Cambridge Digital Humanities course timetable
June 2020
| Wed 3 |
Sources to Data
CANCELLED
We are currently reformatting our Learning programme for remote teaching; this will require some rescheduling so bookings will reopen and new sessions will be created for online courses as soon as possible. In the interim we would encourage you to register your interest so as to be notified of the new schedule. Please be aware that we hope to run many of our courses online, but that this is dependent on staff availability and resources so please be aware we may have to postpone or cancel some sessions Archives typically hold records containing enormous quantities of data presented in a variety of scribal and print formats. Extracting this information has traditionally involved long hours of expensive manual data-entry work. Nowadays this work can be automated to a large degree and could soon open archives and allow for unprecedentedly large structured data sets for curators, researchers, and the public alike. This workshop will examine new methods for collecting historical data from manuscript and printed documents. We will look at archival photography, OCR, page structure recognition, and new handwritten text recognition systems. Cutting-edge Cambridge research in this field will be demonstrated. |
| Fri 5 |
Mapping the Past [remote delivery]
Finished
This intensive workshop is split into two online chats and two 1-hour sessions. Participants will first learn to collect and process geospatial data from historical sources and process it using geographical information systems from Google Earth to QGIS. The first online session introduces research techniques for collecting, arranging and mapping geospatial data from historical sources, and is taught by Dr Oliver Dunn. His session is split into two parts: Part A will introduce both online sessions by showing some of our own research that makes use of Google Earth, 3D Maps in Excel, and historical GIS. In Part B you will be asked to locate a set of Scotland’s historical lighthouses on historical maps online and map their location and other attributes in Google earth and 3D Maps. The second online session introduces students to mapping humanities data using Q-GIS which is a free GIS (Geographical Information System) software platform. Course participants will need to download and install QGIS on their laptops before 5th of June. On the 1st of June there will be further details concerning downloading QGIS, a chat forum where we can discuss why you might wish to use GIS, and whether GIS is the right choice for you, and a release of course teaching materials. On 5 June you will be taken through the map creation process step-by-step. This session will be taught by Max Satchell. |
| Tue 9 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Wed 10 |
We are currently reformatting our Learning programme for remote teaching; this will require some rescheduling so bookings will reopen and new sessions will be created for online courses as soon as possible. In the interim we would encourage you to register your interest so as to be notified of the new schedule. Please be aware that we hope to run many of our courses online, but that this is dependent on staff availability and resources so please be aware we may have to postpone or cancel some sessions This session focusses on providing photography skills for those undertaking archival research. Dr Oliver Dunn has experience spanning more than 10 years digitising written and printed historical sources for major university research projects in the humanities and social sciences. The focus is very much on low-tech approaches and small budgets. We’ll consider best uses of smartphones, digital cameras and tripods. |
| Thu 11 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Mon 15 |
We are currently reformatting our Learning programme for remote teaching; this will require some rescheduling so bookings will reopen and new sessions will be created for online courses as soon as possible. In the interim we would encourage you to register your interest so as to be notified of the new schedule. Please be aware that we hope to run many of our courses online, but that this is dependent on staff availability and resources so please be aware we may have to postpone or cancel some sessions This public workshop will mark the end of the 2020 programme of Machine Reading the Archive, a digital methods development programme organised by Cambridge Digital Humanities with the support of the Researcher Development Fund. It will showcase the digital archive projects created by our cohort of project participants as well as invited contributions from leading experts in the field. |
| Tue 16 |
Bug Hunt 2020 [cancelled - Covid 19]
CANCELLED
This programme is an opportunity to learn, through practical experience and shared investigation, how to apply digital methods for exploring and analysing a body of archival texts. The core of the programme will be 5 x 2 hour classroom based sessions supplemented by group and individual work on tasks related to the project design, delivery and documentation in between sessions. In addition to attending all five face-to-face sessions, participants should set aside an additional 8-10 hours over the duration of the course for work on project-related tasks. During the programme we’ll work together on a particular topic: how insects were represented in books created for children in the 19th century. This question will help us to think about how children’s encounters with the natural world might have been framed and shaped by their reading. We’ll work on digital collections of 19th century children’s books exploring how such collections are built and how they can be used for machine reading. We’ll develop specific research questions and you’ll learn how to explore them using different tools for textual stylistic analysis. At the end, we’ll present findings and consider the implications of what we’ve discovered. Topics covered include; • The development of methods for machine reading the archive – ideas, motivations and ethics • Children’s books of the long 19th century – a beginner’s guide • Designing a small-scale investigation • Building a collection of digital texts • Transforming texts into searchable data • Analysing stylistic patterns in the data |
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Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Wed 17 |
Emma Reay is a third-year PhD researcher at the University of Cambridge and an associate lecturer at Anglia Ruskin University. Her current project explores depictions of children in videogames, and her research interests include representation studies, children's digital media, gaming and education, and playful activism. Adam Dixon is a game designer and writer who makes both physical and digital games. He has worked on everything from big public games that involve running around cities to narrative video games about learning scientific skills. Much of his work has involved working with museums and research organisations such as the Wellcome Trust, Science Museum, Nottingham Trent University and the V&A. This has included designing games, using play for public research engagement and most recently, teaching teenagers to create digital games for Wellcome Collection’s Play Well exhibition. Outside of that he works and releases his own games including roleplaying games, LARPs and interactive fiction. Applications https://www.cdh.cam.ac.uk/file/cdhgamedesign201920applicationdocx-0 should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Wednesday 10 June 2020. Successful applicants will be notified by 15 June 2020. This online course will introduce participants to the practice of game design. It will explore the different ways that digital and analogue games are designed, particularly how you can design with intent to communicate a mood, theme or message. Participants will learn game design skills - such as boxing-in, design documents and prototyping – alongside opportunities to test them out by creating their own short games. Examples will focus on game design in research-related contexts, including using games as part of your research process and to communicate research outcomes to diverse audiences. The sessions focus on game design, how to shape mechanics and play experiences, so no technical skills are needed. Participants will create their short games using both non-digital tools and simple, free software that will be taught in the sessions. Topics covered:
Format The course will be delivered online, with live teaching sessions taking place on Zoom.
