The project plan for a digital project is a foundational document that describes the rationale, goals, overall timeline, necessary resources, terms and conditions, and outcomes of the DH project. Then planning process should be intensive, collaborative and requires substantial input from everyone on the project team. Team members should be in agreement on such crucial questions as scope, technical design, infrastructural needs, and success criteria.
Here is a project plan template to guide you with a basic DH project:
Also important is planning for and managing your research data. Make use of the University's DMPOnline and read more about research data management on our guide.
Most digital projects rely on the synthesis, analysis, and visualization of data. This data can come from text, surveys, and can even be crowd sourced from the general public. Once this data has been gathered, it will need to be properly cleaned and organised to be efficiently used. Here are some more tools that will allow you to easily work with collections of data.
Wordpress.com is most associated with web publishing. There are a few web publishing platforms that are free to use, but you might incur costs when trying to expand or develop. The University provides access to Omeka S, a web publishing platform designed with DH in mind, for free. It is highly versatile and can be extended for crowd sourcing, basic mapping, timelines and other functionality.
Here are some other tools to consider:
Text analysis methods include concordances (the arrangement of w words within a text that allow you to find its frequency, and where), topic modelling (which identifies the recurring theme of texts based on computational linguistics and common words), and stylometry (the statistical analysis of writing style that is useful in research such as authorship studies). Before you can apply textual analysis methods you must assemble and clean your corpus. This is the most laborious part of a text analysis project as you may need to find machine-readable copies of your materials, make them machine-readable through optical character recognition (OCR), remove formatting and tags, and clean up mistakes from OCR.
Here are some text finding tools:
Here are some tools for cleaning up your text:
The University provides access to Adobe Pro for OCR capabilities. Contact ICT Services to request Adobe Pro.
Here are some text analysis tools:
The UFS Library and Information Services' Makerspaces provides workshops on various aspects of content creation, including podcasts. Other support and resources are available in the Sasol Library, including a podcast studio (
).
Take a look at some other tools for podcasting:
Read more about oral history methods:
Recording Oral History by See our copyright and licensing guide to learn more about fair use, licensing, public domain, and more.