# Data package and Data assets

The data package https://youtu.be/fsrsQ71quCk

Understanding how data is structured within a research project is crucial for effective data management. Each individual piece of data or documentation is known as a Data Asset, which may evolve as the research progresses. These assets collectively form a Data Package, the final compilation of all collected, analyzed, and processed data, along with the necessary contextual information to ensure its future usability.

In this chapter, we will explore the different types of data assets, how they change throughout the research process, and how to effectively organize them. By properly managing your data assets, you can enhance the quality, reproducibility, and long-term impact of your research.

Research data is often visualized as numerical data; however, research data is full of variety and can differ immensely. It includes all physical and digital information collected, observed, generated, or created for analysis. Additionally, administrative documents such as key files, informed consent forms, and interview guides are essential components of research data that contribute to the FAIRness of a project.

FAIRness refers to your data being Findable, Accessible, Interoperable, and Reusable. You will often see this term referred to when discussing research data. The goal of FAIR data is to ensure transparency, longevity, and availability of research data. Applying these four principles to your research data increases the usability of your data and ensures it remains valuable now and into the future. Good data management contributes to the FAIRness of your data. For more information on what FAIR means to your research check out this resource.