METADATA AND DIGITAL EXHIBITIONS, ARCHIVES, AND DATABASES
Omeka digital exhibition platform https://omeka.org/
Omeka Showcase displaying examples of projects using Omeka: https://omeka.org/classic/showcase/
General Metadata Resources
The Digital Curation Centre in Britain’s very helpful list of current metadata standards covering many different fields: http://www.dcc.ac.uk/resources/metadata-standards/list.
Oral History for Metadata Synchronizer http://www.oralhistoryonline.org/.
QR Code Generator https://www.qr-code-generator.com
American Museum of Natural History. “Anthropology Thesaurus”. https://www.amnh.org/our-research/anthropology/collections/thesaurus.
The Getty Research Institute. “Getty Vocabularies”. http://www.getty.edu/research/tools/vocabularies/.
Museum of Applied Arts and Sciences. “Object Name Thesaurus”. https://maas.museum/research/object-name-thesaurus/.
Victoria and Albert Museum . “Chinese Iconography Thesaurus (CIT)”. https://www.vam.ac.uk/research/projects/chinese-iconography-thesaurus-cit.
TEXT ENCODING AND MUSIC ENCODING (TEI AND MEI)
Text Encoding Initiative, https://tei-c.org/.
Teach Yourself TEI https://tei-c.org/Support/Learn/
TEI By Example. https://teibyexample.org/
University of Illinois at Urbana-Champaign. “An Introduction to XML and the Text Encoding Initiative”. Accessed May 16, 2019. https://guides.library.illinois.edu/xml/oxygen
University of Nebraska Center for Digital Research in the Humanities. “What is TEI?”. Accessed May 16, 2019, https://cdrh.unl.edu/articles/basicguide/TEI.
“Stylesheets”, TEI. https://tei-c.org/tools/stylesheets/.
Music Encoding Initiative, https://music-encoding.org/.
Tools for telling stories with maps: all of the following are user-friendly plug-and-play desktop or online mapping tools which work very well for the classroom environment as well as individual digital humanities initiatives:
MyMaps, Google. http://mymaps.google.com.
Knight Lab. “StoryMap”. https://storymap.knightlab.com/.
ArcGIS StoryMaps https://storymaps.arcgis.com/en/app-list/.
MapStory Foundation. “MapStory”. https://mapstory.org/getstarted.
Odyssey, CartoDB. https://cartodb.github.io/odyssey.js/.
MapScholar. Edelson, S. Max, and Bill Ferster. https://drive.google.com/file/d/0B7rqU3alkXgjczRBWG9DY3dJdmM/view.
General Mapping Resources:
Levin, John, “Mapping Resources”, Anterotesis (blog). http://anterotesis.com/wordpress/mapping-resources/dh-gis-projects/.
Harvard University. “Harvard WorldMap”. http://worldmap.harvard.edu/.
Tools for making heat maps showing the density of geographic data:
Open Heatmap (http://www.openheatmap.com/)
Warden, Pete, “How OpenHeatMap can Help Journalists”, YouTube video, 4:09, posted by “Pete Warden”, July 24, 2010, https://www.youtube.com/watch?v=vxnxe9T7mMw.
Heat Mapper (http://heatmapper.ca)
ESRI’s ArcGIS is the gold standard for digital mapping, and the following is a very useful set of teaching resources which they provide:
COMPUTATIONAL TEXT ANALYSIS
Voyant Tools (http://voyant-tools.org) , created by Stéfan Sinclair and Geoffrey Rockwell, is a set of tools designed to help digital humanities students and researchers to engage in large-scale textual analysis on the web. You can upload your own corpus or experiment with the Jane Austen corpus provided to test out text analysis and data visualization.
Google Books Ngram Viewer (https://books.google.com/ngrams) is Google’s tool which allows you to trace word usage over time in a variety of corpora held within Google Books. Corpora include American English, British English, English (from anywhere in the world including the USA and the UK), Chinese, French, German, Hebrew, Italian, Spanish, and Russian texts. You can tell Google’s Ngram Viewer the timespan which you wish to search across, and enter a word or phrase to see how and when that phrase occurred during that time span in particular corpora.
Paper Machines (http://papermachines.org/) is a plugin for the bibliographic software Zotero designed by Jo Guldi and Cora Johnson-Roberson which enables humanities researchers to generate topic models from their bibliographic datasets without needing extensive computational knowledge or resources. You can work with your Zotero library to engage in text analysis and visualization.
Introductions to Coding and Text Mining
Julia Silge and David Robinson, Text Mining with R: a Tidy Approach (2014) https://www.tidytextmining.com/ .
Garrett Grolemund and Hadley Wickham, R for Data Science (2017) https://r4ds.had.co.nz/ .
Matthew L. Jockers, Text Analysis with R for Students of Literature (New York, NY: Springer, 2014).
Taylor Arnold and Lauren Tilton, Humanities Data in R: Exploring Networks, Geospatial Data, Images, and Text (New York, NY: Springer, 2015).
Mauricio Vargas Sepulveda and Jodie Burchell, The Hitchhiker’s Guide to GGPlot2 (2018). Check out this resource if you want to generate graphs as part of your big data analysis.
Stanford CoreNLP (https://stanfordnlp.github.io/CoreNLP/) offers a set of tools which people with experience with programming can use to parse words, names, parts of speech, locations, and various other entities within a textual corpus.
Shawn Graham, Scott Weingart, and Ian Mulligan, “Getting Started with Topic Modeling and Mallet”, UWSpace http://hdl.handle.net/10012/11751 is an invaluable resource providing an introduction to using Mallet to engage in topic modeling.
Project Gutenberg is the world’s oldest digital library, currently offering over 58,000 full-text books free of charge to anyone with a web connection.
JSTOR’s Data for Research (DfR) (https://www.jstor.org/dfr/) is JSTOR’s way of providing access to large datasets of critical articles held within its digital archives which can be used for computational analysis.
The Hansard Corpus (http://www.hansard-corpus.org) holds transcripts of nearly every speech given in the British Parliament from 1803 to 2005.
Chronicling America (https://chroniclingamerica.loc.gov/ocr/) enables you to download, en mass, text from the Library of Congress’ digitized collections of historical American newspapers dating from 1836 to 1922.
Early English Books Online Text Creation Partnership (EEBO-TCP, https://www.textcreationpartnership.org/tcp-eebo/) provides fully searchable, accurate SGML/XML-encoded texts of books held within the Early English Books Online database. Early English Books Online includes over 125,000 volumes of texts published between 1475 and 1700.