9 Sep 2024 - 13 Sep 2024 9am - 5pm Cambridge, UK

Description

The Social Data School (SDS), taking place in Cambridge between 9-13 September 2024, welcomes applications from individuals working in the media, academia, civil society organisations, trade unions, the public sector and industry. This programme equips participants with the skills and knowledge to conduct data-driven investigations in the public interest.

This year, the SDS will focus on Machine Learning and the investigation of environmental issues, with key sessions delivered in conjunction with partners in the Pulitzer Center, who have been developing cutting edge technologies to carry out impactful investigations.

The School’s intensive in-person teaching programme will be structured around the lifecycle of a project, exploring the methods used to create, visualise, and analyse digital data. Along with leading academic researchers and practitioners, the Data School team have created a teaching and learning experience which incorporates lectures, digital tools demonstrations, workshops, group work and more. Through this varied programme, participants will not only develop their technical skills, but engage with critical questions about data in society.

Previous participants have benefitted from the practical way digital methods are applied to real problems, the critical way in which they are employed, as well as by the rich interactions with teachers and peers during a week of stimulating activities.

We encourage anyone working with social data to apply.


Q&A session

A Q&A information session will take place with the SDS convenors in April, offering further insight into the content of the Data School and the application process.

16 April 2024 2 – 2.45pm

Register here


Further information

Module overview

Modules cover 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.

Participants will gain hands-on experience with data-intensive research methods, being equipped with tools, methods, and ideas to study society in the ever-changing digital environment today.

You may apply with a pre-existing data project, but having one is not a requirement. Taught sessions, workshops, keynotes, and other activities will provide opportunities for developing skills and projects with teachers and peers. Participants will be expected to present their progress and what they learned at the end of the school.

Modules will cover the following content in the context of discussions about Machine Learning, Environmental Data, Satellite Imagery, and Social Media Networks, which will run across the whole curriculum:

  • Methodology for Digital Investigations
  • Machine Learning for Environmental Investigations
  • Basic Automation for Investigations
  • Social Network Analysis
  • Critical Approaches to Data Visualisation

Keynote speakers include:

  • Gustavo Faleiros, Director of Environmental Investigations for the Pulitzer Center
  • Anton Delgado, Pulitzer Center Fellow and multimedia journalist based in Southeast Asia
  • More to be announced

In addition, participants will be able to engage in discussions with speakers, participate in hands-on exercises with teachers available on-site to assist and join in participatory activities with peers.

*Content may be subject to change

Teaching team

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

*Teaching team may be subject to change

How to apply, fees & FAQs

Who can apply?

The Social Data School welcomes applications from all backgrounds.

You might be involved in journalism, marketing, academia, an NGO, activism, a trade union, a civil society organisation, or the public sector. 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 programme 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 in-person during the week of 9-13 September.

We can supply successful applicants to the Data School with a letter to support your 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. Applicants applying for a visa are encouraged to apply as early as possible.


When and where?

The school will be held in person in Cambridge, UK, from 9–13 September 2024. Sessions will take place between 10am and 5pm daily in the central university buildings on the Sidgwick Site.

Successful applicants will need to arrange and pay for their own travel and accommodation for the duration of the school. Cambridge Digital Humanities has block-booked a limited number of rooms at Selwyn College for £88.55 per night. These rooms will be offered to successful applicants on a first come, first served basis, once they have received their acceptance email. More details will be released closer to the date.

You can also look for accommodation on the following sites:

Each day will contain a mixture of classes, workshops, and practical sessions at the university.

Lunch vouchers will be provided for the duration of the school, except for Monday as the Data School commences after lunch at 2pm. On Monday, light afternoon refreshments will be provided after 2pm. For all other days, lunch vouchers can be used at the ARC café, in the Alison Richard Building, which has a wide range of hot food and snacks, including vegetarian, vegan and gluten free options. Additionally, morning and afternoon refreshments will be provided outside the classroom.

Participants will also be invited to join the teaching team for an informal meal on the evening of 12 September in one of the colleges. Please note this will be an additional cost and more information will be provided to registered participants closer to the School.

An online Social Data School also runs once a year, but the dates for the 2024/25 programme have not yet been confirmed. Please check our website or sign up to our mailing list for more details. Please note that the fees for in-person Data Schools are higher than for the online versions.


Fees

  • Standard: £750 per person
  • Early Bird (available until 21 April 2024): £695 per person
  • Concession (limited places): £460 per person

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. 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 Wi-Fi will be available in the university premises.

There is a limited number of concessionary places for the unemployed, unfunded projects, and Global South residents that can demonstrate financial need. In addition, a small number of bursaries (waived fee) are available to those who are not able to afford this training and can demonstrate how attending the school will be beneficial for them or their sector. If you wish to be considered for a bursary, please indicate this on the application form.

The deadline for payment is six weeks before the start of the School.

Please note that in the event of the Data School being cancelled by us, we will refund your registration fee, according to our Terms and Conditions, 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/


How to apply

Fill in the application form by 16 June 2024. You will hear whether your application was successful or not by 24 June 2024.

The Social Data School is application-only with limited places. During your application you should make best use of the free text sections to explain your current experience, and what you would get out of attending the School. If you are applying for a concession or a bursary, you should state in your application why you meet the criteria (see the Fees section above).


Frequently Asked Questions

Fee rates, prices, eligibility

Q – I’m a student / member of staff at the University of Cambridge, can I apply?

A – While University of Cambridge staff and students are welcome to apply, we strongly encourage you to sign up for the CDH Learning Programme sessions which take place throughout the academic year. Most of the content of the Data School is repeated in our regular programme which is open to graduate students and all categories of staff, and for this reason we are likely to prioritise external applicants for Data School places, unless the applicant meets other eligibility criteria (for example, if you are a staff member or student applying in relation to your engagement with a community heritage project, or if you are visiting scholar and you would benefit from an intensive programme).

