Use Cases
Use Cases for Digital Research Infrastructure
Exemplary use cases, as developed by the DISKAH Fellows, demonstrate how data and compute intensive research relies on various Digital Research Infrastructure components. Their user journey roles reveal how researchers navigate through roles, workflows, and requirements across the DRI landscape.
Use Journey roles
The user journey roles of the DISKAH Fellows illustrate how, through data and compute intensive workflows, researchers and practitioners engage with the various components of Digital Research Infrastructure (DRI). These include networks, skills development through training and technical support, as well as access to data (e.g. Data services) and compute infrastructures (e.g. High Performance Computing systems). Such components are essential in supporting researchers to perform processes related to managing, curating, and analysing big complex datasets.
The exemplary use cases and associated user journey roles essentially demonstrate how researchers and practitioners iteratively move through different roles as part of their workflow development, while also highlighting different access needs across DRI, depending on tasks and varying levels of digital skills.
Identified roles
Research Framer: Frames the research focus and shapes a workflow, defining the use of different DRI components. This is often the first role undertaken by a researcher or practitioner.
Source Explorer / Corpus Builder: Identifies sources of data and gathers relevant materials to build a corpus for analysis.
Data Generator: Generates data through digitisation, by deploying born digital data or simulations to build the required dataset for the research.
Data Shaper: Prepares the dataset by cleaning, transforming and structuring it so that it is ready for analysis.
AI / Compute Developer: Develops computational tools and methods to run effective data analyses in DRI compute.
Computational Critical Interpreter: Deploys already existing computational tools and methods to analyse datasets and interpret findings.
Scholarly Communicator: Disseminates research and practice findings through various formats and channels, such as publishing datasets and workflows, producing academic publications and disseminating research through outreach activities.
