History and the digital
Summary
The course presents a number of computational approaches & tools that can be used to study history. Drawing on case studies from the history of science & technology, the course also offers students the opportunity to critically reflect on their own practices as digital humanists and data scientists.
Content
The development of information technologies and the rise of the digital humanities have opened new, exciting avenues for historical research and for the engagement of historians with the public. History and the digital have intersected in ways that, first, reconfigure historical research through the extensive digitization of sources and the creation of computational tools to process historical data ("digital history"); second, offer a wealth of new objects for historical research ("historicizing the digital"). Accordingly, the course proposes not only to survey the main computational approaches and methods that can be used to study history, but also, drawing on a series of case studies from the history of science and technology, to critically reflect on what it means to think digitally. Students will develop individual or small-group projects in digital history and will document their research in a final paper.
INTRODUCTION
Week 1. History, Science, History of Science
PART I: TEXTS
Week 2. Towards Big Data? Digitized and Born-Digital Sources in History
Week 3. History of Information Overload
Week 4. Text Analysis
PART II: NUMBERS
Week 5. Multiple Component Analysis & Regressions
Week 6. Trust in Numbers: Quantifying the World
Week 7. Network Analysis
PART III: IMAGES
Week 8. Data Visualization
Week 9. Image Analysis & Computer Vision
Week 10. Picturing Science: Drawings, Graphs, Diagrams
PART IV: THE PUBLIC
Week 11. Virtual Museums
Week 12. Science, the Public, and Invisible Technicians
CONCLUSION(S)
Week 13. A Critique of Digital Humanities
Week 14. Final Presentation of Projects
Keywords
history, social sciences, digital, history of science, big data, text analysis, data visualization, citizen science, history of technology, digital humanities, computational thinking, ethics, science and society
Learning Prerequisites
Required courses
None
Recommended courses
nice to have:
- CS-401 (Applied data analysis) or equivalent
- a SHS course in history (for example: HUM-221, HUM-276, HUM-385 etc.)
Learning Outcomes
By the end of the course, the student must be able to:
- Identify and formulate important research questions in history
- Explore historical data using a variety of computational approaches
- Analyze the differences and similarities between the natural and the human/social sciences
- Contextualise her/his data science practice through historical examples
Transversal skills
- Make an oral presentation.
- Write a scientific or technical report.
- Use a work methodology appropriate to the task.
- Demonstrate the capacity for critical thinking
Teaching methods
Lectures + discussion of readings (2 hours per week)
Student projects (3 hours per week)
Expected student activities
Students are expected to attend lectures, read the assigned articles, participate actively to class discussions, design and conduct projects in small groups, take the final exam.
Assessment methods
Project (70%): two intermediary reports (each 10%) and one final report (50%)
Final written exam (30%)
Supervision
| Office hours | Yes |
| Assistants | Yes |
| Forum | Yes |
Resources
Bibliography
Lisa Gitelman (ed.), "Raw Data" is an Oxymoron, Cambridge, Mass.: MIT Press, 2013.
Shawn Graham, Ian Milligan and Scott Weingart, Exploring Big Historical Data, The Historian's Macroscope, London: Imperial College Press, 2015.
Jo Guldi and David Armitage, The History Manifesto, Cambridge: Cambridge University Press, 2014.
Ian Milligan, "Mining the 'Internet Graveyard': Rethinking the Historian's Toolkit," Journal of the Canadian Historical Association, 23(2), 2015: 21-64.
Ressources en bibliothèque
- Lisa Gitelman (ed.), "Raw Data" is an Oxymoron
- Jo Guldi and David Armitage, The History Manifesto
- Ian Milligan, "Mining the 'Internet Graveyard': Rethinking the Historian's Toolkit,"
- Shawn Graham, Ian Milligan and Scott Weingart, Exploring Big Historical Data, The Historian's Macroscope
Moodle Link
In the programs
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: History and the digital
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 3 Hour(s) per week x 14 weeks
- Type: mandatory
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: History and the digital
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 3 Hour(s) per week x 14 weeks
- Type: mandatory
- Exam form: Written (summer session)
- Subject examined: History and the digital
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: History and the digital
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: History and the digital
- Courses: 2 Hour(s) per week x 14 weeks
- Project: 3 Hour(s) per week x 14 weeks
- Type: optional