This book addresses the need of humanities scholars for whom technology and data now play a large role in their research and teaching and who need deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The first part in the book provides some basic grounding and orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. A Keywords chapter also explains specific terms and concepts in the digital humanities context. The second part addresses a range of topics including data modeling standards and the role they play in shaping digital humanities practice; traditional forms of modeling in the humanities and how they have been transformed by digital approaches; ontologies which seek to anchor meaning in digital humanities resources; and how data models inhabit the other analytical tools used in digital humanities research. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.
Preface (Julia Flanders and Fotis Jannidis) 1. Data Modeling in a Digital Humanities Context (Julia Flanders and Fotis Jannidis) 2. A Gentle Introduction to Data Modeling (Fotis Jannidis and Julia Flanders) 3. Complex Ways of Information Structuring: Benefits and Problems (Piotr Banski and Andreas Witt) 4. How Modeling Standards Evolve: The Case of TEI (Lou Burnard) 5. The Shape of Data in Digital Humanities: Ontologies and Data Modeling (Øyvind Eide and Christian-Emil Ore) 6. Modeling Space in Historical Texts (Ian Gregory, Chris Donaldson, Andrew Hardie, and Paul Rayson) 7. Modeling the Actual, Simulating the Possible (Willard McCarty) 8. Visualizing Information (Isabel Meirelles) 9. How Subjective is Your Model? (Elena Pierazzo) 10. Constraint (Wendell Piez) 12. Where Semantics Lies (Stephen Ramsay) 13. Modeling Time (Benjamin M. Schmidt) 14. Playing for Keeps: The Role of Modeling in the Humanities (C.M. Sperberg-McQueen) 15. Aspects of Linguistic and Computational Modeling in Language Science (Elke Teich and Peter Fankhauser) 16. Algorithmic Modeling; Or, Modeling Data We Do not yet Understand (Ted Underwood) 17. Keywords and Glossary (Julia Flanders and Fotis Jannidis)
Digital technologies are increasingly important to arts and humanities research, expanding the horizons of research methods in all aspects of data capture, investigation, analysis, modelling, presentation and dissemination. This series, one of the first and most highly regarded in the field, covers a wide range of disciplines and provides an authoritative reflection of the 'state of the art' in the application of computing and technology. The titles in this peer-reviewed series are critical reading not just for experts in digital humanities and technology issues, but for all scholars working in arts and humanities who need to understand the issues around digital research.