Data Stewardship

Can be taken as a single course.

Data Stewardship provides a comprehensive introduction to responsible research data management and to the professional role of the data steward.

The course covers the whole research data life cycle, from searching for relevant existing data, through organising and documenting datasets, to publishing data in suitable repositories.

Combining theory, hands-on exercises and a micro-internship, it is made up of three modules:

• Module 1: a self-paced online module covering theory and best practice in research data management.
• Module 2: 3 days of in-person workshops where participants apply Module 1 content through collaborative activities.
• Module 3: a 2-day micro-internship with a local employer that gives participants experience of tasks typical for a professional data steward.

On completion you will have the knowledge and practical skills to manage research data responsibly and effectively, both for your own project and more broadly. You will also have gained workplace experience in data management, highly valued by both academic and non-academic employers.

This course is primarily designed for PhD candidates, from any scientific discipline and regardless of the type of data they work with.
The course is open to PhD candidates enrolled at UiT and to PhD candidates from other European universities. Applicants who are not registered at UiT must upload an official document from their home institution confirming their PhD ­registration.
The course corresponds to 3 ECTS. PhD candidates at UiT who intend these 3 ECTS to count towards the 30 ECTS that make up the compulsory education part of their PhD should discuss this with their supervisor.
Postdoctoral research fellows may apply and will be admitted only if places remain available.
All participants must hold a Master’s degree (or equivalent).
Maximum number of participants: 20
If fewer than 10 applicants apply, the course co-ordinator will decide whether the course will run.
If applications exceed capacity, places will be allocated in the following order of priority:

• PhD candidates admitted to a PhD programme at UiT (priority given to those most recently admitted)
• PhD candidates from other universities
• Postdoctoral research fellows

All PhD candidates at UiT apply for admission by registering for class in Studentweb by February 1 for the spring semester.
Other participants apply for admission in Søknadsweb.

Application code 9301.

Knowledge

• Describe the research data life cycle and identify good research data management (RDM) practices for each key stage (finding and reusing, storing, organising, documenting, and archiving research data).
• Explain and reflect on how responsible RDM (including the FAIR principles) supports research quality, transparency, reproducibility and reuse.
• Explain key legal and ethical considerations that affect RDM (e.g. ownership, licensing, sensitive data, CARE principles) and how these constrain sharing and reuse decisions.
• Justify the purpose, typical structure and functions of Data Management Plans (DMPs).
• Describe and compare the role and responsibilities of data stewards in academic and non-academic settings.

Skills

• Select and use suitable tools to write a DMP for a research project.
• Search for and reuse published datasets in line with good practice.
• Implement good practice for storing, organising and documenting research data during the active phase of a project.
• Prepare and deposit a dataset in a suitable reputable repository.
• Carry out and document typical data stewardship tasks during a workplace placement.

General Competence

• Critically assess RDM practices in the light of relevant policies, standards and principles.
• Communicate RDM requirements and benefits, and advocate for good RDM practice.
• Reflect on the value and relevance of RDM knowledge and workplace experience for post-PhD career pathways within and/or beyond academia.

Recommended prerequisites

GEN-8001 Take Control of your PhD Journey: From (p)reflection to publishing, SVH-8005 Research Ethics

• Self-paced online course (Module 1), including reflection tasks and test-yourself quizzes.

• Teacher-led workshops, with a focus on group activities. Pre-assignments given for each session (Module 2).

• Individual or group work carried out during a micro-internship with a local employer (Module 3)

Language of instruction and examination

Schedule

More info about the coursework requirements

• Completion of the Module 1 multiple-choice exam

• Completion of the Module 2 final home assignment

• 80 % attendance in Module 2

Re-sit examination