From e4f0924482aa00a7773cfaaea1c9e13e920a3d0a Mon Sep 17 00:00:00 2001 From: Brian Ressler Date: Fri, 4 Aug 2023 18:45:57 -0500 Subject: [PATCH] Update curriculum structure Changes per ARC curriculum team. --- .../Open-Science-101/curriculum_structure.md | 426 ++++++++++-------- 1 file changed, 236 insertions(+), 190 deletions(-) diff --git a/docs/Area2_Capacity_Sharing/Open-Science-101/curriculum_structure.md b/docs/Area2_Capacity_Sharing/Open-Science-101/curriculum_structure.md index 0a7e0eb29..a89836ab2 100644 --- a/docs/Area2_Capacity_Sharing/Open-Science-101/curriculum_structure.md +++ b/docs/Area2_Capacity_Sharing/Open-Science-101/curriculum_structure.md @@ -1,31 +1,31 @@ -# Proposed Open Science Curriculum Structure +# Open Science Curriculum Structure -The purpose of the Transform to Open Science curriculum, the Open Science 101, is 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 should help participants gain a nuanced **understanding** of the open science ethos and workflow, show participants the tools needed to follow an open science **process** and thus actively participante in open science communities, and help to familiarize participants with the **benefits** of open science to their research and beyond. +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. -Currently, no prerequisites are proposed for the Open Science Curriculum, as we want to make this course as accessible as possible. In the future, this course may itself be a prerequisite to more advanced or in-depth material, see end of this document for ideas. TOPS is also developing incentives to motivate scientists to take the course. More information on these can be found in [Area 3: Incentives](/docs/Area3_Incentives/readme.md) +Prerequisites are proposed within each of the modules. -The following is a proposed structure for the Open Science 101, to help reinforce these primary objectives. +The following Open Science 101 structure will help reinforce these primary objectives. ### Ethos of Open Science -* Lesson 1: Introduction to the Ethos of Open Science: What is open science? Why should science be open? -* Lesson 2: Basic Open Science Principles: Background of open science and introduction to leading practices and considerations. -* Lesson 3: Open Science Communities: Discussion of different open science communities, how they support science, and how to participate. -* Lesson 4: Benefits and Challenges of Open Science -* Lesson 5: Community Stories, Resources and Policy +* 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: Where to Learn More -### Open Science Tools & Resources +### Open Tools & Resources * Lesson 1: Introduction to Open Science Tools -* Lesson 2: Tools for Open Data -* Lesson 3: Tools for Open Software -* Lesson 4: Tools for Open Results -* Lesson 5: Community Stories, Resources and Policy +* Lesson 2: Concepts and Tools for Using Research Products +* Lesson 3: Concepts and Tools for Making Open Data and Results +* Lesson 4: Concepts and Tools for Making Open Software +* Lesson 5: Concepts and Tools for Sharing (Publishing) Open Products ### Open Data * Lesson 1: Introduction to Open Data * Lesson 2: Using Open Data * Lesson 3: Making Open Data * Lesson 4: Sharing Open Data -* Lesson 5: Community Stories, Resources and Policy +* Lesson 5: Community, Resources and Next Steps ### Open Software * Lesson 1: Introduction to Open Software @@ -39,187 +39,233 @@ The following is a proposed structure for the Open Science 101, to help reinforc * Lesson 2: Using Open Results * Lesson 3: Making Open Results * Lesson 4: Sharing Open Results -* Lesson 5: Community Stories, Resources and Policy - -## Proposed Detailed Outline -The following outline combines the initial braintorming and framing by the TOPS curriculum team, to provide interested community members with further details on the possible content of the completed Open Science 101. The structure presented above is used in this outline. - -### Module 1: Ethos of Open Science -*By the end of this module, learners will be familiar with the definitions central to open science and have explored some concrete examples of the benefits of open science principles and practices. The course will include best practices for building open science communities, increasing collaboration, and introducing open principles to project design, as well as an overview of open science norms. This module will also explore the historical impact of “closed” science, and how open science seeks to create a more diverse and equitable scientific community.