Course content, level, pre-requisites

Q – What level of technical knowledge do you expect of participants? 

A – We are looking for participants who are comfortable with regularly using computers in their work or study, but we don’t require specialist knowledge or experience of programming. To keep up with the course you’ll need to have some basic knowledge of how to handle files on your computer, how to input data into a spreadsheet (e.g., Microsoft Excel or Google Sheets) and how to install software.

Q – Do I need to know how to code to attend the Data School?

A – No, you don’t. We may be teaching some Python as an option in some modules, but you can follow the course without knowing any code.

Q – Are there any academic requirements for attendance at the Data School?

A – There are no specific academic requirements however the course content is broadly suitable for those with an undergraduate degree or equivalent professional experience. For the Cultural Heritage Data School in particular, we strongly encourage participants to familiarise themselves with with the contents on this free online course from Open University before attending the Data School:  https://www.open.edu/openlearn/history-the-arts/digital-humanities-humanities-research-the-digital-age/content-section-overview?active-tab=content-tab 

Q – Will I get academic credits or an official accreditation from the Data School?

A – The Data Schools are not an accredited course, so no academic credits or official accreditation will be offered. However, we extend a certificate of attendance if you fulfil the attendance requirements.

Q – Are there language proficiency requirements for the Data School? 

A – The Data School will be taught in English and participants will need to be able to follow the live sessions, interact with other participants and read English in order to take part.

Technical requirements, hardware, software

Q – What equipment do I need to take part in the Data School? 

A – To access the Data School live sessions you will need an internet connection and a laptop (Wifi in the university is available for free in-person editions). You can use a mobile phone or tablet to join the live video sessions but you will need to have a laptop on which you have admin privileges in order to install software to work through the course content.

Q – What time commitment is expected in the Data School?

A – Each module in the School consists of two live sessions. The first hour long session will focus on demonstrating methods and techniques, so you should allow around 1-2 hours in addition to work through the material again before the second hour-long live session. The teaching materials provided will also include suggestions for further self-paced work on the topic which you may find beneficial if you want to explore in more depth.

The only exception to this is the Named Entity Recognition with Python module, where there is a more substantial time commitment outside the live sessions. This module offers two different ‘tracks’ for participation: a ‘no-code’ track which will take 1-3 hours outside the live sessions and ‘coding track’ which will take around 3-5 hours outside the live sessions.

Learning sessions

Q – Can I access these teaching materials after the DS?

A – The teaching materials are available for participants’ private study after the Data School. They will be delivered via our own virtual learning environment, Moodle which will be accessible for the rest of the current academic year. However, copies can be downloaded and archived for future use beyond that date. Some teaching content may be available to share publicly and re-use, depending on what licence the individual teacher has decided to use for their materials (there will be resources explaining this in the Moodle and if in doubt please check with the person who created the content – ie the teacher of that specific session).

Q – Can I reuse/repurpose the material for something unrelated to CDH?

A – You need to check the licensing of the specific material in question. If the author has used a Creative Commons licence which allows public sharing and/or adaptation (for example a CC-BY license, or a CC-BY-SA license) then you can. But if it is marked as ‘All rights reserved’ then you can ONLY use for private study unless you get permission from the author. If the material is marked as CC-BY-ND then you may share copies but not adapt or transform it.

Q – Is it possible to have recordings of the sessions?

A – The short answer is no. We encourage all participants to be present in the live sessions, as we don’t have plans to record them in the near future. We are working on developing some on-demand materials, but these will be used in conjugation with the live sessions, not as a substitute.

Q – What happens if I miss one or more sessions?

A – We understand that anything can happen with online teaching and all of us may have unexpected urgent things to solve. If you miss one or two sessions we will ask why and try to understand your situation, but if you miss three sessions with no justifiable reason we will reserve the right to deny access to live teaching and other materials.

In-person editions in Cambridge

Q – How about travel and accommodation?

A – You will need to arrange and pay for your own travel and accommodation for the school. CDH has block-booked a limited number of rooms at Selwyn College, at £88.55 per night. These will be offered to accepted participants on a first come, first serve basis, once they have received their acceptance email. More details will be released closer to the date.

Q – What meals will you be serving?

A – Lunch vouchers will be provided for the duration of the school, except for Monday as the Data School commences after lunch, at 2pm. On Monday, light afternoon refreshments will be provided after 2pm. For all other days, lunch vouchers can be used at the ARC café, in the Alison Richard Building, which has a wide range of hot food and snacks, including vegetarian, vegan and gluten free options. Additionally, morning and afternoon refreshments will be provided outside the classroom.

Participants will also be invited to join us for an informal meal on the evening of 12 September. Please note this will be an additional cost and more information will be provided to registered participants closer to the School.

Q –  Will CDH sponsor a visa application to enter the UK?

A -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 let us know on the application if you will be applying for a visa, and apply early to allow as much time as possible for processing.

Miscellaneous

Q – Are there any possibilities to join CDH research projects in the future?

A – We have a Data School Alumni Network which will provide opportunities to join further workshops and events so please sign up for this opportunity when we share details of how to join. We also encourage participants in the Data School to connect with each other and the CDH research community, but we can’t guarantee that we can find the right partners for every proposed project as this depends on finding CDH associates with matching interests and time to pursue a collaboration. We’re happy to hear suggestions for collaborations and will do our best to suggest possible partners from within our extended network. Please feel free to raise this informally with the teaching team during the school or email the Data School convenor.

 

 

 

Programme

To be announced

Cambridge Digital Humanities

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