Topics in DH
3D Modeling
3D modeling is the process of creating a three-dimensional model either through computer software or through 3D printing. 3D modeling serves as the basis for many Virtual Reality experiences. 3D models can be “drawn” by hand in a computer or created through the use of videos or photographs. Creating 3D models from photographs, especially in the case of archeology, is known as photogrammetry.
Further information can be found at:
- Wikipedia List of 3D Modeling Software.
- 3D Modeling of Buildings: Outstanding Sites (2014) Raphaële Héno and Laure Chandelier.
- Photogrammetry.
Black Digital Humanities
Black Digital Humanities is an approach to community, methodology, praxis, and theory in digital humanities that centers black thought and cultural production. In the words of Jessica Marie Johnson and Mark Anthony Neal, it “roots itself in the challenge of living in the wake of black people rendered inhuman, non-existent, and disposable by the slave ship, the plantation, the colonial state, the prison, the border.” As Marisa Parham says, “Black people deserve frivolity and the future.”
Further information:
- Black Code Studies special issue of the Black Scholar edited by Jessica Marie Johnson and Mark Anthony Neal.
- sxarchipelagos special issue “Slavery in the Machine” edited by Jessica Marie Johnson.
- Black Digital Humanities Projects & Resources: A List.
Computational History
Computational History is a branch of digital history that carries out historical studies via machine learning and other data-heavy and computational approaches like network analysis.
For further information see:
- How the New Science of Computational History Is Changing the Study of the Past MIT Technology Review (June 23, 2016).
- Computational Historical Thinking: With Applications in R (2018, ongoing) Lincoln A. Mullen.
Computational Linguistics
Computational linguistics is an interdisciplinary field that is interested in the rule-based modeling of any natural (human) language from a computational perspective. It is also interested in computational approaches to the study of traditional questions of linguistics research. Computational linguistics is practiced by computer scientists, linguists, philosophers, psychologists, and a variety of other scholars.
Further information can be found at:
- Wikipedia Computational linguistics.
- The Handbook of Computational Linguistics and Natural Language Processing (2013) edited by Alexander Clark, Chris Fox, Shalom Lappin.
- The Oxford Handbook of Computational Linguistics (2004) edited by Ruslan Mitkov.
Corpus Linguistics
Corpus linguistics involves the study of language from a corpus of texts. In corpus linguistics, texts are grouped together by their type for study, that is texts of a similar nature are studied in relation to one another in order to produce meaningful results. For example, one can make a corpus of doctoral dissertations for study or a corpus of news articles from similar types of newspapers. Corpus linguistics can include the annotation of texts, or it can include the analysis of texts.
Further information can be found at:
- The Cambridge Handbook of English Corpus Linguistics (2015) edited by Douglas Biber and Randi Reppen.
- Contemporary Corpus Linguistics (2009) edited by Paul Baker.
- Tools for Corpus Linguistics by Kristin Berberich, Ingo Kleiber, and others.
- An Introductory Bibliography to Corpus Linguistics by Heather Froehlich.
- Corpus Linguistics: Method, Analysis, Interpretation online course from Future Learn.
- Lancaster Summer Schools in Corpus Linguistics. This link is for summer 2019. See the main Lancaster Summer Schools page for up-to-date information about their annual offerings.
Critical Code Studies
Critical code studies is a broad field that brings together digital humanities, software studies, cultural studies, computer science, and human-computer interaction. The main focus of the field is to study the cultural importance of computer code. The idea is to examine a piece of code with the same emphasis on nuance and understanding as examining a piece of literature.
For more information see:
- Critical Code Studies Mark C. Marino, electronic book review December 4, 2006.
- Track Changes: A Literary History of Word Processing (2016) Matthew G. Kirschenbaum.
- 10 Print (2012). By Nick Montfort, Patsy Baudoin, John Bell, Ian Bogost, Jeremy Douglass, Mark C. Marino, Michael Mateas, Casey Reas, Mark Sample, and Noah Vawter.
Cultural Analytics
Cultural analytics is the study of large-scale cultural phenomena using computational approaches. Practitioners generally mine large sets of cultural data such as library catalogs, collections of images or videos, scanned books, or social networks.
