Courses

Methods, Tools and Best Practices in Digital Humanities (fall term 2017)

Tuesday, 10:15-12:00, 3 ECTS
Dr. Laurent Pugin

This course provides an overview of the methods, the tools and the best practices in the domain of the Digital Humanities. It will cover a wide range of concepts by looking at existing projects in the field.

Topics:
- data acquisition (digitisation, crowdsourcing, document recognition)
- data structures and formats
- knowledge modelling, with a focus on digital editions based on the Text Encoding Initiative
- information archiving and versioning
- visualisation techniques using temporal and geographic information systems;
- and algorithms for data processing and data analysis (concepts of machine learning, image analysis methods).

Through hands-on sessions with their own laptops, the students will also learn basic programming concepts using software used for processing this type of data. At the end of the course, the students will have gained an overall understanding of the Digital Humanities and gathered a ground knowledge on how to collect, organise, process and publish data in this context. No programming prior knowledge is required.

Further information: KSL

 

Previous DH courses 

Introduction to Digital Humanities

What is (or are) the Digital Humanities? What relevance do digital methods have for research in the different humanistic disciplines? What does it mean to “do digital humanities”? This seminar is a discussion-led introduction to the field of Digital Humanities, intended for students at the advanced Bachelor’s or Master’s level. We will cover the history of the field to the present day, and take a closer look at the relationship between computational analysis, humanistic theory, and hermeneutics. We will also touch on more practical aspects of the digital humanities such as the representation of cultural artifacts, and particularly texts, within the digital domain. By the end of the course students should have a good understanding of how to formalize and model concepts from their humanistic disciplines into the digital domain, and will be aware of the plethora of further hands-on training opportunities in Digital Humanities tools and techniques across Switzerland, Europe, and the rest of the world.

Electronic Publishing for Scholars

This course is a hands-on introduction to the technology and techniques behind electronic publishing, as it is relevant for scholarly and academic communication. Topics to be covered include: practical aspects such as the basics of HTML and XML markup and platforms for self-publishing (e.g. blogs); electronic scholarly journals and open access; digitization, preservation, and sustainability of electronic publications; freedom of information, data protection, and copyright issues; issues of academic credit, citation, and plagiarism. The course will include practical sessions in a computer lab as well as class discussion and debate.

Tools and Techniques for Digital Humanities

This course is a workshop, open to students at all levels, for experimentation with tools and techniques that can be applied to various research questions and academic practices within the digital humanities. Through hands-on sessions with their own laptops, students will gain experience with software for managing citations and bibliography; techniques for text transcription, markup, and processing; basic statistical analysis; regular expressions for complex data retrieval; straightforward computer scripting; and other topics pertaining to the needs and interests of the students.

Management of Digital Research Data

The first stage of almost any digital humanities project is to collect and organize the data that will be studied; this might be texts, images, spreadsheets, or any other collection of information and resources. In this class we will focus on the management, organization, and modeling of the digital data we collect. The lessons will cover how to process and access flat-file formats such as Excel and CSV, how to build tabular data up into a relational database, alternative database solutions such as XML databases for projects that make heavy use of XML encodings such as that of the TEI, and data storage and modeling with the use of graph databases. Students will gain experience with Python programming over the course of the term, although no prior knowledge of Python is necessary.

DH courses at Uni Bern, HS 2016

Introduction to Digital Data and Digital Editions 

Tuesday 10:15-12.00 a.m.

The development of the digital world opens new perspectives for research in the humanities. In this context collecting, organizing, processing and publishing data in an appropriate way is essential. This course is an introduction to best practices for managing digital data for human sciences with a focus on digital editions. It will cover a wide range of formats and data structures that are used in this field, primarily text formats but not only. It includes HTML, XML in general and widely used standards such as TEI and MEI. Through hands-on sessions, students will also learn basic programming concepts using software used for processing this type of data. No programming prior knowledge is required. 

 

Previous DH courses at Uni Bern 

Introduction to Digital Humanities

What is (or are) the Digital Humanities? What relevance do digital methods have for research in the different humanistic disciplines? What does it mean to “do digital humanities”? This seminar is a discussion-led introduction to the field of Digital Humanities, intended for students at the advanced Bachelor’s or Master’s level. We will cover the history of the field to the present day, and take a closer look at the relationship between computational analysis, humanistic theory, and hermeneutics. We will also touch on more practical aspects of the digital humanities such as the representation of cultural artifacts, and particularly texts, within the digital domain. By the end of the course students should have a good understanding of how to formalize and model concepts from their humanistic disciplines into the digital domain, and will be aware of the plethora of further hands-on training opportunities in Digital Humanities tools and techniques across Switzerland, Europe, and the rest of the world.

Electronic Publishing for Scholars

This course is a hands-on introduction to the technology and techniques behind electronic publishing, as it is relevant for scholarly and academic communication. Topics to be covered include: practical aspects such as the basics of HTML and XML markup and platforms for self-publishing (e.g. blogs); electronic scholarly journals and open access; digitization, preservation, and sustainability of electronic publications; freedom of information, data protection, and copyright issues; issues of academic credit, citation, and plagiarism. The course will include practical sessions in a computer lab as well as class discussion and debate.

Tools and Techniques for Digital Humanities

This course is a workshop, open to students at all levels, for experimentation with tools and techniques that can be applied to various research questions and academic practices within the digital humanities. Through hands-on sessions with their own laptops, students will gain experience with software for managing citations and bibliography; techniques for text transcription, markup, and processing; basic statistical analysis; regular expressions for complex data retrieval; straightforward computer scripting; and other topics pertaining to the needs and interests of the students.

Management of Digital Research Data

The first stage of almost any digital humanities project is to collect and organize the data that will be studied; this might be texts, images, spreadsheets, or any other collection of information and resources. In this class we will focus on the management, organization, and modeling of the digital data we collect. The lessons will cover how to process and access flat-file formats such as Excel and CSV, how to build tabular data up into a relational database, alternative database solutions such as XML databases for projects that make heavy use of XML encodings such as that of the TEI, and data storage and modeling with the use of graph databases. Students will gain experience with Python programming over the course of the term, although no prior knowledge of Python is necessary.