Technical Overview

Team

Organisation: King's Digital Lab
Site: https://kdl.kcl.ac.uk
Email: kdl-info [at] kcl.ac.uk
Twitter: @kingsdigitallab
GitHub: https://github.com/kingsdigitallab
Location: London WC2B 5LE, United Kingdom

Research Software Analyst: Arianna Ciula
Site: https://www.kdl.kcl.ac.uk/who-we-are/arianna-ciula/

Research Software UI/UX Designer: Ginestra Ferraro
Site: https://www.kdl.kcl.ac.uk/who-we-are/ginestra-ferraro/

Research Software Engineer: Miguel Vieira
Site: https://www.kdl.kcl.ac.uk/who-we-are/miguel-vieira/

Technologies and Processes

Development

For more information see development and development with docker.

Data model

The Radical Translations project data model is based on BIBFRAME, for Resources (Works, Instances, Items are flattened under one object type) and Events, and based on FOAF for Agents (Persons, Organisations).

Django models

Django models

The data model graph was generated with the django-extensions graph_models command:

$ fab django "graph_models -X TimeStampedModel,PolymorphicModel -o models.png agents core events utils"

Conceptual model frameworks:

  • BIBFRAME to model objects and relationships for bibliographic resources (the instances for paratexts are resources labelled as paratexts and part_of other resources)

  • BIBFRAME uses FOAF for its Agent class to model relationships between agents, persons, organisations and other objects.

Controlled terms

The vocabularies, data points and taxonomies, used by Radical Translations data model:

  • FAST used for genres (subjects): this is part of the Library of Congress Linked Open Data resources mapped as FAST topics/forms

  • Additional terms for subjects (with respect to types of publications and genres) use terms from the RBMS controlled vocabularies (in particular the RBMS printing and publishing and RBMS genre vocabularies)

  • Wikidata for the professions (roles) of persons e.g. authors and translators as well as types of organisations e.g. political parties vs publishers; Wikidata terms are also used to express editorial classification e.g. of dates (e.g. inferred), events (typology) and relationships (e.g. uncertain attribution)

  • VIAF to identify some of the agents (persons) who are well known translators/authors

  • ISO code for languages

  • GeoNames for geocoded placenames

  • Extended Date/Time Format (EDTF) Specification to express dates

  • In one case controlled terms are based on project-specific terms; this is the case for ‘classification scheme edition’ for the Resources objects (in particular paratexts) with values partially adapted from Kathryn Batchelor, Translation and Paratexts (Roudledge 2018); Amy Nottingham-Martin,”Thresholds of Transmedia Storytelling” in Examining Paratextual Theory and Its Applications in Digital Culture, ed. Nadine Desrochers and Daniel Apollon, (IGI Global 2014), 287-307.

Workflows

TODO: data processing & editorial workflows

Architecture

TODO: Extract high level description from PQ

Local Docker stack

Local Docker Stack

Production Docker stack

Production Docker Stack

The graphs were generated by the docker-compose-viz tool:

$ docker run --rm -it --name dcv -v $(pwd):/input pmsipilot/docker-compose-viz render -m image local.yml

Design process

TODO: describe design process