The second part of the introduction to the Data Stewardship Wizard (DSW) is primarily intended for data stewards, service administrators, and other users who want to better understand how DSW works “under the hood.” It is also relevant for those considering customizing content, creating templates, or deploying DSW at the institutional level.
The Data Stewardship Wizard is not just a tool for completing a questionnaire, but a comprehensive system built on several interconnected layers. Key components include knowledge models, the questionnaire, and document templates.
The knowledge model is the core building block of DSW. It defines what the tool asks, what types of answers it offers, and how individual questions are connected.
It can be understood as a template for a structured questionnaire, organised in a tree-like structure. It includes chapters, questions, possible answers, and follow-up questions that are displayed based on selected responses.
The knowledge model can also include additional information, such as:
As a result, the knowledge model not only collects information but also serves as a tool for guiding users and sharing know-how. The questions within the knowledge model come in different types, depending on the kind of information required. They can be used to enter specific values, such as text, numbers, or URLs (often with input validation), or to select from predefined options. These selection-based questions enable questionnaire branching, ensuring that users only see relevant sections.
In cases where multiple similar entities need to be described, such as several datasets within a project, item lists can be used to repeatedly fill in the same set of questions. Another useful feature is integration questions, which allow connections to external services or databases. This enables users to select specific records directly from these sources, with responses containing not only text but also identifiers or links, thereby supporting FAIR principles.
Additional question types support multiple selections, linking between completed items, or file uploads. This combination makes it possible to create questionnaires that are both structured and flexible, adapting to the specific needs of a project.
“Another major advantage is the ability to customise existing knowledge models or create new ones tailored to the needs of an institution or a specific project. I also focus on document templates for different funding organisations. These make it easy to generate clear and well-structured documents that meet specific funder requirements, which significantly simplifies my work.”
Georgia Koutentaki
The questionnaire is a specific instance of the knowledge model that the user completes within their project.
Unlike traditional forms, it has several distinctive features:
These metrics are calculated as a weighted average based on the responses and can serve as an indicative measure of how well data management is set up within the project.
The result of a completed questionnaire can be a document, typically a Data Management Plan.
The structure of this document is defined by templates, which determine how individual responses are transformed into the final text and in what format the document is generated. Creating custom templates requires a certain level of technical knowledge. Templates are composed of a combination of JSON metadata, mapping logic (primarily using the widely adopted templating language Jinja2), and additional supporting files.
To support their development, the DSW Template Development Kit (TDK) is available, making it easier to create and test output documents.
The Data Stewardship Wizard can be deployed in different ways depending on institutional needs, governance requirements, and available resources.
In the Czech environment, the key solution is the deployment of DSW within the National Repository Platform (NRP). This is a centrally managed instance designed for the entire platform, using e-infra login for authentication, providing a unified environment for researchers, and tailored to the needs of the NRP infrastructure. The instance is currently in pilot operation and represents the recommended way of using DSW in the Czech Republic.
DSW is also operated within the ELIXIR infrastructure, which connects services for biological and life sciences across Europe.
Two main options are available:
It allows immediate use without the need for maintenance, but provides only a standard environment with limited possibilities for customisation.
A dedicated instance can be set up for individual institutions, offering full customisation, including custom knowledge models and templates. These instances are funded by ELIXIR-CZ, which comes with certain limitations, such as the absence of a guaranteed SLA or dedicated support.
DSW is an open-source tool that can also be deployed within an institution’s own infrastructure, such as on-premises or in an institutional cloud.
This option provides:
However, it also requires managing the operation independently, including installation, updates, monitoring, and backups.
For organisations that require guaranteed operation and support, a commercial version called FAIR Wizard is available.
It offers an extended version of DSW in a Software-as-a-Service model, including:
This option is particularly suitable for institutions and companies with higher requirements for stability and support.
For a more detailed understanding of how DSW works, including knowledge models and templates, the official documentation is available.
Matthias Täschner first got into programming through computer games, spent twelve years in the army, and now works as a data scientist at Leipzig University. In this interview, he shares why data science isn’t about turning everyone into programmers, how to spark interest in AI, and what to expect from his course at the EOSC Summer School for data stewards.
Planning how to manage research data does not have to mean writing long documents based on rigid guidelines and templates. Data Stewardship Wizard is an online tool that guides you through the entire research data management process, step by step and in a clear, user-friendly way, without unnecessary administrative burden.
