Foundational School in Research Data Science
22 October – 2 November, 2018
University of Rwanda, Kigali, Rwanda
The goal of this workshop was to train researchers in Research Data Science (RDS). RDS refers to the principles and practice of Open Science and research data management and curation, the use of a range of data platforms and infrastructures, large scale analysis, statistics, visualization and modelling techniques, software development and data annotation. These are important tools for extracting useful information from data and these tools are useful in every research area. A 10-day workshop, organized by CODATA, ICTP and EAIFR, was conducted at the University of Rwanda, Kigali to introduce participants to the skills of RDS.
Topics covered
- Open Science
- Unix Shell
- Version Control
- Introduction to R
- Research Data Management
- Databases and SQL
- Data Visualization
- Machine Learning and Artificial Neural Networks
- Research Computational Infrastructure
Directors
Robert Quick
UITS Research Technologies, Indiana University
rquick (at) iu.edu
Louise Bezuidenhout
Institute for Science, Innovation and Society, University of Oxford
louise.bezuidenhout [at] insis.ox.ac.uk
Participation Information
This workshop was open to researchers in every field. Science graduates (masters and doctoral levels) working in data intensive fields would find it particularly useful. Women candidates are strongly encouraged to apply. Selection of participants is based on their technical background and also the urgency of their needs to apply the tools of RDS. Applications for participation for the workshop can be found at: https://e-applications.ictp.it/applicant/login/9006. For further information contact: info@eaifr.org or workshop20181022@eaifr.org
Information for Applicants
There is no registration fee for these events. Some support for travel and accommodation is available and its allocation is determined during the selection process. Much of this funding is intended for participants from lower and middle income countries. Potential participants have the opportunity to indicate they need support in the application. Self-funded participants are welcome. All applicants are strongly encouraged to look for alternative ‘third-party’ sources of funding to support their participation.
The CODATA-RDA Research Data Science Summer School is open to participants in any research discipline. The data skills taught are also useful for (data) librarians and other research support staff, such as those who envisage a career as data steward or data analysts. Furthermore, people who are more advanced in their careers who would like to improve their data skills as a form of continuing professional development are also eligible.
Participants are selected on merit from a very competitive field. Applicants are urged therefore to ensure they pay careful and full attention to the requirements of the application process.
Selected participants for the Research Data Science Summer School will have a baseline of data skills and these will have been tested by an online form. Applicants to the Advanced Workshops should demonstrate their capacity and skills to engage with these themes on a more advanced level.
Applicants to either event should pay particular attention to their personal statement and communicate persuasively their reasons for wishing to attend the Summer School and/or Advanced Workshops: how do they intend to use these skills and experiences, how will participation in the Summer School and/or Advanced Workshops benefit their research or the institution in which they work? Finally, candidates should take pains to ensure that their application is well supported by references from their past or present tutors or line managers. This is particularly important so that the directors and organisers of these events have confidence in the candidate and that the skills learnt will have the maximum benefit and impact.
