Cambridge Digital Humanities course timetable

Places are limited, and participants must complete this form to participate in addition to booking online. We will write and confirm your participation by email. Bookings will remain open until 10 am, Wednesday 20 October; however, participants are encouraged to apply early as demand is likely to be high, and we will not be able to guarantee that your ArcGis Online account will be activated for the first session.

This CDH Guided Project series will offer an overview of GIS techniques applied to digitising historical material, from basic manual digitisation to using platforms for crowd-sourced digitisation. It will introduce GIS best practices and terminology and enable participants to design and launch their own projects. Each session will offer a 20-minute presentation, followed by 10 minutes of Q&A and one hour of practice, using ArcGis Online and a range of other GIS solutions. The teaching will be delivered by a team composed of a geospatial analyst, an architect and a historian, giving participants from all fields a broad range of views and expertise to draw on.

Participation in this guided project will also contribute to an ongoing research project led by Dr Alexis Litvine and Dr Isabelle Séguy (anrcommunes.fr), which is (among other things) reconstructing historical transport networks for France. During the sessions, participants will help digitise nineteenth-century French roads using military maps. The work will ultimately be part of a journey planner (aka a "Google Maps") of the past for France.

Applications are invited from early career researchers and others at the University of Cambridge to join this project for four online sessions during the Guided Project phase in Oct-November. The project concludes with a live “mapathon” session on International GIS day, i.e. November 17. On this day, participants will all meet (in person preferably but online will be possible) for a friendly but competitive digitisation challenge against participants in a similar guided project held in France — pizza and refreshments will be provided.

Participants will need to commit to joining the live sessions and to set aside at least 3-4 hours of individual digitisation work. Participation in the final “mapathon” (online or in-person) is also expected, but no prior GIS knowledge is required.

Places are limited, and participants must complete this form to participate in addition to booking online. We will write and confirm your participation by email. Bookings will remain open until 10 am, Wednesday 20 October; however, participants are encouraged to apply early as demand is likely to be high, and we will not be able to guarantee that your ArcGis Online account will be activated for the first session.

This CDH Guided Project series will offer an overview of GIS techniques applied to digitising historical material, from basic manual digitisation to using platforms for crowd-sourced digitisation. It will introduce GIS best practices and terminology and enable participants to design and launch their own projects. Each session will offer a 20-minute presentation, followed by 10 minutes of Q&A and one hour of practice, using ArcGis Online and a range of other GIS solutions. The teaching will be delivered by a team composed of a geospatial analyst, an architect and a historian, giving participants from all fields a broad range of views and expertise to draw on.

Participation in this guided project will also contribute to an ongoing research project led by Dr Alexis Litvine and Dr Isabelle Séguy (anrcommunes.fr), which is (among other things) reconstructing historical transport networks for France. During the sessions, participants will help digitise nineteenth-century French roads using military maps. The work will ultimately be part of a journey planner (aka a "Google Maps") of the past for France.

Applications are invited from early career researchers and others at the University of Cambridge to join this project for four online sessions during the Guided Project phase in Oct-November. The project concludes with a live “mapathon” session on International GIS day, i.e. November 17. On this day, participants will all meet (in person preferably but online will be possible) for a friendly but competitive digitisation challenge against participants in a similar guided project held in France — pizza and refreshments will be provided.

Participants will need to commit to joining the live sessions and to set aside at least 3-4 hours of individual digitisation work. Participation in the final “mapathon” (online or in-person) is also expected, but no prior GIS knowledge is required.

We are pleased to welcome Dr Ann Borda as a guest lecturer for this CDH Methods Workshop. Ann is the Participatory Health Lead in the Co-design Living Lab for Digital Health in the Centre for Digital Transformation of Health at the University of Melbourne. She is a Fellow of the Australasian Institute of Digital Health, Honorary Senior Research Associate at University College London, and sits on the policy committee of the Climate and Health Alliance. Ann formerly held collaborative positions in JISC and at the Science Museum London. Her research spans living lab and citizen science methods, and emerging participatory practices in digital health and culture.

There is an increasing presence in research incorporating participatory approaches to the production of knowledge. Participatory research is a range of methods framed within ideological perspectives. Its fundamental principles are that the subjects of the research become involved as partners in the process of the enquiry, and enacted through a set of social values. Participation can be classified by various degrees of involvement. Participatory activities can be expressed through various methods and approaches, such as co-design, citizen science, crowdsourcing, living labs, participatory action research and community-based participatory research, among others.

Places are limited, and participants must complete this form to participate in addition to booking online. We will write and confirm your participation by email. Bookings will remain open until 10 am, Wednesday 20 October; however, participants are encouraged to apply early as demand is likely to be high, and we will not be able to guarantee that your ArcGis Online account will be activated for the first session.

