Open Science 101 is designed to introduce NASA-funded scientists or future NASA-funded scientists to the benefits and principles of open science such that they can upskill and continue collaborating with NASA science activities. The Open Science 101 curriculum will help participants gain an understanding of the open science ethos and workflow, show participants the tools needed to follow an open science process and thus actively participate in open science communities, and help to familiarize participants with the benefits of open science to their research and beyond.
The following Open Science 101 structure will help reinforce these primary objectives.
- Lesson 1: What is Open Science?
- Lesson 2: Why is Open Science Important?
- Lesson 3: How to Do Open Science
- Lesson 4: When Not to be Open
- Lesson 5: Planning for Open Science: From Theory to Practice
- Lesson 1: Introduction to Open Science Tools
- Lesson 2: General Tools for Open Science
- Lesson 3: Tools for Open Data
- Lesson 4: Tools for Open Code
- Lesson 5: Tools for Open Results
- Lesson 1: Introduction to Open Data
- Lesson 2: Using Open Data
- Lesson 3: Making Open Data
- Lesson 4: Sharing Open Data
- Lesson 5: From Theory to Practice
- Lesson 1: Introduction to Open Code
- Lesson 2: Using Open Code
- Lesson 3: Making Code Open
- Lesson 4: Sharing Open Code
- Lesson 5: From Theory to Practice
- Lesson 1: Introduction to Open Results
- Lesson 2: Using Open Results
- Lesson 3: Making Open Results
- Lesson 4: Sharing Open Results
- Lesson 5: From Theory to Practice
The following outline combines the initial brainstorming and framing by the TOPS curriculum team, to provide interested community members with further details on the content of the completed Open Science 101 curriculum. The structure presented above is used in this outline.
Welcome to this introductory module on open science. Open Science is the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity. In this module, you take a closer look at what open science is, the current landscape as well as the benefits and challenges. You then get a glimpse into the practice of open science, including a case study. To start your journey with open science, you are presented with actions that you can take starting today, such as exploring communities that you can engage with.
Key Terms: Open science, open data, open source, open access, interdisciplinary, equitable, citizen science or community service, open research, open scholarship, reproducibility and replicability, peer review, FAIR principles, metrics [in context of scientific merit], altmetrics, openness, transparency, rigor, and computational provenance
- Explain what open science is, why it's a good thing to do, and list some of the benefits and challenges of open science adoption.
- Describe the practice of open science, including considerations when writing a management plan and the tasks in the "Use, Make, Share" framework.
- Evaluate available options when determining whether research products should or should not be open.
- List ways to connect with others who are part of the open science community.
Lesson 1: What is Open Science?
- Explain the motivation to do open science and the goals of open science.
- Define open science.
- List different groups that practice open science.
Lesson 2: Why is Open Science Important?
- Describe the ways in which open science benefits your career with attribution, reach, and more collaborations.
- Describe the ways in which open science can advance science.
- List the benefits society receives when open science principles are adopted.
Lesson 3: How to Do Open Science
- List reasons information should not be shared due to security or privacy issues.
- Define what intellectual property is and recall the different ways it can be shared openly through licenses or the public domain.
- Recognize sharing policies and procedures of your department, organization, funding agency, and publication in order to make the most responsible science sharing decisions.
Lesson 4: When Not to be Open
- Recognize your own fears and concerns for adopting open science, and list mitigation strategies for overcoming them.
- List common barriers to practicing open science that occur from misaligned incentives and mitigation strategies.
- List several social challenges that can arise when practicing open science and strategies for communicating effectively to overcome differences in perspective.
- List several institutional and infrastructure barriers to doing open science and mitigation strategies where available.
Lesson 5: Planning for Open Science: From Theory to Practice
- List considerations to include in a planning for open science and define an open science and data management plan (OSDMP).
- Describe the different parts of the scientific workflow and how open science can be integrated into it.
- Differentiate real world examples of how a team can use open science.
- List four steps that anyone can take to be more open.
