The ODISSEI Hub develops a community and supports the usage and usability of the infrastructure through an educational program, community events and as analytic support.
The Hub consists of five closely interrelated tasks:
Community management is aimed at building and maintaining a sustainable ODISSEI collectivity. It is led by the Coordination Team based at EUR who have several responsibilities within ODISSEI to ensure smooth operations across the diverse range of activities. The first subtask will be the general administration of the project including financial and technical reporting, the administration of calls and the monitoring of progress. Being a community infrastructure, it is vital that ODISSEI actively monitors researchers’ needs as input for future directions and communicates what ODISSEI offers. Community Officers will engage in various community development activities through regular face-to-face meetings as well as mailings, the website, social media, and the aforementioned ODISSEI annual conference. Community Officers are the first point of contact for researchers from member organisations turning to ODISSEI. Their job is to help researchers find their way in the infrastructure. Finally, Data Stewards will help researchers create FAIR data and execute ethical practices. Experts from DANS will develop and maintain the user agreement, which focus on data management, data sharing, research ethics, and the principles and practice of FAIR data. ODISSEI Data Stewards will provide support to researchers to implement the user agreement, in collaboration with the experts at DANS.
Project team Community Management: Suze Zijlstra (ODISSEI Coordination Team – Task leader), Eva Heitbrink (ODISSEI Coordination Team).
The ODISSEI Hub’s External Relations Officer will operate an extensive educational programme to facilitate the use of the infrastructure and the uptake of computational and innovative methods in the social sciences. First, there will be an annual ODISSEI Conference where researchers can showcase their projects and engage in broad and open discussion about developments in the infrastructure. This annual event will be hosted by a different member organisation every year and will be coordinated by EUR. Second, there will be a series of workshops aimed at promoting the usage of the infrastructure and the methods and skills needed to do so. These workshops will be coordinated by the EUR but will be hosted by various member organisations. There will be approximately six workshops per year. The program of workshops includes but is not limited to: The ODISSEI Data Facility users Bootcamp; An introduction to Statistics Netherlands microdata access; An introduction to the LISS Panel; Ethics and GDPR in ODISSEI; Machine learning for social science;. Third, there will be regular communications with the educational officers at member organisations to synchronise and coordinate existing educational programs on computational social sciences.
Project team Educational programme: Suze Zijlstra (ODISSEI Coordination Team – Task leader), Eva Heitbrink (ODISSEI Coordination Team).
Social data science team
The Social Data Science Team will bridge the gap between applied social scientists and the data, computing, and analytical infrastructure provided by ODISSEI. They will actively seek out short-term collaborative projects with social scientists across ODISSEI member organisations to uniquely leverage ODISSEI’s infrastructure to answer novel substantive questions and to build expertise in computational social science. These projects will result not only in ‘traditional’ publications, but also in open source reusable code that can be used for teaching purposes or as a starting point for other projects.
Project team Social data science team: Daniel Oberski (Utrecht University – Task leader), Erik-Jan van Kesteren (Utrecht University).
Questions regarding Social data science team? Contact Kasia Karpinska (ODISSEI Coordination Team).
The ODISSEI Hub will design and set-up a benchmark for social sciences that addresses a real world problem that social scientists are working on and that ideally draws from various data sources. Benchmarking is about creating a system of reference, in which various models that address the same task can be compared, in order to be able to analyse the strengths and weaknesses of various approaches and gain new insights. For computer scientists, benchmarks provide a standardized way to validate predictive models, which has proven to be able to detect major breakthroughs, like deep learning. However, social scientists mostly focus on causality and explanation, and so whether social systems can be predicted remains debatable. It could be argued though that causality and explanation, as well as prediction are different sides of the same coin. As such, they can supplement and strengthen each other and provide a more complete and insightful picture of social phenomena.
Project team Benchmarking: Paulina Pankowska (Vrije Universiteit Amsterdam – task leader), Adriënne Mendrik (Eyra), and Daniel Oberski (Utrecht University).
Questions regarding Benchmarking? Contact Suze Zijlstra (ODISSEI Coordination Team).
Grants for computational social science
The ODISSEI Hub will provide grants for computational social science to support the use of the data infrastructure developed across the other three Work streams. Following a successful practice employed at the NLeSC, these grants will provide hours from eScience Research Engineers employed at the NLeSC to collaborate with social scientists to enhance their research, by exploiting digital technology. The grants will be made available via an annual open call which will be assessed by experts in the field of computational social science.
Project team Grants for computational social science: Rena Bakhshi (Netherlands eScience Center – Task leader).
Questions regarding Grants for computational social science? Contact Suze Zijlstra (ODISSEI Coordination Team).