This CDH Guided Project series will offer an overview of GIS techniques applied to digitising historical material, from basic manual digitisation to using platforms for crowd-sourced digitisation. It will introduce GIS best practices and terminology and enable participants to design and launch their own projects. Each session will offer a 20-minute presentation, followed by 10 minutes of Q&A and one hour of practice, using ArcGis Online and a range of other GIS solutions. The teaching will be delivered by a team composed of a geospatial analyst, an architect and a historian, giving participants from all fields a broad range of views and expertise to draw on.

Participation in this guided project will also contribute to an ongoing research project led by Dr Alexis Litvine and Dr Isabelle Séguy (anrcommunes.fr), which is (among other things) reconstructing historical transport networks for France. During the sessions, participants will help digitise nineteenth-century French roads using military maps. The work will ultimately be part of a journey planner (aka a "Google Maps") of the past for France.

Applications are invited from early career researchers and others at the University of Cambridge to join this project for four online sessions during the Guided Project phase in Oct-November. The project concludes with a live “mapathon” session on International GIS day, i.e. November 17. On this day, participants will all meet (in person preferably but online will be possible) for a friendly but competitive digitisation challenge against participants in a similar guided project held in France — pizza and refreshments will be provided.

Participants will need to commit to joining the live sessions and to set aside at least 3-4 hours of individual digitisation work. Participation in the final “mapathon” (online or in-person) is also expected, but no prior GIS knowledge is required.

We are pleased to welcome Dr Ann Borda as a guest lecturer for this CDH Methods Workshop. Ann is the Participatory Health Lead in the Co-design Living Lab for Digital Health in the Centre for Digital Transformation of Health at the University of Melbourne. She is a Fellow of the Australasian Institute of Digital Health, Honorary Senior Research Associate at University College London, and sits on the policy committee of the Climate and Health Alliance. Ann formerly held collaborative positions in JISC and at the Science Museum London. Her research spans living lab and citizen science methods, and emerging participatory practices in digital health and culture.

There is an increasing presence in research incorporating participatory approaches to the production of knowledge. Participatory research is a range of methods framed within ideological perspectives. Its fundamental principles are that the subjects of the research become involved as partners in the process of the enquiry, and enacted through a set of social values. Participation can be classified by various degrees of involvement. Participatory activities can be expressed through various methods and approaches, such as co-design, citizen science, crowdsourcing, living labs, participatory action research and community-based participatory research, among others.

In this CDH Basics session, we will discuss how to assess the impact of relevant legal frameworks, including data protection, intellectual property and media law, on your digital research project and consider what approach researchers should take to the terms of service of third-party digital platforms. We will explore the challenge of informed consent in a highly networked world and look at a range of strategies for dealing with this problem. 

This CDH Basics session investigates three different methods for accessing digital data ‘in bulk’: using an API (Application Programme Interface), web scraping and direct access (via download or on a hard drive). We will explore the importance of good practice in documenting the provenance of data that others have created and discuss the practical steps in research data management essential to ensuring that you are able to make legal and ethical use of this type of data in your research. No knowledge of programming languages is required, however, there will be a demonstration of a Python web scraper during the session and references to more in-depth tutorials on web scraping will be provided.

Data which other people have created is often either unstructured or structured in the wrong way for the questions that you want to answer. Rather than reinventing the wheel and collecting it all over again, this CDH Basics session introduces participants to OpenRefine, a free ‘power tool’ for dealing with messy data. In order to work with OpenRefine you will need administrator privileges to install software on your laptop. 

Itamar Shatz - Methods Fellow CDH

This course will introduce participants to key concepts in statistical analyses, including statistical significance, effect sizes, and linear models. The goal is to give participants the basic tools that they need in order to understand the use of statistical methods by others and to use these methods effectively in their own research. We will focus on an intuitive and practical understanding of statistical analyses, rather than on the mathematical details underlying them. As such, the course will be accessible for those without a quantitative background, although it will help to have knowledge of basic descriptive statistics (e.g., mean and standard deviation).

The course will cover (approximately) the following topics:

• Session 1: statistical significance and statistical tests (including hypothesis testing, p-values, statistical power, t-test, and chi-square test).
• Session 2: effect sizes, correlation, confidence intervals, and outliers.
• Session 3: linear regression (including simple/multiple regression, residuals, beta coefficients, and R-Squared).
• Session 4: linear regression continued (including test statistics, standard errors, centering, interaction, categorical predictors, linear models, and assumption testing).