This module is designed to help you get started on your journey to practicing open science. It offers an introductory view of the concepts and resources that are fundamental to open science. The bridge between the concepts and the practice of the concepts is something called the use, make, share framework. There are many methods and models that define how to get started with open science. The use, make, share framework was constructed to help you immediately assign purpose to the concepts and tools that are covered in this module as well as in the entire Open Science 101 curriculum. All of the information that you learn here will be addressed in more detail as you participate in other modules but can also be applied immediately after completing this module.
Key Terms: Virtual machine, metadata, data repository, computing environment, ORCiD, Persistent Identifiers (PIDS), and Digital Object Identifiers (DOIs)
- Define the foundational elements of open science, which includes research products, the “Use, Make, Share” framework, and the role of an Open Science and Data Management Plan.
- List and explain the purpose of resources used to discover and assess research products for reuse, including repositories, search portals, publications, documentation such as README files, metadata, and licensing.
- Develop a high-level strategy for making and sharing data that employs the FAIR principles, incorporates a data management plan, tracks data and authors with persistent identifiers and citations, and utilizes the appropriate data formats and tools for making data and sharing results.
- Describe the software lifecycle and design a high-level strategy for making and sharing software that considers the the use of a software management plan, the tools needed for development including source code, kernels, programming languages, third-party software and version control, and the tools and documentation used for publishing and curating open software.
- List the resources for sharing research products including preprints, open access publications, reference management systems, and resources to support reproducibility.
Lesson 1: Introduction to the Practice of Open Science
- Define common types of research products including data, software, and results.
- List common ways to share data, code, and results while practicing open science.
Lesson 2: General Tools for Open Science
- Recall the definition of open science tools.
- Describe what a persistent identifier is and state an example.
- List a few commonly used open science tools that support research.
- List the components of an Open Science and Data Management Plan and what they include.
Lesson 3: Tools for Open Data
- Define the different types of scientific data.
- Define what the acronym FAIR means and explain how it supports the sharing of open data.
- Identify data management practices and tools to locate data in repositories.
- List and explain the purpose of the resources commonly used in making data including the data formats, inspecting data, and assessing ‘FAIR’-ness of data.
Lesson 4: Tools for Open Code
- Explain the benefits of using tools for open code development.
- Define version control and understand how it supports collaboration in the development and management of code.
- List a few tools for editing software and some of their features.
- Distinguish between software repositories and software archives.
Lesson 5: Tools for Open Results
- Describe some of the benefits of preprints and identify resources for open access journals.
- List commonly used tools that increase the reproducibility of a result.
- List applications for project management and reference management.
This module focuses on the practice and application of open science for data. It provides a ‘how to’ process for finding and assessing open data for use, for making open data and for sharing open data. The step-by-step flows are easy to follow and can be used as checklists after you complete the module. Some of the key topics discussed include: data management plans, the process for assessing data for reuse, creating a plan for making data including choosing open formats and adding documentation, and the considerations for sharing data and making your data citable.
Key Terms: Copyright, data, data license, CC-BY and CC0 license, data management plan, metadata, machine-readable persistent identifiers (PID), findable (data), accessible (data), interoperable (data), reusable (data), and dataflow
- Describe the meaning and purpose of open data, its benefits, and how FAIR principles are used.
- Recall methods to assess the reusability of data based on its documentation, and cite the data as instructed.
- Implement an open data management plan, select open data formats, add the needed documentation, including metadata, README files and version control, to make the data reusable and findable
- Evaluate whether your data should and can be shared.
- Recall practices to make data more accessible, including the registration of an affiliated DOI and the inclusion of citation instructions in documentation.
Lesson 1: Introduction to Open Data
- Define the concept of open data.
- List a few benefits of and challenges to creating open access data.
- List a few benefits of implementing FAIR principles to the practice of open science.
- Describe how to plan for open data.
Lesson 2: Using Open Data
- Select data sources and use search techniques to discover open data.
- Assess if a dataset incorporates open access elements that ensure easy reusability.
- Explain the importance of citing open data, and find and follow citation instructions.
Lesson 3: Making Open Data
- Evaluate and select open data formats.
- Add documentation that enables other researchers to assess the relevance of the data. This includes metadata, README files, and version control.
- List two common open licenses used for datasets.
Lesson 4: Sharing Open Data
- Recognize institutional variables, issues of security, and timing that affect your decision to share data.
