Awesome AEC in NFDI4ING is a curated collection of research data management resources for researchers, infrastructure providers, and organisations in the engineering sciences, with a specific focus on architecture, engineering, and construction. The collection builds on the idea of the awesome-RDM collection by UB Mannheim and extends it with resources relevant to NFDI4ING and the AEC research community.
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Research data management (RDM) comprises the planning, documentation, storage, publication, archiving, and reuse of research data across the data lifecycle. Its aim is to keep data accessible, reusable, verifiable, and understandable beyond individual persons or projects. Good RDM reduces the risk of data loss, avoids duplicate work, supports review and funding requirements, and enables future reuse. It also requires attention to legal, ethical, copyright, and data protection issues. A useful guiding principle is: as open as possible, as closed as necessary.
More Info: RDM at forschungsdaten.info (DE)
The engineering sciences constitute a highly heterogeneous research landscape, spanning architecture and civil engineering to mechanical, electrical, process, and systems engineering. Each field has its own research cultures, methods, artefacts, tools, and objects of study. As a result, requirements and challenges in research data management differ considerably across engineering disciplines and even between individual projects.
NFDI4ING addresses this diversity through a method-driven approach based on archetype personas. These archetypes describe recurring research practices and provide a way to approach RDM from the perspective of concrete methods, workflows, and data practices rather than from disciplinary labels alone.
More Info: NFDI4ING Archetypes
Research data management in architecture, engineering, and construction addresses the specific ways in which research on the built environment works with data, documentation, models, software, and sources. AEC research often combines heterogeneous materials, including drawings, digital models, simulations, images, 3D objects, measurements, textual sources, software, and contextual metadata.
RDM in this field, therefore, goes beyond the storage of files. It supports the transformation of diverse research artefacts into well-described, traceable, and reusable data resources. This includes metadata, controlled vocabularies, open formats, repositories, long-term archiving, publication services, and FAIR principles.
Because AEC research sits at the intersection of design, engineering, construction practice, cultural knowledge, and digital methods, RDM needs to remain sensitive to disciplinary workflows while enabling data to be found, understood, connected, and reused across projects, tools, and communities.
Check out the NFDI podcast - For a FAIR Data Future: Datenmanagement in der gebauten Umwelt
The Research Data Management Organiser (RDMO) helps you figure that out. It is a web-based tool that guides you through common questions to consider, especially during the planning phase of a project.
With RDMO, you can create data management plans based on project questionnaires, including templates for engineering-specific research. Grab a chocolate — it might be a bit dry — but working through the questions is a good way to understand what research data management means for your own project.
Also, check your local RDM-Guidelines
Local and cloud-based file storage are often the first places where research data is collected. But once data needs to be organised, documented, shared, and enriched with metadata, we recommend using Coscine.
Coscine is a research data platform for secure storage, sharing, and metadata-based documentation. It is available to researchers within NFDI4ING. You will need to apply for storage space, but once your project is set up, you can upload your data and describe it with structured metadata.
Coscine provides a wide range of existing metadata forms based on application profiles, which can be reused and extended for your specific case. Don’t hesitate to get in touch with us if you need help choosing or adapting a profile.
The NFDI4ING Jupyter Service provides a hosted JupyterLab environment that runs directly in the browser. It allows you to create, run, and document computational notebooks without having to set up everything locally.
This is especially useful for interactive data analysis, teaching, reproducible workflows, and small research scripts. You can combine code, explanations, visualisations, and results in one place, making your computational work easier to understand and reuse.
The NFDI4ING Data Ingest Service supports the upload, documentation, and publication of research data from civil engineering, architecture, urbanism, and related fields.
It helps you prepare data for sharing by adding metadata, organising files, and making research outputs more reusable. Depending on the use case, it can also support publication workflows in which datasets receive persistent identifiers, making them easier to cite.
Many useful tools, standards, and initiatives already exist in the AEC community, but they are often spread across different platforms, projects, and disciplines.
Our Open Source AEC Initiatives collection brings together relevant resources for research in architecture, engineering, construction, urbanism, and the built environment. It is a starting point for discovering tools, workflows, data formats, and community projects that may be useful for your own research.
