I hope this email finds you and your loved ones well in these special times.
I am pleased to send you today the program of the University of Geneva’s Data Science Competence Center (CCSD) for the coming year.
First of all, I would like to thank all of you! This program comes as a result of the personal contributions of each of you and the time that you did not hesitate to give to the project, whether it was during the interviews that we conducted together or during our April plenary meeting.
Validated by the Rectorate, this program constitutes a solid foundation for launching the Center and allowing us to think together about its future development, so that its services and initiatives stay as close as possible to the needs of our university community and those of the City.
As such, I invite you to read the following, and do not hesitate to come back to me with your opinions, comments and concrete ideas for participating in the projects.
Other messages will follow, specifying more clearly each of the activities planned for the next semester.
I look forward to meeting you in September and I wish you, dear colleagues, a lovely day and a great summer.
Guive Khan-Mohammad, PhD
CCSD Program Manager
Operational definition of the term "data science"
We interpret the term “data science” as the science of learning from data.
As such, data science is based on several academic disciplines, including data management and engineering, statistics, algorithms, machine learning, programming, optimization, visualization, law and ethics, as well as on many skills, such as elicitation and problem formulation, collaboration and communication.
At the heart of data science is a process of continuous improvement, aimed at solving complex, unstructured and data-rich problems, by applying specific methods, techniques and practices.
Data science thus provides a whole scientific learning process from data to the humanities and social sciences, economics, medicine, environmental sciences, as well as a multitude of other disciplines, and provides decision support, helping to understand and act on complex real world problems.
Vision of the Centre
By leveraging our strengths of interdisciplinarity and critical transversal approach, we apply data science to understand complex problems, contributing to consolidate the status of scientific excellence of our university in the era of big data and to develop skills, initiatives and concrete solutions for the public good.
Mission of the Centre
The Data Science Competence Center (CCSD) of the University of Geneva's mission is to federate the skills and initiatives of UNIGE in data science, with the aim, through transversality, of promoting the emergence of innovative research and of supporting a critical and informed transformation of scientific culture in the era of big data.
Objectives and 2020-21 projects
Objective 1: Promoting interdisciplinary and critical research in data science
- UNIGE’s Data Science Days
The UNIGE's Data Science Days are a two-day scientific symposium which will take place in June 2021. For the first edition, the theme will be “Epidemics and (Big) Data: contributions and challenges of data science in the study of diffusion phenomena ”.
- Seed funding for project development
In preparation for the UNIGE’s Data Science Days, an interdisciplinary call for projects will be launched in September 2020.
- Common lexicon
In order to define a common language among the disciplines, a working group will be set up to develop an interdisciplinary lexicon in data science.
Objective 2: Facilitating the transformation of UNIGE researchers’ scientific practices through the development of data science services
- Data Science Clinics
On a bimonthly basis, an interdisciplinary meeting will be organized to allow researchers - who have requested it - to share with data science experts certain concrete problems they encounter in the treatment of their research data. To be dealt with during these sessions, these questions must have the potential to give rise to the development of mutually beneficial collaborations between these researchers (publications or joint research projects).
- Data Science Seminars
Three seminars per year will be organized around themes linked to data processing. These themes were highlighted by the researchers gathered during the April plenary session. In 2020-21, Data Science Seminars will address the following themes "Data quality and bias", "International collaboration and sharing of data", and "Data status and protection".
- DatAid Network
In order to promote permanent exchange between CCSD members, the network of data science experts will remain accessible at all times through the creation of a platform allowing members to interact on specific questions.
Objective 3: Supporting the development of the transversal training offer in data science at the UNIGE
- Summer School
The Center will support the establishment of a Summer School in data science in the summer of 2021.
- Mapping of training resources
In order to identify the learning possibilities in data science offered by our institution, a mapping will be carried out, which will cover both the faculty offers, but also the training provided by certain departments and divisions (DIS, DISTIC, etc.).
- Skills repository and self-learning platform
A working group will be set up to develop a skills repository related to data science, as well as to identify the internal training offers at UNIGE (identified by the mapping) and the complementary external offers, by which these skills could be reinforced.
Objective 4: Improving the visibility and accessibility of UNIGE's expertise in data science
- Skills directory
In order to make visible and accessible the expertise of UNIGE collaborators in data science outside, but also inside our institution, an interactive skills directory will be integrated into the Centre's website.
In order to reach a wider audience, the Center will publish podcasts presenting the research of its members on a monthly basis.
- General public conferences
Based on possible proposals from members of the Center and depending on the resources available, conferences for the general public can be organized on specific research themes.