Before you start using READ or READ Workbench
What is READ?
Research Environment for Ancient Documents (READ) is an open-source platform for manuscript and epigraphic research. You can use it for transcription, research, understanding, analysis and publishing of scholarly editions and studies.
READ offers these workflows for textual research:
- Linking between an image and a transliteration
- Documenting linguistic features like phonology, morphology, and more
- Generating a glossary and adding a translation and chāyā
- Creating outputs with multiple versions and viewing options, for example, RTF, HTML, TEI, and digital rendition
What is READ Workbench?
READ Workbench (or just Workbench) is a self-service portal that lets you use READ’s research capability either as an individual or as a team. You can use it to integrate different researchers, resources, tools, and processes for specific projects, making it easy to collaborate on textual corpora. Different projects and languages you develop in Workbench can have their own configurations and institutional branding.
Workbench can take you through an entire project workflow, from importing to editing and analysing, and all the way through to digital publication.
So what’s the difference between them?
READ is the core research platform, and Workbench is the framework that lets you bring your READ projects to fruition. READ is integrated into Workbench, so the distinction between them can be hard to pin down. Don’t worry too much about this—this training will guide you through everything step-by-step.
TextBases
READ and READ Workbench use TextBases as the main component in research projects. A TextBaseis a database based on a single text. Each TextBase can contain the following unique things, each attached to the text:
- Transliteration
- Glossary
- Translation
- Chāyā
- Paleographic report
- Structural analysis
TextBases belong to at least one research project, which you choose when you log in to READ Workbench. You can compile different TextBases into larger collection databases if you want to analyse them together or create composite research outputs.
You build and develop TextBases in READ, then manage their ownership, control, support, innovation, and standardisation in Workbench.
Substrates and strata
Within a TextBase there is a substrate and stratum.
A substrate is made of two things: a text and an image. In a substrate these are connected so that the syllables in the text and the segmented akṣaras in the image are aligned.
The user who builds the substrate maintains ownership of the whole TextBase. Only they can make edits to the substrate.
A stratum (plural: strata) is a layer of analysis that is built on a substrate. You can have multiple strata on a single substrate. A glossary is an example of a stratum. Strata are constrained by the relationship between syllables and segments in their substrate, which ensures that they are always valid and relevant.
The owner of a TextBase can share strata access with other users to let them add their own strata or do their own analysis on existing strata.
Texts vs Editions
So far, we’ve been talking about texts as the main component that TextBases are built on. As you might have gathered, a text is physical writing or inscription on an object. Texts can have missing spans caused by damage to the object, or parts that are uncertain or unclear. Every text is unique.
An edition is a transliterated reading of a text. It includes diplomatic, reconstructed, and hybrid versions.
In a TextBase, an edition is the object of:
- Glossary
- Translation
- Chāyā
- Structural analysis
Multiple editions can be built for a single text, with each one including the particular readings and reconstructions developed by that edition’s editor. Through a process of cubing you can create multiple editions for one text: multiple substrates in a single TextBase. Each substrate is then independently available for the development of analysis stratum.
Now you know all you need to know about working with READ and Workbench, you can get started.