the tools you need to kick-start a scientific collaboration by creating contributor guidelines that ensure ethical contributorship. It starts out with a use case of open science in action, then a review of how to discover and assess open results. Next, the focus is on how to publish results which includes a task checklist. The module wraps up with specific guidance for writing the sharing results section of the Open Science and Data Management Plans (OSDMP). We will also reflect on how our society and technology are constantly evolving in the way we do science.

Learning Objectives

After completing this module, you should be able to:

  • Describe what constitutes an open result.
  • Explain what the reproducibility crisis is and how open science can help combat it.
  • Use a process to discover, assess and cite open results for reuse.
  • List the responsibilities of the following participants that are creating open results: open results user, project leader, collaborator, contributor and author.
  • List the tasks for creating reproducible results and the items to include in a manuscript to ensure reproducible results.
  • Define a strategy for sharing your results including selecting publishers, interpreting journal policies and licenses, and determining when to share your data or software with your manuscript.

Lesson 1: Introduction to Open Results:

This lesson aims to broaden your perspective regarding what shareable research outputs are produced throughout the research lifecycle. We will first consider what constitutes an open result. To do so, we will read an example of a forward-thinking research project that utilizes open result best practices. The perspectives gained from this example will ultimately get us thinking about how we can work towards creating reproducible research.

Lesson 2: Using Open Results:

By the end of this lesson, you will be familiar with resources for open results utilization, how and when to cite the sources of the open results that you use, how to provide feedback to open results providers, and how to determine when it is appropriate to invite authors of the open results materials to be formal collaborators versus simply citing those resources in your work.

Lesson 3: Making Open Results:

In this lesson, we focus on making open results. We will start by discussing what it means to make reproducible results. Having earlier in the course discussed the computational reproducibility practices in open software, in this lesson, we specifically emphasize the importance of collaborations in making those results open and reproducible. This begins with acknowledging that the scientific results are not made by single individuals. We will then teach how to ensure equitable, fair, and successful collaborations when making your open results that acknowledge all contributions. Once you’ve planned the rules of engagement, we will provide you with ways to ensure that your reporting and publication abide by open results principles and combat the reproducibility crisis.

Lesson 4: Sharing Open Results:

In this lesson we will place emphasis on publishing manuscripts as open access. You will learn what subtleties to consider when determining what journal to publish in, including how to make sense of a journal’s policies on self-archiving. Finally, we discuss some commonly held concerns about sharing open access publications, and how to overcome them. Ultimately, we want to ensure that you have confidence in your decision to publish as open access.

Lesson 5: From Theory to Practice:

In this lesson, we tie the concepts from previous lessons together with some specific guidance for writing the Sharing Results section of an Open Science and Data Management Plans (OSDMP). We will also reflect on how our society and technology constantly evolve, as does the way we do science. A new technology with the potential to radically alter the way we do and share science is artificial intelligence (AI), particularly when it comes to language learning models. These AI tools are already changing how we interact with written text. In this lesson, we discuss some of the ways that AI is and will affect how we do and share our science.

Additional Resources

In addition to the TOPS module training, the community resources below are excellent information sources about open science.