WP4 - NA3 - Training


This WP will establish a joint training and education resource on big social data in the European research area, promoting the education of the next generation of data science researchers, with emphasis on social analytics. Moreover, it will connect with research communities yet underrepresented in social big data resources and will engage researchers with new research methodologies for social big data and will support the SoBigData++ research infrastructure usage through user training.


T4.1 Online Training Modules
Task leader: KCL.
In this task, we will deliver a range of open-source training modules, arising from training events and the expertise of each consortium partner. These will be integrated into the teaching environments available on the platform as an evolution of the online e-Learning Area developed in the first phase. Currently, the e-Learning Area is a repository of
courses and materials organized by topics and pre-requisites. The next step is to create online courses as already done for the Fair Online Course: First Aid for Responsible Data Scientists (See http://fair.SoBigData.eu/moodle/). These modules will at first integrate the existing training materials and promote and sustain them by making them available
as open educational resources. The final result will be the creation of training modules which will adapt to stakeholder requirements in collaboration with the developments in WP2, WP5, WP7 and WP10.

T4.2 Summer schools
Task leader: SNS.
Participants: USFD, LUH, UNIROMA1
We plan to organize at least 4 summer schools (one each year) that are aimed at training the new generation of Data Scientist and are inclusive to groups currently under-represented in data science. These summer schools will introduce participants to techniques and methodologies for analysing big data, in order to provide them with a solid background in the computational and mathematical theories behind algorithmic tools for empowering their future research. The summer schools will be strongly interdisciplinary and include experts across arts and sciences. Participants will be selected on a competitive basis and will be encouraged to complete their own mini-projects during the summer school.

T4.3 Datathons
Task leader: CNRS
Participants: CNR, IMT, KTH, ETHZ
We will organize a series of Datathon (minimum 4) whose aim is to bring together young and bright minds in smaller dedicated groups, providing complementary theoretical and practical skills to visualise and analyse social big data questions addressing important societal problems. All the Datathon will be supported by the Operational Ethics and
Law Board (see task 2.1) in order to include Ethical and Law aspects in the Datathon activities.

T4.4 Cultivating diversity in data science through training
Task leader: KCL
Participants: ALL
Computer Science and Data Science currently fail to adequately embody staff equality and diversity issues. For instance, not only females but also minority groups, etc are still woefully underrepresented in data science. The aim is to leverage existing networks (i.e. the Women Network within the European Association on Data Mining and Machine Learning,
AI club for Gender Minority), in order to raise awareness regarding the opportunities provided by employment in the field of data science. SoBigData++ will support specific events and provide travel grants for young female and minority group researchers.