A CRASSH blog post was created for the originally scheduled session which may be of interest to read and can be found here: http://www.crassh.cam.ac.uk/blog/post/Play-as-Research-Practice |
| Thu 18 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Tue 23 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Wed 24 |
Emma Reay is a third-year PhD researcher at the University of Cambridge and an associate lecturer at Anglia Ruskin University. Her current project explores depictions of children in videogames, and her research interests include representation studies, children's digital media, gaming and education, and playful activism. Adam Dixon is a game designer and writer who makes both physical and digital games. He has worked on everything from big public games that involve running around cities to narrative video games about learning scientific skills. Much of his work has involved working with museums and research organisations such as the Wellcome Trust, Science Museum, Nottingham Trent University and the V&A. This has included designing games, using play for public research engagement and most recently, teaching teenagers to create digital games for Wellcome Collection’s Play Well exhibition. Outside of that he works and releases his own games including roleplaying games, LARPs and interactive fiction. Applications https://www.cdh.cam.ac.uk/file/cdhgamedesign201920applicationdocx-0 should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Wednesday 10 June 2020. Successful applicants will be notified by 15 June 2020. This online course will introduce participants to the practice of game design. It will explore the different ways that digital and analogue games are designed, particularly how you can design with intent to communicate a mood, theme or message. Participants will learn game design skills - such as boxing-in, design documents and prototyping – alongside opportunities to test them out by creating their own short games. Examples will focus on game design in research-related contexts, including using games as part of your research process and to communicate research outcomes to diverse audiences. The sessions focus on game design, how to shape mechanics and play experiences, so no technical skills are needed. Participants will create their short games using both non-digital tools and simple, free software that will be taught in the sessions. Topics covered:
Format The course will be delivered online, with live teaching sessions taking place on Zoom.
A CRASSH blog post was created for the originally scheduled session which may be of interest to read and can be found here: http://www.crassh.cam.ac.uk/blog/post/Play-as-Research-Practice |
| Thu 25 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Tue 30 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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July 2020
| Wed 1 |
Emma Reay is a third-year PhD researcher at the University of Cambridge and an associate lecturer at Anglia Ruskin University. Her current project explores depictions of children in videogames, and her research interests include representation studies, children's digital media, gaming and education, and playful activism. Adam Dixon is a game designer and writer who makes both physical and digital games. He has worked on everything from big public games that involve running around cities to narrative video games about learning scientific skills. Much of his work has involved working with museums and research organisations such as the Wellcome Trust, Science Museum, Nottingham Trent University and the V&A. This has included designing games, using play for public research engagement and most recently, teaching teenagers to create digital games for Wellcome Collection’s Play Well exhibition. Outside of that he works and releases his own games including roleplaying games, LARPs and interactive fiction. Applications https://www.cdh.cam.ac.uk/file/cdhgamedesign201920applicationdocx-0 should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Wednesday 10 June 2020. Successful applicants will be notified by 15 June 2020. This online course will introduce participants to the practice of game design. It will explore the different ways that digital and analogue games are designed, particularly how you can design with intent to communicate a mood, theme or message. Participants will learn game design skills - such as boxing-in, design documents and prototyping – alongside opportunities to test them out by creating their own short games. Examples will focus on game design in research-related contexts, including using games as part of your research process and to communicate research outcomes to diverse audiences. The sessions focus on game design, how to shape mechanics and play experiences, so no technical skills are needed. Participants will create their short games using both non-digital tools and simple, free software that will be taught in the sessions. Topics covered:
Format The course will be delivered online, with live teaching sessions taking place on Zoom.