Further information can be found here:
DH Feminism
DH feminism aims to emphasize and increase the role of women and feminists in technology and digital humanities, as well as approach technological questions with a feminist lens. For similar approaches, but with an emphasis on postcolonialism, see DHPoCo.
For more information see:
- Women in the digital humanities started by Jacqueline Wernimont.
- All the Digital Humanists Are White, All the Nerds Are Men, but Some of Us Are Brave Moya Z. Bailey Journal of Digital Humanities 1, no. 1 (Winter 2011).
- don’t circle the wagons Bethany Nowviskie.
- Some things to think about before you exhort everyone to code Miriam Posner.
- Bodies of Information: Intersectional Feminism and Digital Humanities (2018). Elizabeth Losh and Jacqueline Wernimont, Editors.
DH Postcolonialism
DH postcolonialism is the application of key facets of postcolonial studies such as critiques of colonialism, imperialism, and globalization and their relationships to race, class, gender, sexuality, and disability to digital humanities. Much like DH Feminism aims to bring more women and approaches of feminist studies to DH, DH post-colonialism aims to decolonize digital studies.
For more information see:
- Postcolonial Digital Humanities. Adeline Koh and Roopika Risam.
- New Digital Worlds (2018). Roopika Risam.
Data Visualization
Data visualization, or DataViz, concerns the visual representation of data in a variety of ways including graphs, plots, maps, and other graphics like network visualizations.
Examples of visualization software include QGIS and ArcGIS for GIS mapping or Gephi and Pajek for networks, and Tableau for general purpose visualizations.
Many of the approaches and tools for data viz come from the natural and social sciences. For some discussion of how best to apply visualization techniques to humanistic research, see humanities visualization.
Reference works on the best practices of data visualization include:
- The Visual Display of Quantitative Information (1983) Edward R. Tufte.
- Data Visualization: A Practical Introduction (2019) Kieran Healy.
- Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures (2019) Claus O. Wilke.
Digital Art History
Digital Art History is the use of digital humanities tools to further traditional aspects of art history and to create new avenues for exploration. Using these methods, scholars can process large volumes of digitized images or texts that describe works of art. Scholars can also trace connections between artists, purchasers, and museums through network analysis for example.
Further information can be found at:
Digital Editions
Digital editions are often instances of physical objects, often texts like novels or news publications, that are created digitally rather than in print format. Digital editions further allow scholars to include annotations and scholarly interpretations of a text using a number of technologies, for later analysis or publication, including through the use of the Text Encoding Initiative.
Further information can be found at:
Digital Forensics
Digital forensics is a form of forensic science that seeks to recover and investigate materials stored on digital devices. A practitioner of digital forensics can take metadata, for example, and use it to determine authorship of documents. Similar techniques can also be used to determine if a digital document has been tampered with or falsified in any way.
Further information can be found at:
- Wikipedia Digital Forensics.
- The Journal of Digital Forensics, Security and Law.
- Digital Investigation: The International Journal of Digital Forensics & Incident Response.
- The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics (2015) John Sammons.
- Digital Forensics with Open Source Tools (2011) Cory Altheide and Harlan Carvey.
Digital History
Digital history is as multifaceted as history itself, but often aligns itself with one of a few varieties:
- Using the web, mobile apps, and other digital media to engage the public with history. See also Digital Public History.
- Using computational techniques, including statistical and visual, to augment traditional research practices. See also Computational History and Cultural Analytics.
- Using scanners, cameras, photogrammetry, modeling software, etc. to construct flat or 3D models of historical documents, artifacts, and buildings. Models might be used for archival, public, or research purposes. See also 3D Modeling and Digital Editions.
- Creating complex and deep maps of the past for public or research purposes. See also Historical GIS.
- Using digital teaching methods and assigning the creation of multimedia objects like websites, podcasts, and videos for students of history. See also Digital Pedagogy.
More information can be found in these sources:
- The Historian’s Macroscope (2015) by Shawn Graham, Ian Milligan, and Scott B. Weingart.
- The Inclusive Historian’s Handbook | Digital History (2019) by Sheila Brennan.
- Wikipedia | Digital History.
