Introduction to Research Data Management for Social Scientists
Instructors: Dr. Alexia Katsanidou, Laurence Horton, Dr. Sergiu Gherghina
March 20 (2pm) – March 22 (1pm), 2013
Target groups
Social science researchers working with qualitative or quantitative data (principal Investigators, researchers who are parts of project teams, individual researchers, and PhD students)
Contents
Are any of these questions relevant to you?
- Ever lost research data?
- Do you know if your research data is securely stored and backed-up?
- Had troubles with coding and documentation of data?
- Are you confident you would be able to understand your data sometime in the future?
- Considered sharing your research data to increase the visibility of your work?
- Thought, why would anyone be interested in my research data?
- What to do with your research data after a project?
- Encountered problems working in a collaborative setting (teams, co-authors etc)?
- Need arguments to persuade your institution about the necessity of research data management?
If so, this workshop will be useful. Designed to address the needs of social science researchers, it discusses ways to maintain the security and integrity of research data.
Good research data management practice minimizes the risk of data loss, ensures research integrity and facilitates replication; it enhances data security, research efficiency and reliability, and over the long-term, saves time and resources. Moreover, data management planning and data re-use is increasingly a requirement of funding organizations.
Workshop sessions include a basic conception of data management, advice on writing a data management plan, licensing data for reuse or to reuse, consent and ethics for data reuse, file formats, documentation and metadata, data storage, back-up and security, data management in collaborative research, and archiving your data.
The workshop promotes an interactive hands-on approach to looking after your research data and encourages discussion amongst participants on sharing problems and experiences.
Learning objectives
- Gain a basic understanding of research data management in social science research (e.g. general rules, tools, role, benefits)
- Learn how to write and implement a research data management plan
- Illustrate roles and responsibilities for research staff regarding research data management within the larger data lifecycle
- Gain awareness of data re-use in the social sciences and ways to enhance your own research.
Requirements
Participants are expected to be advanced students or researchers of any level in the social sciences. A good command of English is required.
Number of Participants: 20