* - -Key Terms: Open science, open data, open source, open access, interdisciplinary, equitable, citizen science, open research, open scholarship, reproducibility and replicability, peer-review, FAIR principles, metrics [in context of scientific merit], altmetrics, openness, transparency, rigor, computational provenance - -**Lesson 1: Introduction to the Ethos of Open Science** -* What is open science, why does it matter to specific research projects, science writ large, and society -* How does open science connect to the history of research, publication and academic merit? -* Why should we [e.g., early career researchers, NASA scientists] do it -* Explanation of how open science is critical for building public trust in science and influencing key societal challenges -**Lesson 2: Basic Open Science Principles** -* Short background on open science practices and principles -* Leading practices and considerations, key components and behaviors -* Brief overview of the motivation behind open science frameworks and workflows -* Guiding practices and principles related to open results and the advantages of implementing them across stages of a research process +## Detailed Outline -**Lesson 3: Open Science Communities** -* How to select open science communities that are compatible with a research project +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. -**Lesson 4: Benefits and Challenges of Open Science** -* Benefits of open science (e.g., climate change research, DEIA, collaboration, innovation, technology advancement) -* The intersection of open science and metrics, and how to prove merit with alternative metrics -* Challenges of open science - -**Lesson 5: Community Stories, Resources and Policy** -* How open science as created an amazing ecosystem of tools and resources which will be touched upon in the coming lesson - -### Module 2: Open Tools -*By the end of this module, a learner will have gained hands-on experience working with different open science tools, databases/datasets, and policies. Learners should have been introduced to open science communities within their field of study.* - -Key Terms: Virtual research environments (VRE), SMART goals, advocacy, metadata, data repository, executable papers, Permanent URLs (PURLs) or Digital -Object Identifiers (DOIs) - -**Lesson 1: Introduction to Open Science Tools** -* What open tools are currently “the default” for the open science community -* Explain why open science tools are valuable and how they enable open data, open software and open results -* Why open science tools encourage scientific practice - -**Lesson 2: Tools for Open Data** -* Please include Zenodo and how to select a data repository -* How to use data dictionaries - -**Lesson 3: Tools for Open Software** -* Please including GitHub, Jupyter, Posit -* How to select a good software tool (e.g., GitHub integration), and how to implement version control - -**Lesson 4: Tools for Open Results** -* Please include ORCID, the use of Twitter and Medium -* Please include executable and/or shared notebooks, virtual research environments, pre-registrations of studies, and interactive science -* The way science is sharing differently today versus a few years ago -* How to think about the impact of your work -* How to think of collaborations - -**Lesson 5: Community Stories, Resources and Policy** -* Provide examples of how open science is practiced in different scientific fields -* How open tools have made it easier to share data, software and results -* Final call to action! +### Module 1: Ethos of Open Science +Welcome to this introductory module on Open Science. Open Science is a philosophy and practice of making science available for all, while accelerating and expanding scientific advancements. In this module, learners take a closer look at what Open Science is, the current landscape as well as the benefits and challenges. Learners then get a glimpse into the practice of Open Science, including a case study. To start your journey with Open Science, learners are offered actions that one can take, including exploring communities that learners can engage with now. + +Key Terms: Open science, open data, open source, open access, ethics, morals, interdisciplinary, equitable, citizen science, open research, open scholarship, reproducibility and replicability, peer-review, FAIR principles, metrics [in context of scientific merit], altmetrics, openness, transparency, rigor, computational provenance + +**Module 1 Learning Objectives** +* Explain what Open Science is, why it's a good thing to do, and the mission of NASA TOPS. +* List the benefits and challenges of Open Science adoption. +* Describe the elements included in the practice of Open Science including considerations when writing the management plan and the tasks in the Use, Make, Share framework. +* Explain some options when evaluating 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? +* Reiterate the definition of Open Science as well as its goals and outcomes +* List at least two examples of research projects that applied Open Science principles +* Explain why we should be doing Open Science now and how the Internet has made it more achievable + +Lesson 2: Why is Open Science Important? +* List the benefits you receive when you adopt Open Science principles in your research. +* List the benefits society receives when Open Science principles are adopted. +* List current challenges with adopting Open Science and how to navigate them. + +Lesson 3: How to Do Open Science +* Explain where Open Science fits in the scientific workflow and what needs to go into an Open Science research plan. +* List the activities and high-level tasks that are part of the practice of Open Science. +* Describe the practical benefits of integrating Open Science principles into a research project. + +Lesson 4: When Not to be Open +* List reasons why research products should not be shared and provide examples. +* Describe the tasks and considerations for