Data is the fundamental currency in clinical and other biomedical research, therefore, taking care of data in a proper way is of great importance for the quality and integrity of current and future research. The current explosion of large and complex datasets holds great promise for improved patient care and for innovation and discovery, for example, in prevention, personalized medicine, novel diagnostics and treatments. However, this expansion of data also brings challenges in data analytics, preservation, reuse and sharing, including the possibility that data may be inadvertently lost or inappropriately used. If data are to be secured, but also reused for maximum benefit, then increasing care must be taken in the planning, creation and long-term storage of data.
Data management and data stewardship make up the research data life cycle and have as their purpose appropriate, efficient, and productive data use and reuse. The outcomes of good data management and data stewardship are high quality data resources that facilitate and simplify the ongoing process of discovery, evaluation, and reuse in downstream studies. Since good data management and data stewardship are necessary for high quality research, planning ahead for good data management and data stewardship is required. Increasingly, science funders, publishers and governmental agencies are beginning to require data management plans for data generated in publicly funded studies.
At the end of this course students are familiar with all the stages of the research data life cycle and know what it requires in every stage to create FAIR research data. This means that research can be reproduced and that data can be reused without involvement of the researcher. All participants will create a data management plan for a research project they work on.
After this part of the course the participants:
- will be able to indicate what information is considered research data and know what the difference is between information and data;
- will be able to define the commonly used terms in data management and data stewardship;
- will be able to describe the research life cycle and the basic options to store, backup, organize and document research data;
- will be able to identify sources of information within and outside the LUMC on data management and data stewardship;
- will be able to interpret common policies regarding information ownership, security and privacy protection at the LUMC;
- will be able to evaluate research (meta)data using the FAIR data principles;
- will be able to name the purpose of a data management plan and list the most important issues to consider in writing different parts of a data management plan;
- will be able to prepare a data management plan based on own research that meets the requirements of funders.
This concerns a 1.5-day course intended for all persons in the LUMC interested in data management and data stewardship and writing data management plans.