Digital Pedagogy
Digital pedagogy is the use of digital technologies for both teaching and learning. Digital pedagogy can encompass websites that include full lessons, like SocialChange101.org; online repositories of annotated primary sources, like Seventeen Moments in Soviet History; and using technology for assignments to assess student learning such as having students create a blog post or podcast instead of a traditional paper or exam.
Digital Pedagogy in the Humanities offers curated and peer-reviewed pedagogical materials that are available now for reuse and re-mixing, all organized around important concepts and keywords. See the Introduction or use the Search to find materials based on your needs. The Getting Started tag offers entry-level assignments, syllabi, rubrics for those who are new to Digital Pedagogy.
Further information can be found at:
- Digital Pedagogy in the Humanities.
- Global Resources: MOOCs/online courses.
- CMU Eberly Center Technology for Education.
- Wikipedia Digital Pedagogy.
- Hybrid Pedagogy. An open-access journal of learning, teaching, and technology
Digital Public History
Public history consists of tasks such as historic preservation and collecting oral histories as well as storing and disseminating historical information through archives and museums. Digital public history is a branch of public history that includes the electronic collection, storage, or access of public history materials. In 2015, the Joint Task Force on Public History Education and Employment found that while public history employers still highly value traditional historical skills such as research and writing, historiographical knowledge, and oral and written communication, employers in public history are increasingly seeking candidates that have skills related to digital media, fund-raising, and project management. Thus, those interested in public history should also have a knowledge of related digital applications of traditional public history approaches. Examples of digital public history include The History Makers, The US Holocaust Memorial Museum, and The Charles “Teenie” Harris Archive.
Digitization
Digitization is the process of taking a physical source and making a digital version of it for preservation, access, or analysis. Digitization can take many different approaches and forms.
Digitizing images such as photographs, drawings, or pages and saving them as image files (like .jpeg or .tiff) allows them to be examined for the purposes of cultural analytics or digital art history. Digital images can also be housed online for digital public history projects such as museum websites or online archives.
Optical character recognition (OCR) is the process of converting the images of text pages into editable text. Adobe Acrobat and AbbyyFinereader both have OCR features. The free software Tabula is good for extracting text from images containing tabular data.
Another form of digitization is 3D modeling. 3D models can be used for a variety of historical, artistic, or archaeological research. 3D modeling also allows for the creation of virtual reality experiences, which can be applied to a variety of disciplines such as history or English for the purposes of digital pedagogy.
Distant Reading
Distant reading, as the name suggests, is set in opposition to the form of literary analysis known as close reading. Instead of focusing on textual minutiae, distant reading focuses on the generalities of a text or texts, often via computational means. A frequent objective of distant reading is not to scrutinize a particular work, but to see texts in relation to one another as part of a system.
Further information on distant reading can be found at:
- Stanford Literary Lab.
- Distant Horizons: Digital Evidence and Literary Change (2019) Ted Underwood.
- Macroanalysis: Digital Methods & Literary History (2013) Matthew Jockers.
- A World of Fiction: Digital Collections and the Future of Literary History (2018). Katherine Bode.
Global Digital Humanities
An effort to put the global digital humanities community in conversation with itself, particularly focused on making space for communities orthogonal to global power structures. The effort often elevates the technical and critical contributions of communities beyond those that are commonly known or well-resourced.
For more information see:
HGIS
HGIS stands for historical geographic information system. Most often, this means using mapping software to display or analyze geographic data in order to answer historical questions. Although most often used for environmental history, HGIS lends well to a variety of historical methodologies such as social and economic history. HGIS is a form of Digital History.
HGIS research can be done with a variety of webplatforms as well as desktop software such as:
- The website kepler.gl.
- The ESRI webplatform ArcGIS Online
- The open source desktop software QGIS
- The licensed desktop software ArcGIS Pro
More information can be found in these sources:
- Wikipedia | Historical geographic information system
- H-net HIGS
- Historical Geography and GIS SSHA
- Placing History: How Maps, Spatial Data, and GIS Are Changing Historical Scholarship (2008) Edited by Anne Kelly Knowles and Amy Hillier.
- Historical GIS: Technologies, Methodologies and Scholarship (2007) Ian Gregory and Paul Ell.
- The Routledge Companion to Spatial History (2018) Edited by Ian Gregory, Don DeBats and Don Lanfreniere.
