This new cross-disciplinary programme will create expert data scientists taught through the exciting lens of cultural heritage.
- Developed and delivered by leading academics at the , in collaboration with industry and
- Innovation and practice-driven MSc, giving you the opportunity to learn data science through real applied challenges that require the use of advanced skills and solutions.
- Alongside the latest data science skills, you will develop valuable cross-cutting and transferrable skills, including communication and interdisciplinary collaboration, and will develop your critical thinking.
- You will have the opportunity to work on exciting real case studies provided by leading national and international heritage organisations.
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The role of digital technologies and data in all aspects of contemporary society is immediate, relevant and complex, and the multidisciplinary field of cultural heritage is no exception. From historic buildings, sites, landscapes, museums and collections, the world of heritage provides an exciting setting in which to learn and apply skills of data science.
The opportunities of using data science in diverse contexts are vast. Employers from increasingly diverse sectors now require people with skills in a range of state of the art methods and technologies to understand, manage and exploit data.
This programme pioneers a new way of teaching data science through application in a cross-disciplinary context. As a student on the Data Science for Cultural Heritage (DSCH) MSc, you will develop advanced data science skills, such as crowd sourced data science, machine learning or imaging data analysis. You will explore the complexities of acquisition, analysis and exploitation of the variety of data that is generated and used in heritage contexts, including data generated through analysis and measurement, imaging and surveying, citizen science, and digitally born data.
- Learning outcomes
Cultural Heritage presents complex challenges that bring together science, engineering and technology with social science and humanities. You will develop and learn how to apply your data skills and knowledge within the cultural heritage context, giving you a balance of academic skills, active learning experience, business capabilities and cross-disciplinary skills that are in high demand in many industries and sectors.
You will learn about:
- The data pipeline from acquisition, through exploitation, to storage and reuse
- Data analysis, visualisation and management skills
- Practical skills of data acquisition and treatment in the context of cultural heritage, such as machine learning, Heritage BIM, crowd-sourced data, AI or imaging technologies
- Legal concepts related to data management and ethics
- Data archives and repositories in the context of cultural heritage, their value and conservation
- Working with stakeholders (including the public) to acquire, contextualise and evaluate data
Furthermore, this programme will develop your critical thinking skills through the exploration of the concept of cultural heritage and the motives and needs for its preservation, as well as the importance of heritage values, integrity and authenticity.
- Programme structure
Cultural heritage data offers a unique and complex perspective through the data pipeline of: Acquisition > Analysis > Visualization > Storage > Repurposing > Access > Curation
You will address qualitative and quantitative data generated about culture and heritage and data as heritage. Data about culture and heritage covers data generated through documentation, measurement, imaging and surveying, analysis, citizen science, as well as digitally born data, e.g. through social media and other digital social interaction, which is increasingly collected by cultural and heritage institutions. Data as heritage comprises digitally born heritage, as well as digital collections or collections of digitized heritage assets.
The MSc DSCH is structured along four learning streams:
1) Cultural heritage context. This stream will provide you with a cross-disciplinary understanding of the cultural heritage context, its significance and value in society and will develop your critical analytical skills.
2) Core data science skills is designed to develop core data science skills required for data analysis, interpretation, visualization and management. You will learn about mathematical methods for statistical analysis, signal processing and optimisation, you will explore the principles of human-computer interaction and the basis for data organisation and data exploration, and you will develop your programming skills.
3) Applied data science skills. Through hands-on applied modules, you will be able to learn about applied data skills of great potential, not only in the heritage sector but in other science and engineering contexts, and even social science contexts. Examples are crowd sourced data science, imaging data analysis, Heritage Building Information Modelling and many more
4) Research skills. During the programme, you will explore the latest cutting-edge research methods and technologies, enabling you to develop your own research skills, which will help you through your dissertation work.
You will study four compulsory modules and three optional modules:
Term 1 – compulsory modules
- Science and Engineering in Art, Heritage and Archaeology in Context
- Introduction to Statistical Data Science
- Heritage Data Mapping and Visualisation
Term 2 – compulsory module
- Heritage Data Management
Term 2 – select three optional modules from the list below
- Heritage Building Information Modelling
- Heritage Imaging
- Crowd-sourced and Citizen Data for Cultural HeritageMachine Learning for Heritage
Term 3 – dissertation
Students are required to submit a 10,000-word dissertation. The topic of the dissertation, which is supervised by a member of BSEER staff, is selected by the student in agreement with the programme director. It can be taken from a wide range of subjects related to the main themes of the programme and may be selected to assist career development or because of its inherent interest. Collaboration with industry for the selection of dissertation projects will be encouraged and facilitated whenever possible.
The programme can be studied full-time over one year, two years part-time, or two-to-five years flexibly.
Tuition fee information can be found on the UCL Graduate Prospectus.
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the section of the UCL website.
The Institute for Sustainable Heritage has collaborated with many of the world’s leading organisations in the field, including the V&A, Tate, the British Library, the National Archives, the Smithsonian Institution and UNESCO, as well as many industry partners. Guest speakers drawn from the Institute’s extensive contacts across the heritage sector will be invited to lead specialist lectures and tutorials, providing specialist knowledge as well as industry practice.
The programme draws upon the full range of expertise offered by the UCL Institute for Sustainable Heritage, the UCL Department Statistical Science, and industry and sector leaders. The DSCH programme is delivered by some of the world's most respected experts in their disciplines, producing both substantial scholarly work and highly innovative research at the leading edge of their fields.
- Key staff
Dr Alejandra Albuerne
Professor Matija Strlic
Dr Josep Grau-Bove
Data science is in high demand in many and diverse industries. As a graduate of the DSCH MSc you will be ideally placed to gain employment as a data scientist, in particular in those sectors that foster interdisciplinarity and break down barriers between technology and humanities or social sciences. Beyond the heritage sector, your training will equip you to succeed as a data scientist in applications such as marketing, media, architecture and construction, the arts and many more.
Cross-disciplinarity, critical thinking, an applied focus and an emphasis on innovation are the key qualities that will define the professional character of our graduates, and will make you stand out from other data scientists.
The programme has been developed with input from industry leaders from a diverse range of sectors, including architecture, heritage, social media and digital technologies. You will gain exposure to real data challenges from these industries and will develop a skill-set in data science that will be highly transferable across these and many other sectors.
- See detailed module information for this programme
- For more key programme information, including how to apply, please visit the UCL Graduate Prospectus
- If you haven’t found the information you need, you can email the Programme Leader, Dr Alejandra Albuerne: email@example.com
- For administrative information, please contact firstname.lastname@example.org