- Recall the features, inherent responsibilities, funding considerations, and sponsor requirements that researchers should consider when selecting a repository to share data.
- Describe the tools and list some best practices that optimize the shareability of data.
Lesson 5: From Theory to Practice
- Describe the steps toward writing a data management plan.
- List opportunities for involvement in the open data communities.
- Identify additional open science resources and list ways to continue training.
This module focuses on the practice and application of open code as part of the open science workflow. It provides a ‘how to’ process that follows the code development lifecycle and “Use, Make, Share” framework. Some of the key topics discussed include: benefits and limitations of open code, how to discover and assess code, considerations and methods for programming following open principles, and finally when and how to share your code.
Key Terms: Source code, software, software license, open-source license, open-source software, closed-source software, derivative work, version control, code repository vs. software repository, and long-term repository
- Explain what open-source software means, including the software development cycle, the benefits, some common limitations, and how they are addressed.
- Assess open-source software for reuse by evaluating provided documentation, including README files and licensing details, and then cite the software appropriately.
- Create an open-source software management plan that includes the strategy for selecting open software dependencies and open repositories such as GIT, and how open elements including metadata, README files and version control, will be included to make the software reusable and findable.
- Evaluate whether your open-source software can be shared and the best options for sharing to increase visibility.
- List the responsibilities a software developer has once the open-source software is shared including managing legal requirements and ensuring the software is maintained.
Lesson 1: Introduction to Open Code
- Define open-source software and distinguish it from closed-source software.
- List common benefits and challenges to the production of open code and describe how researchers can respond to some of the challenges while maximizing openness when appropriate.
- Describe the function and purpose of a Software Management Plan, as its utility as a guidebook for everyone involved in a scientific project.
Lesson 2: Using Open Code
- Describe the process of using open code and list some key elements of discovering code.
- Describe the four key considerations when assessing open software: functionality, interoperability, security, and licenses.
- List some common problems that arise when reusing Open Code and best practices to resolve them.
- Describe how, where, and under what circumstances one should acknowledge (cite) code.
Lesson 3: Making Code Open
- Describe the key considerations when planning a new open software project.
- List three reasons for projects to use version control.
- Explain the purpose and recall general information typically included in a README file.
- Be able to select a license for your code and list the differences between permissive and protective open-source software licenses.
- Explain best practices in software development that support transparency, inclusion, and reproducibility.
Lesson 4: Sharing Open Code
- Describe what it means to share code: for archiving or for code development.
- Evaluate whether you should share your code and list important security considerations.
- Describe best practices for when and where to share code.
- Recall commonly used practices to help others reuse your code.
- List the roles and responsibilities for sharing and maintaining shared code.
Lesson 5: From Theory to Practice
- Recall the definition of a software management plan, potentially as part of an open science and data management plan, and where to find helpful resources.
- List ways to engage with and contribute to open software communities.
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.
Key Terms: Research objects, predatory publishing, preprint, preregistering, persistent identifiers, reproducibility crisis, DOI, and code of conduct
- 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
- Describe what constitutes open results and list the research objects that can be created throughout a research cycle.
- Describe how sharing open results can advance science and your career.
- Explain what the reproducibility crisis is and how open science can help combat it.
Lesson 2: Using Open Results
- Identify a variety of open results sources including both published science research and non-traditional sources.
- Evaluate the reliability and quality of open results sources based on key characteristics.
- List the responsibilities of an open results user, including providing feedback to open results developers.
- List the ways to cite open results into your own research process.
Lesson 3: Making Open Results
- Identify approaches to make different types of open results.
- Recognize the importance of collaboration in making results.
- Develop contribution guidelines to enable recognition of contributors who make results.
- Combine different open results to create scientific reports and reproducible outputs.
Lesson 4: Sharing Open Results
- List ways that you can share open results to become a more collaborative, effective, scientist.
- List different types of open access publications and considerations when sharing like licenses.
- List some of the concerns around open access publishing, including responsibilities for authors, the threat of predatory publishers, and the fear of being wrong.
Lesson 5: From Theory to Practice
- List what to include in an OSDMP for sharing results openly.
- List some concrete steps toward sharing results openly.
- Describe how emerging technology like AI is currently impacting how we use, make, and share our science.