Itamar Shatz - Methods Fellow CDH

This course will introduce participants to key concepts in statistical analyses, including statistical significance, effect sizes, and linear models. The goal is to give participants the basic tools that they need in order to understand the use of statistical methods by others and to use these methods effectively in their own research. We will focus on an intuitive and practical understanding of statistical analyses, rather than on the mathematical details underlying them. As such, the course will be accessible for those without a quantitative background, although it will help to have knowledge of basic descriptive statistics (e.g., mean and standard deviation).

The course will cover (approximately) the following topics:

• Session 1: statistical significance and statistical tests (including hypothesis testing, p-values, statistical power, t-test, and chi-square test).
• Session 2: effect sizes, correlation, confidence intervals, and outliers.
• Session 3: linear regression (including simple/multiple regression, residuals, beta coefficients, and R-Squared).
• Session 4: linear regression continued (including test statistics, standard errors, centering, interaction, categorical predictors, linear models, and assumption testing).

Jessica M. Parr, PhD (Simmons University and The Programming Historian)

We welcome Jessica Parr as a guest lecturer for this Methods Workshop, where we will discuss mapping techniques for scholars of the transatlantic slave trade. It will open with a discussion of addressing the Eurocentricity of geospatial techniques and the archives. We will then discuss strategies for reading against the archive to locate Black voices and strategies for determining geospatial coordinates from primary sources. Finally, the workshop will conclude with a demonstration of how to create maps in Tableau and some discussion of data ethics.

Please apply for a place if you would like to attend, on registration, you will be asked to complete and submit an information form (which will remain open until 10 am Monday, 14 February 2022), places are limited and selected on a rolling basis, we would suggest early completion.  We will confirm participation week commencing Monday, 21 February 2022.

Thomas Cowhitt, Methods Fellow - Cambridge Digital Humanities

This Methods Fellow's Workshop Series event will introduce users to social network analysis in R. Participants will be asked to generate their own relational dataset. We will then use several R packages to visualize and interpret relational data. By the conclusion of this course, users will be able to construct a relational dataset, load and clean this dataset in R, and generate static network diagrams and reports on descriptive network statistics.

Thomas Cowhitt, Methods Fellow - Cambridge Digital Humanities

This Methods Fellow's Workshop Series event will introduce users to social network analysis in R. Participants will be asked to generate their own relational dataset. We will then use several R packages to visualize and interpret relational data. By the conclusion of this course, users will be able to construct a relational dataset, load and clean this dataset in R, and generate static network diagrams and reports on descriptive network statistics.

Thomas Cowhitt, Methods Fellow - Cambridge Digital Humanities

This Methods Fellow's Workshop Series event will introduce users to social network analysis in R. Participants will be asked to generate their own relational dataset. We will then use several R packages to visualize and interpret relational data. By the conclusion of this course, users will be able to construct a relational dataset, load and clean this dataset in R, and generate static network diagrams and reports on descriptive network statistics.

This CDH Basics session is aimed at researchers who have never done any coding before. We will explore basic principles and approaches to writing and adapting code, using the popular programming language Python as a case study. Participants will also gain familiarity with using Jupyter Notebooks, an open-source web application that allows users to create and share documents containing live code alongside visualisations and narrative text.

Itamar Shatz - Methods Fellow CDH

This course will introduce participants to key concepts in statistical analyses, including statistical significance, effect sizes, and linear models. The goal is to give participants the basic tools that they need in order to understand the use of statistical methods by others and to use these methods effectively in their own research. We will focus on an intuitive and practical understanding of statistical analyses, rather than on the mathematical details underlying them. As such, the course will be accessible for those without a quantitative background, although it will help to have knowledge of basic descriptive statistics (e.g., mean and standard deviation).

The course will cover (approximately) the following topics:

• Session 1: statistical significance and statistical tests (including hypothesis testing, p-values, statistical power, t-test, and chi-square test).
• Session 2: effect sizes, correlation, confidence intervals, and outliers.
• Session 3: linear regression (including simple/multiple regression, residuals, beta coefficients, and R-Squared).
• Session 4: linear regression continued (including test statistics, standard errors, centering, interaction, categorical predictors, linear models, and assumption testing).

This course demystifies principles of data visualisation and practices of graph creation in Python to help trainees better understand and reflect how Good Data Visualisation under “5 Principles” can be achieved, and develop Python’s application in data visualisation beyond analysis. This course is aimed at students/staff who are interested in and/or use data visualisation in research or outreach and hope to explore data visualisation in Python with basic Python knowledge. It is delivered in a format of 4-hr workshop (on Zoom) + c. 2hr self-paced preparation and post-class exercises+ 1hr asynchronous question-shooting, combining theories, case learning, peer interactions and practical: we first present an introduction on key concepts of and problems in data visualisation, before case studies and group discussion on data visualisation principles and how to visualise data better in practices; then under a demonstration, we employ Python to visualise data and go through types of graphs.