- The Programming Historian Lesson Index: Mapping.
Humanities Visualization
As humanists borrow more techniques from the social and natural sciences for research, there is the tendency to also borrow the conventions of data visualization from those fields. Many prominent figures in digital humanities, however, have argued that those conventions are not the best for the interpretive bases of humanistic inquiry. Thus, they call for humanities visualization in an attempt to produce visualizations that convey the uncertainties of this type of research such as ambiguity or contradiction.
For more information see:
- Graphical Approaches to the Digital Humanities (2015) Johanna Drucker.
- Humanities Approaches to Graphical Display Johanna Drucker, digital humanities quarterly 5, no. 1 (2015).
- Data by Design (forthcoming) Lauren F. Klein.
- Data Feminism (2018). Catherine D’Ignazio & Lauren F. Klein.
Latinx Digital Humanities
Latinx Digital Humanities centers the “heritage, history, language, and ethnic identity” of the transnational, exile, native, and immigrant peoples who make up the Latinx community. It finds its historical roots in the recovery work of groups like the University of Houston’s “Recovering the US Hispanic Literary Heritage” project, and in the writing of Chicana feminists like Gloria Anzaldúa and Cherríe Moraga, offering, as María Cotera writes, a “new praxis of Chicana feminism at the intersection of digital and analog culture.” It aims, in the words of Lorena Gauthereau, to use DH “to reclaim lost histories, reveal injustices, and demand that our voices be heard.” Latinx DH can sometimes be found under #usldh
Further Information:
- Gabriela Baeza Ventura, Lorena Gauthereau, and Carolina Villarroel, “Recovering the US Hispanic Literary Heritage: A Case Study on US Latina/o Archives and Digital Humanities.” Preservation, Digital Technology & Culture 48(1), 2019: 17-27. https://doi.org/10.1515/pdtc-2018-0031
- María Cotera, “Nuestra Autohistoria: Toward a Chicana Digital Praxis.” American Quarterly 70.3, September 2018. 483-504. 10.1353/aq.2018.0032
- U.S. Latino and Southwestern DH Projects (Crowdsourced)
Machine Learning
Machine learning is the use of algorithms and statistical models to have a computer perform an automated task through patterns and inference rather than explicit instructions. Stylometry is an example of digital humanities that occasionally uses machine learning.
For further information see:
- Wikipedia Machine Learning.
- Introduction to Machine Learning (Third Edition, 2014) Ethem Alpaydin.
- Python Machine Learning (2016) Sebastian Raschka.
- Deep Learning Cookbook: Practical Recipes to Get Started Quickly (2018) Douwe Osinga.
Multilingual DH
Multilingual DH is a community of practice that focuses on the application of digital humanities tools and methodologies to languages other than English. English-language examples are widely used for digital humanities pedagogy, even in contexts where not everyone works with English text. Modern English is the best-resourced language in the world in terms of the algorithms that underpin many digital humanities methodologies, from text digitization to computational text analysis. For languages that use different writing systems or have very different grammar than English, it can be challenging to apply those same methodologies. Multilingual DH develops resources and documents good practices for working with text in languages around the world.
Further information can be found at:
Network Analysis
Network analysis is the study of relations and structures (often social) by way of networks and graph theory. Network analysis is one of the more popular DH methods used in Digital History as well as literature and cultural studies and Digital Art History. Two common tools for network analysis are Gephi and Pajek.
For an example of how network analysis can be used to further historical research see Ku Klux: The Birth of the Klan During Reconstruction (2015) by Elaine Frantz Parsons. For examples of how network analysis bridges both intellectual history and literary and cultural studies see either the Six Degrees of Francis Bacon or Carolingian Networks projects.
Additional information can be found at:
- Wikipedia Social Network Analysis.
- Network Analysis Literacy: A Practical Approach to the Analysis of Networks (2016) Katharina A. Zweig.
- The SAGE Handbook of Social Network Analysis edited by John Scott and Peter Carrington.
- The Programming Historian Network Analysis Lessons.
Open Data
Open Data is data that is free for anyone to access, modify, and share. One of the most frequent forms of open data in relation to the humanities is civic data. Once downloaded, scholars can run this information through a variety of tools to produce historical, policy, environmental, etc. findings.