sharing controlled research. +* Explain how FAIR, CARE, licensing and intellectual property relate to determining when to share research products. + +Lesson 5: Where to Learn More +* Connect with others who are also part of the Open Science community. + +### Module 2: Open Tools and Resources +This module is designed to help learners get started on their 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 learners 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 one learns here will be addressed in more detail in other modules, but can also be applied immediately after completing this module. + +Key Terms: Metadata, data repository,Persistent Identifies (PIDS), and Digital Object Identifiers (DOIs) + +**Prerequisites** + +Before taking this module, it is recommended that you are familiar with and can define the following. If these are new to you, or you need a refresher, these topics are discussed in *Open Science 101 Module 1: Ethos of Open Science*. +* Open Science as a philosophy +* The principles associated with Open Science including FAIR and CARE +* The benefits of giving credit (citations) when research products are reused + +**Module 2 Learning Objectives** +* Define the foundational elements of Open Science including research products, the use, make, share framework and why Open Science and Data Management Plans are an important practice. +* 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. +* Create a high-level strategy for making and sharing data that considers the FAIR principles, the use of a data management plan, the tracking of the data and authors with persistent identifiers and citations, and the selection of data formats and tools for making data and sharing associated results. +* Describe the software lifecycle and create a high-level strategy for making and sharing software that considers the FAIR principles, 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 lastly the tools and documentation used for publishing and curating open software. +* List the considerations for determining whether a research product can or should be shared and follow the steps in the Open Science Quick Start Guide for sharing data, software, papers, and other results. + +Lesson 1: Introduction to the Practice of Open Science +* Explain the concept of "Open Science". +* List the research products of data, software, and results, and define what each means. +* Describe how the use, make, share framework facilitates the practice of Open Science for data, software, and results. +* Explain why management plans for data, software, and results are important in the practice of Open Science. + +Lesson 2: Concepts and Tools for Using Research Products +* Explain where to discover research products and how version control is used for product selection. +* Discovery sources include repositories, search portals and publications. +* List the resources used to assess research products for reuse and explain why they are important to the assessment process. Resources include: + * Documentation such as README files + * Metadata + * Licensing + +Lesson 3: Concepts and Tools for Making Open Data and Results +* Define what the acronym FAIR means and explain how it supports open data. +* Describe the persistent identifiers that are used for research products and contributors, and how they are used in citations to give and receive credit for research products. +* List and explain the purpose of the resources commonly used in making data including the data management plan, data formats, and tools for inspecting data. +* Define open results and the reasons why considerations for making open results are a part of the data-making process. + +Lesson 4: Concepts and Tools for Making Open Software +* Define what a software management plan is and list the components it includes. +* Describe the software lifecycle and list the tools and techniques that are part of each phase. +* List considerations and examples of source code, kernels, programming languages, third-party software, and version control that can be used for open software development. +* Describe the considerations for publishing and curating open software including the role of FAIR and the inclusions of documentation. + +Lesson 5: Concepts and Tools for Sharing (Publishing) Open Products +* Evaluate whether you can or should share research products by reviewing the governance rules and regulations including CARE, export control, security, intellectual property, and licensing. +* Determine where to post your product for sharing. +* Follow the steps in the Open Start Quick Start Guide to share your data, software, or papers. ### Module 3: Open Data -*By the end of this module, learners should feel comfortable creating a data management plan that follows FAIR principles, including assigning a license/copyright, metadata tagging, and assigning PIDs. Learners should also feel comfortable utilizing and assigning metadata.