The Faculty of Social Sciences Data Lab welcomes all faculty researchers with an interest in data science for consultations. We offered tailored assistance depending on the level of experience and specific needs of the project.
Please feel free to contact the Data Stewards to book a consultation or drop by the Data Lab HQ in 01.1.10.
Types of consultations
The Data Lab offers sparring sessions to provide researchers with inspiration for how to incorporate data science into their research projects. In our experience, there is a wealth of untapped potential for making novel scientific contributions by using data science methods and digital data sources, and we can help identify relevant literature, approaches or collaborators. Sparring sessions can be beneficial for researchers who are in the early stages of grant applications, as well as for adding value to on-going research projects.
Support for specific problems
The Data Lab offers guidance for researchers who have specific data science needs. For example, the Data Lab can help with experimental design, ensuring GDPR compliance when analyzing sensitive data, overcoming coding roadblocks in R and Python, setting up webscrapers for social media platforms, as well as interpreting results. We can also discuss or give feedback on sections of a research paper.
Collaborations with research projects
For research projects that require a deeper level of assistance, the Data Lab can also act as a collaborator and co-author. Collaborations are relevant if there is mutual interest between the research project and Data Lab staff and more hands-on need for support. Here, the Data Stewards can help with tasks such design of algorithms, development of hypotheses, carrying out analyses, and writing relevant parts of a research paper. The Data Lab follows the UCPH code of co-authorship as well as the Vancouver critera for authors and contributions.
The Data Lab regularly engages with a strong network of researchers engaged with data science. We can help identify potential for interdisciplinary collaborations across faculty departments, or between senior and junior staff, for example. Please contact the Data Lab if you are interested in matchmaking or networking.