The list is not meant to be complete, but to help researchers find existing approaches before starting from scratch.
LiaScript: Open-courSe: Datenlebenszyklus
RDM in AEC makes data findable, auditable, interoperable, and reusable, enabling reproducible workflows and unlocking analytics and AI. This reduces rework and delays, preserves institutional knowledge, and protects value while mitigating risk.
- The NFDI4ING Research Data Management Organiser (RDMO) is a web-based research data management organiser for creating and managing data management plans and project questionnaires for engineering research.
A good first step in research data management is to check the RDM guidelines and support services at your own institution. Many universities provide local recommendations, templates, contact points, training materials, and information on storage, documentation, legal aspects, publication, and long-term archiving. These local services are often the most relevant entry point because they align with institutional policies, available infrastructure, and funder requirements. The examples below collect RDM information pages from several German universities and research institutions:
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Carl von Ossietzky Universität Oldenburg Research data management
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Friedrich-Alexander-Universität Research data and research data management
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Ostfalia University of Applied Sciences Research Data Management
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Technische Universität Berlin Service Center Research Data Management
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Ludwig Maximilian University of Munich Research Data Management
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Karlsruhe Institute of Technology (KIT) Research Data Management
- The NFDI4ING Data Search Index is a central point of access for searching research data across numerous distributed repositories. The search tool is freely available and offers both a graphical user interface and an open API for searching and querying metadata.
- The NFDI4ING Data Collections Explorer is a searchable portal for engineering research datasets and repositories.
- re3data is a global registry of research data repositories.
Also, check the section on data repositories
- NFDI4ING Research Software Finder is a discovery platform for (research) software across Research Software Directory and GitHub
- Also, check the Open Source AEC Initiatives, as many of them provide collections of AEC-specific open source software and tools
- The NFDI4ING Metadata Profile Service is a web service for creating, hosting, and sharing standardised metadata profiles and schemas to ensure FAIR engineering research data.
Create, curate, and share engineering metadata profiles. - Coscine is RWTH Aachen's research data platform for secure storage, sharing, and collaborative scientific computing.
Store, manage, and share research data. - The NFDI4ING Jupyter Service is a hosted JupyterLab environment offering browser‑based computational notebooks with preconfigured environments for interactive data analysis, teaching, and reproducible engineering workflows.
Create, run, and document computational research notebooks. - eLabFTW, an electronic lab notebook manager for research teams
Store research experiments and share them with your research team. - SciMesh and SciMesh for RO-Crate - a community-driven platform for packaging, discovering, and reusing scientific software, workflows, and metadata to support reproducible research
- SciKGTeX - a LaTeX package designed to semantically annotate research contributions in scientific documents Embed machine-readable research metadata into scientific publications.
- NFDI4ING HOMER (HPMC tool for Ontology‑based Metadata Extraction and Re‑use) is an open‑source GitLab project that implements a crawler for extracting metadata using ontologies and preparing it for reuse in NFDI4Ing services.
Automatically extract ontology-based metadata from research data files. - The NFDI4ING Field Database Platform is a structured management and discovery platform for sensor‑based field experiment data that enables previewing, contextual metadata exploration, and evaluation before accessing large raw datasets.
Enable discovery and reuse of field experiment datasets. - Kadi4Mat is a generic open‑source virtual research environment for managing, sharing, and analysing research data and electronic lab notebooks.
Manage, analyse, visualise, and share research data.
- NFDI4ING Knowledge Graph Explorer (KGE) is based on RDF-Store, an open‑source software providing an RDF triple store and SPARQL endpoint that supports loading SHACL shapes locally or remotely from the NFDI4Ing Metadata Profile Service
- Architectural RDM-Pipeline is a web-based workflow environment under development that supports researchers in structuring, mapping, validating, visualising, and publishing architectural research data as reusable FAIR data.
A data repository is a platform or service for storing, describing, preserving, and publishing research data so that it can be found, accessed, cited, and reused over time.
