A common data environment for research projects.
RIM brings order to scattered spreadsheets, technical notes and files by offering a single source of truth — guided by the FAIR data principles.
Introduction
The Research Information Model (RIM) is intended to form a common data environment (CDE) for research projects. The database is being assembled guided by the FAIR data principles — it strives to make material data Findable, Accessible, Interoperable and Reusable. A well-designed CDE brings order to scattered spreadsheets, technical notes and files by offering a single source of truth that everybody can trust.
The name Research Information Model (RIM) is chosen by analogy with Building Information Modelling (BIM), a key digital technology in the civil engineering and construction industry. BIM combines an asset model with structured, machine-readable information (materials, quantities, specifications and schedules) so that many stakeholders can work from a shared and continuously updated source of truth.
In practice, BIM delivers value mainly through coordinated information management: it reduces fragmented documentation by keeping project data in one place, enforces consistent data structures and terminology, and improves collaboration by enabling early detection of inconsistencies and better-informed decisions across the whole asset lifecycle.
RIM applies the same philosophy to research projects. Instead of modelling a building, it models the research 'asset' — geometry, materials, production methods, experiments, datasets, documents and their provenance — inside a common data environment. By standardising how these artefacts are described and linked, RIM supports reproducibility and reuse and aligns day-to-day research data handling with the FAIR principles.
To achieve this, RIM bridges design authoring and cloud collaboration. In Grasshopper (GH), users create, query and validate database entries next to their parametric models, enabling a design-driven unified workflow. Combined with cloud functionality similarly to the services such as Nextcloud for synchronised storage, sharing and access control, RIM keeps structured records and supporting files available to the whole team.
Three pillars
The message below summarises why centralising, standardising and collaborating on data is so important:
Centralisation / 01
Keeps all relevant information in one reliable location. A single repository improves efficiency because large datasets are easier to find, reduces inconsistencies by eliminating duplicate copies, and ensures real-time accessibility for dynamic projects. No more hunting through e-mails or local folders — everything lives together.
Standardisation / 02
Harmonises how data is stored and formatted. When data follow clear structures and use consistent units and terminology, different software tools can exchange information seamlessly. Quality improves because validation checks catch errors and missing values before they propagate downstream. Standardised data also makes it simpler for machines (AI systems) and humans to interpret the information.
Collaboration / 03
Flourishes when everyone works on the same platform. User-friendly interfaces invite people from different backgrounds — engineers, materials scientists, architects — to contribute their expertise. Sharing enriches the data, sparks innovation and helps teams achieve better outcomes. Access to a wide range of perspectives encourages creativity and problem solving.
Developing the RIM database is simultaneously the development of its semantic model — a shared, machine-readable vocabulary and set of relationships that gives research assets and their metadata unambiguous meaning. RIM functions as a semantic layer that captures the meaning, relationships, and constraints of research artifacts across geometry, materials, production, and evaluation, enabling consistent interpretation across tools and projects.