* - -Key Terms: Copyright, license, CC-BY and CC0 license, data management plan, metadata, machine-readable persistent identifiers (PID), findable (data), accessible (data), interoperable, reusable (data), privacy, sensitivity, de-identification, mediated access, crawl and mine [research articles], analytical reproducibility, dataflow - -**Lesson 1: Introduction to Open Data** -* Basic Principles, Benefits, Challenges and Success Stories -* Introduction to FAIR -* Open data core principles -* Deep dive into metadata -* Describe key characteristics of open data, and understand how to categorize different types of open data -* Broad benefits of open data and its effects on science - -**Lesson 2: Using Open Data** -* How to discover, use, and assess quality data -* How to cite open data created by others -* How data licenses (or their absence) will or will not affect the ability to publish results -* Data citation example (e.g., AGU data citation guidelines, NASA data citation guidelines) - -**Lesson 3: Making Open Data** -* Best practices on how to create open data -* How to make your own open data citable -* Version control of data -* Creating DOIs -* How to determine the right metadata that is needed and how to add metadata to your data (or find where your metadata is) -* How to select a data format -* How to write and/or use a data management plan - -**Lesson 4: Sharing Open Data** -* Best practices for sharing open data -* How to give credit when using open data (e.g., citation of .cff files) -* Selecting a repository or archive for your data, uploading the data to it and getting a DOI - -**Lesson 5: Community Stories, Resources and Policy** -* Legal and security concerns -* Can you share your data in the first place (e.g., PII, security, HIPAA, US export control) -* Intellectual property, copyright, and licensing concerns -* Data licenses: what are they, how to use, and where do you go to choose which option is best (e.g., NASA example SPD-41) -* Communities and resources -* How having open data enables open software +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, license, CC-BY and CC0 license, data management plan, metadata, machine-readable persistent identifiers (PID), findable (data), accessible (data), interoperable, reusable (data), privacy, sensitivity, de-identification, mediated access, crawl and mine [research articles], analytical reproducibility, dataflow + +**Prerequisites** + +Before taking this module, you should know the meaning of, and have experience with, the following concepts. These concepts are covered in *Open Science 101 Module 2: Tools and Resources*. +* FAIR and CARE +* Repositories +* Documentation techniques including metadata, readme files, version control +* Open data file formats +* Sharing concepts including licensing and persistent identifiers such as a digital object identifier (DOI), and an open researcher and contributor ID (ORCiD) + +**Module 3 Learning Objectives** +* Explain what open data means, its benefits, and how FAIR and CARE principles are used. +* Discover open data, assess the data for reuse by evaluating provided documentation, and cite the data as instructed. +* Create 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, and use the data accessibility process, including adding a DOI and citation instructions to enable it to be findable and citable. + +Lesson 1: Introduction to Open Data +* Define what open data is and how the FAIR and CARE principles are used to guide open data practices +* List the benefits of open data +* Explain how the use, make, share framework can be used to modify the scientific plan for open data + +Lesson 2: Using Open Data +* Select data sources and use search techniques to discover open data +* Assess if a dataset is open for reusability by locating and evaluating the documentation, file format, metadata and license details +* Explain the importance of citing open data, and find and follow citation instructions + +Lesson 3: Making Open Data +* Explain the purpose of a data management plan and the topics that should be included +* Evaluate and select open data formats and tools for interoperability +* Add documentation that enables other researchers to assess the relevance of the data. This includes metadata, README files, and version control. +* List the best practices for making data accessible and findable + +Lesson 4: Sharing Open Data +* Describe the process and considerations for sharing data +* Select and work with a repository to manage the lifecycle for your data including transferring and processing your data for accessibility, and maintaining and archiving your data +* Facilitate reusability by creating the citation statement and applying the appropriate data license + +Lesson 5: Community, Resources and Next Steps +* Get involved with open data communities +* Find additional resources +* Obtain more training ### Module 4: Open Software -*By the end of this module, learners will understand the impact of open-source code, and have hands-on practice with choosing a license, creating a README, and uploading code to GitHub/GitLab. Learners will understand the importance of high-quality and documented code. Learners will discuss the impact of open-source software on open science and advancing equity in scientific fields.