 Welcome to Using Data Ethically. In this video, you will define data ethics and data misconduct, address data use in personal and professional contexts, explore data misconduct in its multiple forms. As a student and researcher, you will be challenged to manage and utilize data in a variety of situations. It is important to know what data is, how data is used, and what constitutes data misconduct. These three subtopics all fall into the realm of using data ethically. Being aware of how you use data and what data is collected about you will make you a more successful student and researcher. Data ethics can be defined as a branch of ethics that studies and evaluates moral concerns related to data. Data includes but is not limited to any kind of information created. Examples can include algorithms, scripts, and information collected as part of the research process, which might include references, results, samples, and what we call raw data, which is the output of some process. As students and researchers, these types of data are everywhere and you must utilize the best practices of working with the data. Ways that you might work with data can include generating, recording, curating, processing, disseminating, sharing, and using data. Starting your research can be exciting and daunting. Planning ahead and thinking about how and what kind of data you will be collecting is very important. You might start by asking questions like, as a researcher, what do I want to know? How will I collect that information? How will I store it? Do I need consent? What are the long-term implications of my data use? You should also keep in mind that data ethics is important even outside of your research agenda. You create and work with data as a researcher, but you also create and work with data in your daily life too. While you might not be accused of misconduct in your personal life, your interactions with data can still leave you open to many potential issues or threats. You should consider what kind of data you are creating, who else has access to it, and how it is stored over time. Taken together, how and in what ways you treat data is important in all aspects of your life. In thinking about how data is used in your personal life, you might ask yourself questions like, what types of data do I share in each of my social media platforms? Does my use differ from platform to platform? Did I give consent for the sharing of data on each platform? What are the long-term implications of shared personal information? Many of you are probably familiar with the term plagiarism. However, when you think about data and how we just previously defined data, you must also be aware and be careful of how you collect and disseminate data as to not fall into the realm of data ethics misconduct. Misconduct is a lot more than just plagiarism. It also includes fabrication and falsification, which are serious matters. The Department of Health and Human Services defines research misconduct as fabrication, falsification, or plagiarism in proposing, performing, or reviewing research results. Let's take a closer look at the parts that make up misconduct. Fabrication is the making up of results and recording or reporting them. Falsification is the manipulation of research materials, equipment, or processes, or changing or emitting results so research is not accurately represented. Plagiarism is the appropriation of another's ideas, processes, results, or words without giving proper credit. While these definitions originate from the Department of Health and Human Services, they are relevant to all fields of study. We've defined data ethics and what data ethics misconduct is, but you need to be aware of how and what information is being collected about you daily. Let's talk through some real-world examples of ethical data use. In Scenario 1, let's think about biological sample data. Think about genetic screening here, where a third party might be taking your DNA sample to run tests. How does it make you feel to think about your DNA results being shared with pharmaceutical companies? If the answer to this question doesn't feel good to you, you might consider avoiding opportunities to send your DNA off for testing. In Scenario 2, let's think about social media. Think about the social media accounts you might have. Now think about the pictures or posts you make on a daily basis. How will you feel in 10 or 20 years if something you post is still around? If that doesn't feel good to you, be mindful before you post. You might also think about questions like, do you have rules about what you post on different platforms? Do you go back and review or even delete your past content? In this video, we've learned about data ethics and data misconduct. Think about how they might affect your personal and professional life and examine real-world examples of data use. This will help you start thinking about how you collect, share, and use data. Some next steps in exploring data ethics further can include participating in trainings at your university, including IRB, or Institutional Review Board Training, or Human Subjects Training. These trainings can help you better understand ethical behavior for data, avoid misconduct, and potentially even gain accreditation for current or future research. You might also talk with a mentor in your specific discipline to better understand ethical norms in your field.