26 Jun 2023 - 30 Jun 2023 9am - 5pm Cambridge, UK


Social Data School 2023 in Cambridge (26-30 June)

We are delighted to welcome students again to our in-person 2023 Social Data School (SDS), organised by Cambridge Digital Humanities at the University of Cambridge. After running the SDS completely online for a couple of years during the covid pandemic, we are glad to receive you for a whole week in Cambridge.

You will learn new methods and tools for data-intensive public interest investigations and academic research, from leading academics and practitioners in the field. You will also have the possibility to use the Library and visit relevant places at the University of Cambridge.

We aim to bring together participants from journalism, academia, publicity, and civil society to explore the methods used to create, visualise and analyse digital data and its dissemination in society.

At the SDS you will learn by doing during in-person sessions and other activities. The school is intensive, but extensive online resources will be available to students to help them follow up on what they learned in the taught sessions during and after the Data School. We encourage anyone working with social data to apply!


Applications closed 13 June 2023.



The SDS is an application only intensive teaching programme structured around the life-cycle of a digital research project, covering principles of research design, data collection, cleaning and preparation, methods of analysis and visualisation, and data management and preservation practices.

Students will gain hands-on experience of data-intensive research methods from leading researchers and practitioners, as well as critically addressing theoretical assumptions about these practices. They will be equipped with tools, methods, and ideas to study the social in the ever-changing digital environment today.

As part of the application process, participants will propose a project to work on during the five days of the Data School. You may apply with a pre-existing project or propose a new project which you will develop during the course of the Data School. In either case, projects should show great potential to have an impact in the public interest. Taught sessions, workshops, keynotes, and other activities will provide opportunities for these projects to be developed with teachers and peers. Participants will be expected to present their progress and what they learned at the end of the school. See more details about projects and their relation to applications in the ‘How to apply’ section below.

Modules will cover the following content in the context of discussions about Machine Learning, Social Media and Decoloniality which will run across the whole curriculum: 

  • Methodology for Digital Investigations
  • Introduction to Computer Vision and Machine Learning for Investigations
  • Basic Automations for Investigations 
  • Geolocation and Open Source Investigations
  • Social Network Analysis 
  • Critical Approaches to Data Visualisation 

We will have three greatly stimulating keynotes from practitioners and/or academics working around those topics:

  • Jacopo Ottaviani, from Code4Africa, on the work his organisation has done with communities, local journalists, and NGOs in Africa.
  • Edgar Gomez Cruz, from the University of Texas at Austin, on ‘Decentering Knowledge’.
  • Sofija Stefanovic, PhD student at the Centre for Doctoral Training in Artificial Intelligence for Environmental Risk.

In addition, students will be able to use the Cambridge University Library, have hands-on exercises with teachers available on-site to help, have participatory activities with peers, and go out for dinner in Cambridge.

You can view the full programme and module descriptions here: Social Data School Programme

Note: content and timings may be subject to change.

Who can apply?

The school welcomes applications from all backgrounds.

You might be in journalism, marketing, academia, an NGO, activism, a trade union, a civil society organisation, civil service. Anyone who works with social data is welcome to apply.

No previous experience of coding is required and there are no specific academic requirements, however the course content is broadly suitable for those with an undergraduate degree or equivalent professional experience. The School is taught in English. 

We are committed to facilitate participation by women, black and minority ethnic candidates as they have historically been under-represented in the technology and data science sector. We also welcome applications from outside the UK, assuming they can attend during the week of 26-30 June. 

We can supply successful applicants to the Data School with a letter to support the appropriate visa application, however please note that applicants are responsible for their own visa costs. Please indicate on the application if you will be applying for a visa and we encourage you to apply as early as possible.

When and Where

The school will be held in person in Cambridge, UK: 26–30 June 2023. Sessions will take place between 10am and 5pm daily in the central University buildings on Sidgwick Site:

You will need to book and pay for your own travel and accommodation for the school. You can look for accommodation on the following sites:

Participants will also be invited to join us for an informal meal at a local restaurant on the evening of 29 June. Please note this will be an additional cost and more information will be provided to registered participants closer to the School.

Teaching Team

Teaching will be by University of Cambridge staff and industry professionals and will include:

  • Dr Hugo Leal (Teaching Associate at CDH’s Mphil in Digital Humanities and Research Associate at the Minderoo Centre for Technology and Democracy)
  • Members of Amnesty International’s Digital Verification Corps (Centre of Governance and Human Rights at Cambridge University)
  • Dr Anne Alexander (Director of Learning, CDH)
  • Dr Irving Huerta (Convenor of the Cambridge Data Schools, CDH)


  • £695 per person (standard)
  • Please see below for details of concessionary and bursary places.

This fee covers around 23 hours of sessions, access to online teaching resources, space for discussions with top practitioners and peers, troubleshooting sessions, and catering (refreshments and one lunch sandwich buffet per day). Participants need to bring a laptop with them to the Data School on which they have the right to install software. We will not provide any equipment but WIFI will be available in the university premises.

Cambridge Digital Humanities is committed to democratising access to digital methods and tools, and is offering subsidised participation fees to encourage applications from those who do not normally have access to this type of training. There are limited concessionary places (five) for the unemployed, community or unfunded project researchers. We will select applications for concessionary places and bursaries based on a combination of factors including expanding the diversity of the Data School cohort and evidence of the benefits which attendance will bring to the individual applicant and/or their organisations or community.

In addition, a small number of full bursaries (two) are available to those who can demonstrate financial need. You can apply for concessionary and bursary places on the application form, but we may not be able to give concessions to everyone who applies.

Please note that in the event of the Data School being cancelled by us, we will refund your registration fee, but we will not be liable for any other costs you have incurred – travel, accommodation, visas etc. We suggest taking out insurance that will cover you in the event of a cancellation. Please see our Terms and Conditions for details of refund policies for Data School tuition fees: https://www.cdh.cam.ac.uk/dataschools/cambridge-data-schools-terms-and-conditions/


Please download the programme here.

Social Data School Programme

Cambridge Digital Humanities

Tel: +44 1223 766886
Email enquiries@crassh.cam.ac.uk