Cambridge Cultural Heritage Data School: April 2024

Module overview

Our modules cover the lifecycle of data-intensive projects related to cultural heritage, including ethical research design, data collection, analysis, visualisation and presentation. Teaching includes lectures, digital tools demonstrations, participatory sessions, workshops, and hands-on activities with leading researchers and practitioners in the field.

You will be able to collect and analyse publicly-available text and image collections from cultural heritage institutions and learn how to use AI both as a tool for research and as an object of inquiry, such as Machine Learning for collections. We will also explore methods for creating digital archives of material objects and the challenges of the archival practice under risky, or critical circumstances.

Modules will cover the following content:

• Ethical research design
• Collecting and working with cultural heritage data at scale
• AI and cultural collections
• Text wrangling for cultural heritage collections
• Digital archives and communities in crisis
• Sentiment Analysis
• Linked Data for Digital Images

*Content may be subject to change

Teaching team

• Dr Anne Alexander (Director of Learning, CDH)
• Dr Estara Arrant (Cambridge University Library)
• Jonathan Blaney (Research Software Engineer, CDH)
• Dr Eleanor Dare (Methods Fellow and Associate Researcher for the Forensic AI project, CDH)
• Professor Lily Díaz-Kommonen (Aalto University School of Arts, Design and Architecture, Helsinki)
• Etienne Posthumus  (Senior Researcher at FIZ Karlsruhe — Leibniz Institute for Information Infrastructure, Information Service Engineering, The Netherlands)
• Dr Giulia Grisot (Teaching Associate, CDH)
• Dr Irving Huerta (Data School Convenor, CDH)
• Mia Ridge (The British Library’s Digital Curator for Western Heritage Collections)

*Teaching team may be subject to change

How to apply, fees & FAQs

Who can apply?

The school welcomes applications from all backgrounds.

You might be working or volunteering in a gallery, library, archive or museum, involved in a community-based cultural heritage project or working with cultural heritage practitioners or institutions as an academic researcher or student. Anyone who works with cultural heritage 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 8-12 April.

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.

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When and where?

The school will be held in person in Cambridge, UK: 8–12 April 2024. No recordings will be available. Sessions will take place between 10am and 5pm daily in the central university buildings on Sidgwick Site:

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.

You can also look for accommodation on the following sites:

• University Rooms
• Airbnb
• Booking.com

Each day will contain a mixture of classes, workshops, and practical sessions in the university premises. A daily vegetarian/vegan lunch will be provided on site, as well as morning and afternoon refreshments, except for Monday where the Data School kicks off after lunch (2.00pm) with afternoon refreshments. There is also a local café and buttery on the Sidgwick Site should you wish to use it.

Participants will also be invited to join us for an informal meal on the evening of 11 April. Please note this will be an additional cost and more information will be provided to registered participants closer to the School.

An online Cultural Heritage 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.

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Fees

• Standard: £750 per person
• Early Bird: £695 per person (until 30 November 2023)
• 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 (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.

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. You can apply for this on the application form.

The deadline for payment is four 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/

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How to apply

Fill in the application form by 21 January 2024. You will hear whether your application was successful or not by 25 January 2024.

The Cultural Heritage 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.

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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 2 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, 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 – Each day will contain a mixture of classes, workshops, and practical sessions in the university premises. A daily vegetarian/vegan lunch will be provided on site, as well as morning and afternoon refreshments, except for Monday where the Data School kicks off after lunch (2.00pm) with afternoon refreshments. There is also a local café and buttery on the Sidgwick Site should you wish to use it.

Participants will also be invited to join us for an informal meal on the evening of 11 April. 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.