READ Workbench is a self-service portal which supports the integration and management of researchers, resources, tools and processes in the collaborative development of textual corpora.
Workbench delivers READ philological research capability, configured for individual projects, as ‘software as a service’.
Workbench three facets – configuration services, self-service portal, and corpus development workflows – provide a scalable implementation framework.
- Configuration services support the provision and management of multiple READ installations; each with project and language-specific configurations and institutional branding.
- Self-service portal features enable researchers to establish and manage their projects without technical support. Comprehensive sharing capability supports flexible collaboration for editing, analysis, and review.
- Corpus development workflows support researchers through the entire project arc of importing, editing, analysing and digitally publishing research outputs. Workbench instantiates a corpus development methodology, TextBase, to address scalability, project management and sustainability in collaborative projects.
The TextBase methodology – text alignment, text cubing, strata management and text aggregation – maps READ features into a comprehensive suite of iterative corpus development workflows.
The adoption of the TextBase, a single text database, as the fundamental object of development, collaboration and portability is quite a departure from a conventional corpus model where a centralized administrator manages a monolithic database. The TextBase model was designed as a solution architecture within which to address some of the ubiquitous issues with a conventional approach; confidentiality, ownership, control, support, innovation and standardization.
The TextBase methodology, encapsulated by READ Workbench, supports a re-framing of research collaboration in the philological domain.
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Developed by Prakaś Foundation, READ Workbench was has been hosted at the University of Sydney since 2016 and supports a range of multi-institutional corpus development collaborations across multiple languages.