Internship type: Communication & case study development
Institution(s): TU Delft
Duration: 3 months (minimal)
Hours/week: 20 (minimal)
Preferred start date: February / March, September 2022
Supervisor name & contact details: Yan Wang (Data Steward Coordinator, TU Delft) firstname.lastname@example.org
The added value of data stewardship has been widely praised and promoted in academia. There are several reports highlighting the progress and achievements on this topic, for instance the national coordination of data steward education in Denmark, professionalising data stewardship in the Netherlands, and the yearly report of TU Delft data stewards achievements (2018, 2019, 2020). There are also inspiring stories demonstrating exemplary cases of making data FAIR and its impact.
When evaluating the impact of data stewardship, people tend to look for quantitative measurements, such as the number of resolved research data management (RDM) requests; number of students trained; number of published datasets; dataset citations and downloads; and more. Whilst these are key metrics of good RDM and FAIR data practice, RDM activities and challenges encountered in research projects are much more diverse and complex. The impact and usefulness of data stewardship is not limited to the aforementioned topics, but can be qualitatively measured by evaluating various issues encountered by researchers and the RDM support requests frequently solved by data stewards throughout the entire research process. Unfortunately, there has not been much investigation into these qualitative insights and the added value of the data stewardship within research institutions.
The internship project serves as a ‘fact check’ that aims to collect qualitative evidence to verify the impact of data stewardship. The programme of work will explore the different types of RDM challenges that arise during the research lifecycle and the benefits of data stewardship. This proposed ‘fact-check’ will also serve as a review and reflection of the data stewardship regarding its scope (e.g. range of data stewardship roles and responsibilities), approach (e.g. means and tools that data stewards used to tackle issues), capacity allocation (e.g. resources required to fulfil the demands from researchers) and service gap (e.g. new issues that no existing solution available from the standard services at the university). In addition to quantitative measures, such qualitative insights could help to design a framework for evaluating the impact of data stewardship.
The intern will liaise with data stewards and researchers across all TU Delft faculties, and develop case studies that:
- Showcase examples of good RDM practices among researchers from various disciplines.
- Identify the role of data stewards in promoting open science and FAIR data practices.
- Categorise different types of support provided by data stewards and evaluate their perceived added value by researchers.
- Provide essential inputs for the development of the evaluation framework of data stewardship
Case studies will be published as dedicated articles on the 4TU.ResearchData website and published within our social media channels (Slack, Twitter and LinkedIn) and newsletter. The intern will have an opportunity to present their work at meetings, conferences and as a peer-reviewed publication.
- Good communication and writing skills are essential, and experience of conducting interviews is desirable.
- A goal-oriented mindset is necessary. The candidate is expected to be pragmatic and cooperative while thinking independently.
- Research experience or familiarity with the research lifecycle in science/engineering/design/social science disciplines is desirable.
Benefits for interns
The intern will:
- Obtain holistic insights into data stewardship activities from an institutional perspective.
- Connect with researchers and data stewards from different disciplines and gain insights into challenges/opportunities of disciplinary data management.
- Learn and practice case study development and service analysis skills which are fundamental for both research and practice.
How to apply
Please send your CV and cover letter (in English, 2 page max for each) to email@example.com with the subject line ‘4TU.ResearchData Internship Programme’. In your cover letter please include your motivation for applying for this project. Please briefly explain what interests you the most in this project, and feel free to mention anything particular that you would like to explore/learn from this project. All applications will be subject to a review process.
For questions about the project activities, please contact the supervisor, Yan Wang (firstname.lastname@example.org). For more information about how to apply, contact the community manager, Connie Clare (email@example.com).