Domain-specific repositories should usually be checked first, because they are more likely to support disciplinary metadata, file formats, community standards, and reuse contexts.
Examples:
- NFDI4ING ING.EST is a gateway for enhanced research data publication in AEC, using format‑aware profiling and automation to visualise 2D/3D data, assign persistent identifiers, and ensure easy long‑term archiving.
- RADAR4Culture is a free service for the sustainable publication and preservation of cultural studies research data—across any data types or formats—in accordance with FAIR principles.
Generic repositories are broad, cross-disciplinary publication platforms that allow researchers to publish, preserve, and share datasets, software, publications, and other research outputs when no suitable domain-specific repository is available.
- Zendodo is a general-purpose open research repository for datasets, software, publications, and other research outputs, offering DOI minting, open access publication, and long-term preservation.
Institutional repositories are a useful fallback when no suitable domain-specific or generic repository is available, especially when local policies, support structures, or affiliation-based publication routes are relevant.
- The License selection guide for Creative Commons is a license chooser that helps users select an appropriate Creative Commons license for copyrightable works such as texts, images, teaching materials, or research outputs.
- Choose an open source license is a GitHub-supported guide that helps developers choose an open source license for software projects and source code.
- The License Selector is an open license selection tool that helps users find suitable public licenses for publishing data or software.
- NFDI4ING ing.grid is a scholarly-led journal for FAIR data management in engineering sciences.
- Data Science Journal is a peer-reviewed, open access, electronic journal, publishing papers on the management, dissemination, use and reuse of research data and databases across all research domains, including science, technology, the humanities and the arts.
- Data in Brief is a multidisciplinary, open-access, peer-reviewed journal which mainly publishes short, digestible data articles that describe and provide access to research data
- COMPAS is an open-source, Python-based framework for computational research and collaboration in architecture, engineering, fabrication and construction. It offers a wide range of functionality for the analysis, planning, and simulation of complex and bespoke architectural and engineering systems.
- fieldcompare is a command‑line tool to compare and validate field experiment datasets, compute differences, and produce summary reports.
- Cookiecutter is a command‑line utility to create projects from templates and bootstrap reproducible project structures.
Create software projects from reusable templates. - plotID is a Python RDM utility that tags figures with persistent IDs and exports the plot file.
- Plot Serializer converts scientific plots (matplotlib) into FAIR JSON and RO‑Crate, and can recreate plots from JSON
- SHACL Form is an HTML5 web component for creating editable and view-only forms from SHACL shapes (Application Profiles) and serialising the entered data as RDF.
- NFDI4ING Terminology Service allows searching, browsing, and downloading ontologies. Find and reuse engineering terminologies and ontologies.
- NFDI4ING Metadata4Ing is an ontology for describing research data generation and provenance in engineering, covering processes, tools, variables, and roles.
Describe research data and workflows using semantic metadata. - DataDesc is a tool to generate comprehensive and clear metadata for your datasets and software, automating data profiling, documentation, and integration.
- Research Object Crate (RO-Crate) is a lightweight, JSON‑LD packaging format for bundling research outputs with metadata and provenance for FAIR reuse.
- Built Environment Ontology Lookup Service is a platform for built‑environment ontology discovery, exploration, and evaluation.
Find, evaluate, and reuse built environment ontologies.
- How to Set Up Automated Testing and Publish a PyPI Package in 2023 Make research software discoverable and reusable via PyPI
- The Data Literacy Alliance (DALIA) Find and reuse FAIR learning materials on research data management.
- The OSArch Community is an international, community-based open-source initiative for architecture, engineering, construction, and the built environment. They provide a lot of resources, events and news on free and open software topics for the built environment.
- opensource construction is a Swiss initiative on open source in construction with events and a nice open source project directory.
- Open AEC Foundation is a Dutch initiative that promotes and contributes to open source software in AEC.
- The Linked Building Data Community Group brings together experts in the area of building information modelling (BIM) and Web of Data technologies, defining existing and future use cases and requirements for linked data-based applications throughout the life cycle of buildings.
Anything missing? Drop us a message at AEC in NFDI4ING!