Further information can be found at:
Oral History
Oral history is the practice of collecting oral testimonials about individuals on either audio or video through the process of interviews. Oral history seeks to collect and preserve information that is often not found in traditional written sources such as government documents, news publications, or memoirs. Not only can oral history contribute to traditional historical research, but it can also reach a wider audience than traditional scholarly publications due to its accessible and personal nature. Oral history often aligns with Digital History and Digital Public History.
Further information about oral history can be found at:
Stylometry
Stylometry is the study of style in text, music, images, etc. It is often employed in attributing authorship to anonymous or disputed documents. An example of authorship attribution research is the unveiling of JK Rowling as the pseudonymous author of The Cuckoo’s Calling. Stylometry is occasionally used in conjunction with Digital Forensics.
Stylomety can be performed with the JGAAP tool.
Further information can be found at:
- Wikipedia Stylometry.
- The Programming Historian Introduction to stylometry with Python.
- Stylometry: A Statistical Method for Determening Authorship, Textual Intergrity, and Chronology (1988) Holly Franking.
- stylo R Package. Complete stylometry package in R, by Eder, Rybicki, & Kestemont.
Text Encoding Initiative
The Text Encoding Initiative (TEI) is a community of practice that defines a specific branch of eXtensible Markup Language (XML). A markup language is a text processing system that annotates documents in ways that are both human and machine readable. Both XML and TEI support numerous languages through Unicode. The goal of TEI is to maintain a standard for representing texts in digital form in order to further their study by scholars from a variety of fields such as literary studies, history, and linguistics. TEI is extremely useful for annotating texts and analyzing them or presenting these annotated texts in digital editions.
More information can be found in these sources:
- Text Encoding Initiative
- Digital Mitford
- What is the Text Encoding Initiative?: How to add intelligent markup to digital resources (2014) Lou Burnard.
- XML in a Nutshell: A Desktop Quick Reference (3rd Edition, 2004) Elliottee Rusty Harold and W. Scott Means.
- Learning XML: Creating Self-Describing Data (2nd Edition, 2003) Erik T. Ray.
- The Programming Historian Transforming Data for Reuse and Re-publication with XML and XSL.
Text Mining and Analytics
Text mining and analytics is the process of deriving information by way of statistical pattern learning from text. In many cases, this is a stage after digitization, although text is often born-digital. Text is formatted in a structured fashion and then a computer program derives patterns from the text, which can then in turn be evaluated and interpreted. Text analytics often relies on natural language processing (NLP), a field that explores the interactions between computers and human (natural) languages. Some examples of applied analytics processes are information retrieval from a corpus, named entity recognition, or sentiment analysis.
Additional information can be found at:
- Wikipedia Text Mining.
- Wikipedia List of text mining software.
- Text Mining with R: A Tidy Approach (2017) Julia Silge and David Robinson.
- Text Analytics with Python: A Practical Real-World Approach to Gaining Actionable Insights from your Data (2016) Dipanjan Sarkar.
- Text Mining and Analysis: Practical Methods, Examples, and Case Studies (2013) Goutam Chakraborty, Murali Pagolu, and Satish Garla.
Virtual Reality
Virtual reality, or VR, is a computer simulation that attempts to construct an imagined world, or reconstruct a physical world. Often today, VR involves putting on a headset so that a user is fully immersed in a situation. VR has additional siblings, including augmented reality (in which a real world situation is enhanced by computer-generated information) and mixed reality (in which artificial things are displayed in the real world). VR works well with 3D modeling to allow a user to experience something that they otherwise cannot experience first-hand, such as attending a theatre production of Shakespeare’s plays in a simulation of how they would have appeared when they were originally written and performed.
More information can be found at:
Web Archives
Web archiving is the act of creating an archive of information stored on the World Wide Web. Web archives frequently automatically access and download full copies of publicly accessible websites through the process of web crawling. The idea is to preserve information stored on the web for research purposes. Scholars interested in web archiving may use it for the purposes of Digital History or Cultural Analytics.
More information can b found in these sources:
- The Internet Archive.
- The Wayback Machine.
- Web Archives for Historical Research Group.
- SAGE Handbook of Web History (2018). eds. Niels Brügger and Ian Milligan.