Theme: CDH Basics

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.

This CDHBasics session focuses on the importance of metadata (‘data about data’), examining the crucial role played by classification systems and standards in shaping how scholars interact with historical and cultural records.

This CDHBasics session looks at how searching and finding technologies structure scholarship. It also covers

• an introduction to search engines, both for web search and custom search functions within collections;
• discussion about OCR errors and blindspots in digital search in historical collections
• problems of fragmentation of the source text, and the legacy of pre-digital formats such as microfilm.

This CDHBasics session explores the lifecycle of a digital research project across the stages of design;

• data capture
• transformation
• analysis
• presentation and preservation

it also introduces tactics for embedding ethical research principles and practices at each stage of the research process.

This CDH Basics session will see discussion on 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 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 which allows users to create and share documents containing live code alongside visualisations and narrative text.

This CDH Basics session provides a brief introduction to different methods for capturing bulk data from online sources or via agreement with data collection holders, including Application Programme Interfaces (APIs). We will address issues of data provenance, exceptions to copyright for text and data-mining, and discuss good practice in managing and working with data that others have created.

This CDH Basics session explores how data which you have captured rather than created yourself, is likely to need cleaning up before you can use it effectively. This short session will introduce you to the basic principles of creating structured datasets and walk through some case studies in data cleaning with OpenRefine, a powerful open source tool for working with messy data.

This CDH Basics session introduces the IIIF image data framework, which has been developed by a consortium of the world’s leading research libraries and image repositories and methods of access to image collections including the collections of Cambridge University Digital Library. We will also discuss a range of methods using IIIF image data in humanities research.

Machine vision systems can potentially help humanities researchers see historical and cultural image collections differently, and could provide tools to answer new research questions. This CDH Basics session provides an introductory overview of basic tasks in machine vision, such as Image Classification, Object Detection and Image Captioning within a critical framework highlighting the challenges of algorithmic bias and the limits of automation as a method for humanistic enquiry.

This CDH Basics session provides a basic introduction to good practice around understanding file formats, version control and the principles of data curation for individual researchers. We will examine the importance of metadata (‘data about data’), exploring the crucial role played by classification systems and standards in shaping how scholars interact with historical and cultural records. Rather than accepting data as a ‘given’, we will discuss the creation and curation of data as interpretative practices and analyse their relationship to other traditions of scholarship in the humanities and social sciences.

In this CDH Basics session, participants will explore how searching and finding technologies structure scholarship, through an introduction to search engines both for web search and custom search functions within collections. We will discuss how errors introduced by digitisation technologies create blindspots for digital search in historical collections, interacting with social and legal processes to structure bias and discrimination into search processes. The session will provide a brief introduction to the importance of machine-learning driven systems for digital search and suggest strategies for researchers to critically engage with, rather than passively accept, search engine results.

This CDH Basics session explores the lifecycle of a digital research project, across the stages of design, data capture, transformation, analysis, presentation and preservation, and introduces tactics for embedding ethical research principles and practices at each stage of the research process.

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 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.

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. 

The impact of well-crafted data visualisations has been well-documented historically. Florence Nightingale famously used charts to make her case for hospital hygiene in the Crimean War, while Dr John Snow’s bar charts of cholera deaths in London helped convince the authorities of the water-borne nature of the disease. However, as information designer Alberto Cairo notes, charts can also lie. This introductory CDH Basics session presents the basic principles of data visualisation for researchers who are new to working with quantitative data.

This CDH Basics session introduces the IIIF image data framework, which has been developed by a consortium of the world’s leading research libraries and image repositories and demonstrates a range of different machine learning-based methods for exploring digital image collections.

Machine learning-driven systems for seeing and sorting still and moving images are increasingly common in many contexts. This CDH Basics session explores the technical fundamentals of machine vision and discusses the societal and cultural impact of these systems, including the challenges and opportunities faced by humanities and social science researchers using computer vision systems as research tools.

Ensuring long-term access to digital data is often a difficult task: both hardware and code decay much more rapidly than many other means of information storage. Digital data created in the 1980s is frequently unreadable, whereas books and manuscripts written in the 980s are still legible. This CDH Basics session explores good practice in data preservation and software sustainability and looks at what you need to do to ensure that the data you don’t want to keep is destroyed.

This session provides a brief introduction to different methods for capturing bulk data from online sources or via agreement with data collection holders, including Application Programme Interfaces (APIs). We will address issues of data provenance, exceptions to copyright for text and data-mining, and discuss good practice in managing and working with data that others have created.

• Data collection methods

• Introduction to working with APIs

• Data brokerage

• Provenance and integrity

• Assessing intellectual property, copyright and Data Protection issues

• Documentation of collection methods

The impact of well-crafted data visualisations has been well-documented historically. Florence Nightingale famously used charts to make her case for hospital hygiene in the Crimean War, while Dr John Snow’s bar charts of cholera deaths in London helped convince the authorities of the water-borne nature of the disease. However, as information designer Alberto Cairo notes, charts can also lie. This introductory Basics session presents the basic principles of data visualisation for researchers who are new to working with quantitative data.

• Principles and good practice in data visualisation

• Basic introduction to quantitative methods of data analysis

This CDH Basics session explores the lifecycle of a digital research project across the stages of design, data capture, transformation, and analysis, presentation and preservation. It introduces tactics for embedding ethical research principles and practices at each stage of the research process.

• Introduction to the digital project life cycle

• Ethics by design and EDI-informed data processing

• Data and metadata - definitions

• Basics of data curation (good practice in file naming, version control)

• Understanding files and folders

Ensuring long-term access to digital data is often a difficult task: both hardware and code decay much more rapidly than many other means of information storage. Digital data created in the 1980s is frequently unreadable, whereas books and manuscripts written in the 980s are still legible. This session explores good practice in data preservation and software sustainability and looks at what you need to do to ensure that the data you don’t want to keep is destroyed.

• Data and code sustainability

• Retention, archiving and re-use

• Data destruction

• Recap on the project life-cycle

Data which you have captured rather than created yourself is likely to need cleaning up before you can use it effectively. This short session will introduce you to the basic principles of creating structured datasets and walk you through some case studies in data cleaning with OpenRefine, a powerful open source tool for working with messy data.

• Structuring your data

• Cleaning messy textual data with OpenRefine

• Batch processing file names