Data Analytics in Digital Humanities
Editor: Dr. Shalin Hai-Jew, Kansas State University, haijes@gmail.com (and 1-785-532-5262)
Publisher: Springer Science + Business Media
Theme: Of late, the “digital humanities” have come to the fore with researchers, academics, and students using digital means to advance their humanities work. These efforts include endeavors to:
- annotate, present, and share raw data and digitized artifacts and processed information through Web-facing digital archives and databases;
- model human experiences digitally through virtual spaces and games;
- collect and analyze data from heterogeneous sources;
- code data;
- query the data and information (manually and computationally);
- extract models;
- pose questions;
- challenge cultural and historical understandings;
- reconfigure current constructs / challenge power and privilege, and
- broaden ways to knowing and being.
This text will focus on a range of technology tools and methods used for research and data analytics in the digital humanities, with particular focuses on local domain-specific applied theories, techniques, and approaches, as well as more global methods.
Book audience: Researchers, academics, practitioners, and students in higher education
Chapters: Research papers, meta-analyses, case studies, technology-based tutorials, and concept papers
About imagery: Please note that Springer has strict limits on the amount of imagery that may be included, with a maximum of 1-2 per paper.
Manuscript preparation details: https://www.springer.com/gp/authors-editors/book-authors-editors/manuscriptpreparation/5636
A Tentative Table of Contents (TOC)
- Exploratory research in the digital humanities
- Principles
- Theories
- Theoretical and practical approaches
- “Best practices”
- Standards
- Structuring questions and approaches
- Research technologies and the digital humanities
- Mobile devices
- Applications
- Multimedia equipment (for data capture and sharing)
- Sensors
- Social platforms
- Augmented spaces
- WWW and Internet
- Search engines, browser add-ons
- Data sources
- XML tagging tools
- Network graphing tools
- Mapping tools
- Machine-based authoring tools
- Open-source tools (such as those on the Dirt Directory) / proprietary tools
- Game design tools
- (Raw) data types (and data representations)
- Metadata
- Trace data / log data
- Content data
- Multimedia
- Text corpuses (and marginalia)
- Coding annotations and markups
- Gray literature
- JSON
- XML
- Other types
- (Processed) data types
- Profiles
- Collections
- Data structures
- Image sets
- Video sets
- Games
- Simulations
- Data preparation standards and practices
- Digitization of analog sources (transcoding)
- Born-digital contents
- Tagging (of text and multimedia)
- XML tagging for machine-based research and visualizations
- Data curation
- Data provenance
- Data indexing
- Data archival and preservation (and data inheritance and re-use)
- Research technologies and related methods of knowledge creation in the digital humanities
- Data management tools
- Data interfaces
- Data dashboards
- Digital content analysis (coding, encoding, decoding, recoding)
- Text analysis
- Stylometry
- Author identification / attribution
- Text mining
- Machine (distant) reading / text summarization
- Image analysis
- Visual semiotics
- Visual rhetoric
- Image mining
- Multimedia analysis (of videos, of simulations, of games, and others)
- Video mining
- Game studies
- Text analysis
- Network analysis (social networks, content networks)
- Geospatiality and geographical mapping (digital cartography)
- 3D reconstruction
- GIS applications
- Sensor research
- Autocoding (unsupervised, semi-supervised, and supervised machine learning)
- Data-related modeling
- Machine learning
- Mass - macro (and / or micro) crowd-sourced; communal (communities of practice, research teams)
- Direct research practices in the digital humanities
- Transmedia studies
- Culturomics
- Computational linguistics, and others
- Online surveys, panels, focus groups, e-Delphi studies
- Crowdsourcing
- Social activism and digital humanities research
- Data capture and datafication
- Data scraping the WWW and Internet
- Social media platforms (and resulting data types, JSON, XML, and others…and their uses)
- Microblogging sites
- Online crowd-sourced encyclopedias
- Online social networking (OSNs)
- Survey sites
- Image-sharing sites
- Audio-sharing (old-school podcast) sites
- Video-sharing sites
- Tagging sites
- http (Web) networks, and others
- Socio-technical systems
- Exploratory big data and the digital humanities
- Data sets acquisition and management
- Data streams
- Technologies and related methods
- Applications
- Digital collections, galleries, libraries, and repositories
- Web 3.0 publishing and sharing sites
- Presentation software for online collections
- Data representations and displays
- Data visualizations
- Graphs
- Maps
- Motion-based visualizations
- Interactive data representations, and others
- Data ethics in the digital humanities
- Humanistic values in data analytics in the digital humanities
- Data verification / validation / forensics in the digital humanities
- Real-world cases
- Knowledge creation and outputs in the digital humanities
- Methods for challenging and countering exploratory research assertions in the digital humanities
* The above is only a suggested potential TOC. Other topics are welcome.
Deadlines:
- Feb. 29, 2016 Submission of chapter proposals (200 - 500 words) via email
- March 15, 2016 Submission of full draft chapter (10-30 pp. single-spaced, maximum 2 images / figures / tables)
- March 31, 2016 Return of feedback from double-blind peer reviews (2 minimum); decision notification
- April 30, 2016 Revised chapters due (with brief summary of changes); related images due
- May 15, 2016 Final notification of acceptance
- June 15, 2016 Final submittal of chapter, related images, contracts, and other related elements
- Note: Publication is slated for some time after August 2016.
Note: Please feel free to share this Call for Chapters broadly.
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