A CRASSH blog post was created for the originally scheduled session which may be of interest to read and can be found here: http://www.crassh.cam.ac.uk/blog/post/Play-as-Research-Practice |
| Thu 2 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Thu 9 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Tue 14 |
Leonardo Impett, Cambridge Digital Humanities Application forms should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Friday 22 May 2020. Successful applicants will be notified by 26 May 2020. This course will introduce graduate students, early-career researchers, and professionals in the humanities to the technologies of image recognition and machine vision, including recent developments in machine vision research in the past half-decade. The course will seek to combine a technical understanding of how machine vision systems work, with a detailed understanding of the possibilities they open to research and study in the humanities, and with a critical exploration of the social, political and ideological dimensions of machine vision. Learning outcomes By the end of the course, students should be able to:
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| Wed 15 |
Emma Reay is a third-year PhD researcher at the University of Cambridge and an associate lecturer at Anglia Ruskin University. Her current project explores depictions of children in videogames, and her research interests include representation studies, children's digital media, gaming and education, and playful activism. Adam Dixon is a game designer and writer who makes both physical and digital games. He has worked on everything from big public games that involve running around cities to narrative video games about learning scientific skills. Much of his work has involved working with museums and research organisations such as the Wellcome Trust, Science Museum, Nottingham Trent University and the V&A. This has included designing games, using play for public research engagement and most recently, teaching teenagers to create digital games for Wellcome Collection’s Play Well exhibition. Outside of that he works and releases his own games including roleplaying games, LARPs and interactive fiction. Applications https://www.cdh.cam.ac.uk/file/cdhgamedesign201920applicationdocx-0 should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Wednesday 10 June 2020. Successful applicants will be notified by 15 June 2020. This online course will introduce participants to the practice of game design. It will explore the different ways that digital and analogue games are designed, particularly how you can design with intent to communicate a mood, theme or message. Participants will learn game design skills - such as boxing-in, design documents and prototyping – alongside opportunities to test them out by creating their own short games. Examples will focus on game design in research-related contexts, including using games as part of your research process and to communicate research outcomes to diverse audiences. The sessions focus on game design, how to shape mechanics and play experiences, so no technical skills are needed. Participants will create their short games using both non-digital tools and simple, free software that will be taught in the sessions. Topics covered:
Format The course will be delivered online, with live teaching sessions taking place on Zoom.
A CRASSH blog post was created for the originally scheduled session which may be of interest to read and can be found here: http://www.crassh.cam.ac.uk/blog/post/Play-as-Research-Practice |
| Wed 29 |
The Transkribus Guided Project
Finished
We introduce the Transkribus software system that can be taught to read handwriting from images of documents and rapidly convert it into useful digital formats. This guided course provides basic training by practical immersion in this software, which requires only basic IT skills. Transkribus was developed by READ under the Horizon 2020 funding framework and is now a co-operative. It had 20,000+ users in 2019, and is becoming a standard research tool for mass transcription of archival sources. Participants will transcribe anonymised data from pre-loaded scans of forms filled out for the French national census of 1999 in Transkribus's downloadable software interface. These manual transcriptions will help train a handwritten text recognition (HTR) model to automatically transcribe many more of these forms later. In fact, the model will eventually allow the creation of one of the largest data sets ever attempted from manuscript sources. This course is a collaboration with Transkribus and Cambridge Digital Humanities. It is funded by a Cambridge Humanities Research Grant. |
August 2020
| Wed 5 |
The Transkribus Guided Project
Finished
We introduce the Transkribus software system that can be taught to read handwriting from images of documents and rapidly convert it into useful digital formats. This guided course provides basic training by practical immersion in this software, which requires only basic IT skills. Transkribus was developed by READ under the Horizon 2020 funding framework and is now a co-operative. It had 20,000+ users in 2019, and is becoming a standard research tool for mass transcription of archival sources. Participants will transcribe anonymised data from pre-loaded scans of forms filled out for the French national census of 1999 in Transkribus's downloadable software interface. These manual transcriptions will help train a handwritten text recognition (HTR) model to automatically transcribe many more of these forms later. In fact, the model will eventually allow the creation of one of the largest data sets ever attempted from manuscript sources. This course is a collaboration with Transkribus and Cambridge Digital Humanities. It is funded by a Cambridge Humanities Research Grant. |
October 2020
| Mon 12 |
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project)
Finished
Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020. Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives. |
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Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project)
Finished
Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020. Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives. |
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| Tue 13 |
This CDHBasics session will explain what data is, and what ‘humanities data’ looks like (via a behind-the-scenes tour of the Digital Library). This session covers good practice around file formats, version control and the principles of data curation for individual researchers. |
| Mon 19 |
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project)
Finished
Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020. Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives. |
|
Delving into Massive Digital Archives - finding lost, forgotten and neglected texts (Guided Project)
Finished
Application forms https://www.cdh.cam.ac.uk/file/cdhdelvingintomassivedaapplicationdocx should be returned to CDH Learning (learning@cdh.cam.ac.uk) by Tuesday 6 October 2020. Successful applicants will be notified by Thursday 8 October 2020. Massive digital archives such as the Internet Archive offer researchers tantalising possibilities for the recovery of lost, forgotten and neglected literary texts. Yet the reality can be very frustrating due to limitations in the design of the archives and the tools available for exploring them. This programme supports researchers in understanding the issues they are likely to encounter and developing practical methods for delving into massive digital archives. |