* - -Key Terms: open-source software, source vs. compiled code, permissive vs. non-permissive license, version control, README, documentation, code repository vs. software repository - -**Lesson 1: Introduction to Open Software** -* Basic Principles, Benefits, Challenges and Success Stories of producing and using open software -* Sharing software as a form of improving impact, reproducibility and and replicability of research (“If the code is good enough to publish a paper, then it is good enough to share”) -* How to identify relevant resources for open software and identify key markers of open software in code - -**Lesson 2: Using Open Software** -* How to discover, use, and assess quality software -* How to cite open software created by others -* How to assess security concerns of open software (e.g., NASA example “do not download a blockchain”) - -**Lesson 3: Making Open Software** -* Best practices on how to create FAIR software (e.g., AGU guidance) -* How to make your own software citable (e.g., citation of .cff) -* Creating and using ORCIDs -* Best practices for code documentation - -**Lesson 4: Sharing Open Software** -* Best practices for sharing open software including selecting a repository, creating a release, getting DOI from Zenodo -* How to give credit when using open software -* How to use and grow software begun by others - -**Lesson 5: Community Stories, Resources and Policy** -* Legal and security concerns -* Can you share your software if created using money from a US agency? How do you find out? How to find information on university/employer/grant guidelines (e.g., NASA ROSES example, NSF example) -* Software release authorizations -* Software licenses, permissive versus less permissive licenses -* Export control in the United States (can point to resources such as this) -* Communities and resources -* How open software impacts research -* How open data and open software enable open results +This module focuses on the practice and application of open science for software. It provides a 'how to' process that follows the software development lifecycle and use, make, share framework. Some of the key topics discussed include: benefits and limitations of open software, how to discover and assess software, considerations and methods for programming following open principles, and finally when and how to share your software. + +Key Terms: open-source software, permissive vs. non-permissive license, version control, README, documentation, code repository vs. software repository, cloud source software, software license, commit, OpenFOAM, MOM6, deal.ll, ASPECT, Fprime, PODAAS, UFS. + +**Prerequisites** + +Before taking this module, you should know the meaning of, and have experience with, the following concepts. If these are new to you, or you need a refresher, these topics are discussed in *Open Science 101 Module 2: Open Tool and Resources*. +* Elements used for open software development including source code, kernels, programming languages, third-party software and version control +* Repositories including GitHub +* Licensing options for software +* FAIR and CARE +* Digital Objective Identifiers (DOI) + +**Module 4 Learning Objectives** +* Explain what open source software means, including the software development cycle, the benefits of open software, and some common limitations and how those are addressed. +* Discover open source software and assess it for reuse by evaluating provided documentation, including README files and licensing details; cite the software when appropriate. +* 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 Software +* Define open software and distinguish it from open (and closed) source software +* List the principles behind open software and describe how they manifest in benefits and challenges +* List some common limitations on open software and describe how researchers can respond to limitations while moving toward openness +* Recognize the elements of the software development lifecycle + +Lesson 2: Using Open Software +* Describe the process of using open software and list some key elements of discovering, assessing, reusing, and acknowledging +* Explain why the README file is the first stop when assessing open software +* Recognize some common open software licenses and describe where they sit on the spectrum of openness +* Describe how, where, and under what circumstances one should acknowledge the use of open software + +Lesson 3: Making Open Software +* List several considerations when planning a new open software project +* Explain one or two reasons for open software projects to use version control +* List a few steps of the basic git process +* Explain some types of information typically included in a README file +* Describe several programming best practices that are essential for open software + +Lesson 4: Sharing Open Software +* Identify and evaluate security concerns when publishing open software +* Recognize the legal responsibilities of software developers +* Identify how to share your software and ways to expand its visibility +* Describe the software developer's responsibilities for maintaining software + +Lesson 5: Community Stories, Resources and Policy +* Recall a few open software success stories and where to find more +* Define communities of practice and list at least one example for open source software +* Identify how to share your software and ways to expand its visibility +* List some benefits of engaging with open source software communities when using open software and building a community when making and sharing open software ### Module 5: Open Results -*By the end of this module, learners will have an in-depth understanding of how open science principles help with increasing the reproducibility and replicability of research, as well as guidelines by which to choose the best location to publish their research. Learners will have hands-on experience with creating a replicable, open science workflow and using a virtual research environment, and practice with some tools that make such a workflow possible.