Video Lesson: What are Open Scientific and Research Data?

Watch the video lesson on open research data, open metadata, open source, open peer review, open infrastructure, and FAIR research data.

Transcript

	Welcome. In this video lesson, we will learn about open scientific and research data. Upon completion of this video lesson, participants will be able to explain what open scientific data, metadata and open source code are. Define the concept of open peer review and understand its role in scientific communication. Describe the fair principles: findable, accessible, interoperable, reusable for research data. Open scientific data are research data that other researchers can freely download, analyze, combine with other data and use in their own research. Data sharing increases research. Transparency enables the replication of results, encourages new analysis and discoveries, and maximizes the return on investment in research. Open scientific data become truly useful when accompanied by high quality open metadata. What are metadata? Metadata are data about data. They describe the characteristics, context, quality, and conditions of use of the research data itself. Standardized and open metadata formats ensure that the data can be easily found, understood, and cited, which is key for their reuse and integration into broader scientific knowledge. What is open source code? In many scientific disciplines, software and algorithms play a crucial role in data analysis and modeling. Open source code means that the source code of these tools is publicly available under an open license. This allows other researchers to verify the methodology, identify potential errors, adapt the tools to their specific needs, and contribute to their further development, which significantly enhances the transparency and reliability of scientific results. The advantages of open source code in scientific research are: transparency of methodologies, the ability to verify, improve tools, and facilitated collaboration. A good example of an open source repository is GitHub. Universities should encourage the storage of source code and other results of the research process via institutional repositories or other publicly available repositories such as GitHub. What is open peer review? Open peer review is a key open science practice that aims for greater transparency and accountability in the evaluation of scientific papers, thereby contributing to the openness of the entire scientific process. The traditional peer review process is often anonymous, which can lead to bias or less constructive comments. Open peer review introduces greater transparency into this crucial step of scientific communication. There are different models of open peer review from revealing the identity of authors and reviewers to the public release of review reports. The goal is to improve the quality of reviews, increase the accountability of all involved, and provide richer context for published works. Data should be handled according to the FAIR (findable, accessible, interoperable, reusable) principles, which offer a set of guidelines for ensuring the discoverability, accessibility, interoperability, and reusability of data. This includes among other things, access to the documentation necessary to understand the data as well as the protocols, instruments, and software code used to collect and prepare the data for analysis, the creation of a standard metadata description, the assignment of persistent identifiers, and the use of open licenses whenever possible. In cases where open licenses are not possible, data can still be FAIR, provided that they're closed only to the extent necessary. Most often to reduce the risk of harm to research participants, the university and its constituents should provide support to researchers regarding research data management throughout the entire research project. Researchers should store research data in trustworthy, disciplinary, or thematic repositories if available, or in institutional repositories when they're not. In both cases, priority is recommended for repositories that are part of the national infrastructure. The concept of open access, which primary primarily refers to free access to scientific publications, is closely related to research data management. Good data management planning is crucial for ensuring the data are collected, documented, stored, and shared in a way that enables open access in order to encourage and realize the concept of open access, strategic planning and resource allocation to goals and activities that support open science, open education, and open data management are important.