Data stewardship: handling data in all phases of research
- Start date:
- 8 November 2017
- 2 days
- Intended Audience:
- Resident physician, Medical specialist, Rsearcher, PhD, Student, Nurse practitioner
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.
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.
The course is organized by Petra van Overveld (Human Genetics) and Ineke van der Veen (Advanced Data Management). This course is part of the Research ICT program.
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 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.
Homework before the start of the course
You follow the e-learning ‘Ethics and data management’ before the start of the course. After this e-learning you will be familiar with terms like privacy, legislation and good data management. The content of this e-learning is assumed to be known before start of the lectures. During the lectures and the practical exercise we will elaborate further on some of the issues touched upon in the e-learning.
This first day will be dedicated to the research data life cycle, how the principles in the research data life cycle translate to FAIR data and what is needed to write a data management plan. Subjects that will be addressed are:
- What is the research data life cycle and why do you need to follow this cycle?
- What are the FAIR principles and how can you apply them to your research?
- How do you create a FAIR data set?
- What is a data management plan, why do you need one and how do you write one?
Homework after course day 1, before course day 2
You will write a data management plan for your own research project. For this you will use the template of Leiden University.
Course day 2
You will discuss your ‘data management plan’ assignment in small groups. Students give each other feedback on the assignment and a summary is presented in the closing session.
The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3, Article number: 160018 (2016)
Het beheren van onderzoeksdata. Informatiewetenschap 77, IVB 475 (2016) (in Dutch)
Course ‘Essentials for data support’ (Dutch and English version available)
Handbook for Adequate Natural Data Stewardship, part of NFU program Data4lifesciences
VSNU Landelijk Coördinatiepunt Research Data Management (LCRDM)
Bioinformatics courses on subjects as Git, Linux, scripting and Python
Day 1: Wednesday 8 november 2017
08:30 Welcome and registration
09.00 Introduction (Ineke van der Veen)
09.15 Lectures data management (Ineke van der Veen)
11.00 Lectures data stewardship (Petra van Overveld)
12.30 Lunch break
13.30 FAIR data and data management plan exercise (Petra van Overveld)
14.30 Exercise: analysis of a grant application to be able to write a data management plan
17.00 End of day 1
Write a data management plan for your own research project.
Day 2: Monday 20 November 2017
08:30 Welcome and registration
09.00 Group and plenary discussions homework DMP
12.00 End of day 2 (end of course)
Day 1: May 15, 2018 - H1-14 (morning, building 1) and V5-45 (afternoon, building 3)
Day 2: May 29, 2018 - V7-39
LUMCHippocratespad 21, 2333 ZD Leiden
Deelname is kosteloos
Participation is for free