* - -Key Terms: p-hacking, null results, workflow design, study plan, data dictionary, codebook, literate programming, open access [publication], green vs gold open access, embargo period, self archiving, pre-print, “reproducibility crisis”, computational provenance, authorship vs. unique identifiers - -**Lesson 1: Introduction to Open Results** -* Basic Principles, Benefits, Challenges and Success Stories -* Apply open result principles to new and ongoing research projects -* How to identify research stages and elements of research objects that can be considered results -* Identify the guiding practices and principles related to open results and the advantages of implementing them across stages of a research process -* How to utilize open access including an explanation of gold versus green, and the use of pre-prints -* How open results can combat the reproducibility crisis -* How publishing is changing at the present moment, including open archives, reproducible (virtual) notebooks, the use of blogs and Twitter etc. - -**Lesson 2: Using Open Results** -* How to discover, use, and assess open results -* How to cite open results -* How to contribute to and provide constructive feedback to others’ results -* When should you reach out to collaborate versus when can you take a result and build upon it in your own research. How do you make this decision? - -**Lesson 3: Making Open Results** -* Best practices on how to create and communicate open results -* Open results contributor guidelines and opportunities for open and equitable collaborations -* Overview of common issues with results including omitting null results, underpowered study, weak experimental design, underspecified methods, errors, data-dredging, p-hacking… -* Identify paths for publicly communicating results - -**Lesson 4: Sharing Open Results** -* Best practices for sharing results, including how to choose the correct open access journal/site -* How to give credit when using open results of others -* Getting a DOI -* Publishing pre-prints -* Open archives -* Journal options for publishing data and software, sharing executable notebooks - -**Lesson 5: Community Stories, Resources and Policy** -* Legal and security concerns -* Can you openly share all results? -* How copyright interacts with open access and how authors can keep control of their work -* How do you determine the rules around sharing of your university/agency/employer/grant (e.g., NASA example) -* Licenses for results OTHER than data and software -* Export control for projects in the United States -* Communities and resources -* How open data, open software an open results are making science more equitable and impactful +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 a discussion on what subtleties to consider when determining what journal to publish in and how to plan the release of your data, software, in conjunction with your paper! + +Key Terms: Quality checks, computational notebooks, persistent identifies, ORCID, DOI, code of conduct, lab guidelines, data and digital management plans. + +**Prerequisites** + +Before taking this module, it is recommended that you are familiar with and can define what the following tools and concepts mean. +* Zenodo as a data release platform +* GitHub as a code hosting platform +* Persistent identifiers (e.g. DOI and ORCID) +* FAIR/CARE and how they provide guideline principles for creating software and data +* Licensing for data, software, and written content + +**Module 5 Learning Objectives** +* 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 +* List which research objects are created throughout the research cycle +* Describe what constitutes an open result +* Explain what the reproducibility crisis is and how Open Science can help combat it + +Lesson 2: Using Open Results +* List a variety of Open Results sources, with a focus on materials associated with published science research +* Assess the reliability and quality of Open Results sources based on key characteristics +* Describe the responsibilities of the Open Results user, including providing feedback to Open Results developers and giving credit via citations or co-authorship +* Identify the situations in which formal collaboration with Open Results providers is appropriate + +Lesson 3: Making Open Results +* Use authorship and contributor guidelines to make results within a collaboration +* Define what a reproducible result is +* List and describe the components needed in your manuscript to ensure reproducible results + +Lesson 4: Sharing Open Results +* Choose Where to Publish Open Access Including Self-Archiving +* Interpret journal licenses and policies +* Determine when to share data and software with your manuscript \ No newline at end of file