What does the resource contain?
The Open Energy Ontology (OEO) is collaboratively developed to provide a standardized terminology for energy system modeling applications. Relevant terms are collected and catalogued with clear definitions and relationships to other ontology terms. The OEO is built on the Basic Formal Ontology (BFO), and reuses existing terms from other ontologies where appropriate, all to improve interoperability between it and other ontologies and use cases.
Four main modules make up the OEO:
- oeo-model: contains entities related to models and modeling (including entities regarding simulation scenarios)
- oeo-physical: contains entities related to energy generation and the physical structures of energy systems
- oeo-social: contains entities related to the social and economic factors that impact energy systems
- oeo-shared: contains entities which are needed in all of the other modules, to avoid duplicated entity implementation
How can the resource be applied?
- Disambiguate terms by using the definitions in this controlled vocabulary.
- Annotate data with standardized terms, improving interoperability with similarly-annotated data sets.
- Improve search functionalities to aid in data discovery and analysis.
Credits
This resource was developed by:
Energy-related Reference Ontologies Foundry
What does the resource contain?
The Energy-related Reference Ontologies (ENERO) Foundry’s mission is to support and guide ontology developers and users. The Foundry provides a set of principles for the development of ontologies in the energy domain. These principles, collaboratively written by experienced ontology developers, highlight best practices for the creation of interoperable, reusable, well-formed and scientifically accurate ontologies.
How can the resource be applied?
- Use the ENERO Foundry principles as a best practices guide when developing a new ontology.
- Align an existing ontology with the principles, to improve its interoperability with other Foundry-compliant ontologies.
- Join the ENERO Foundry community to provide feedback on the principles and help establish guidance for ontology developers.
Credits
Contributors to the ENERO Foundry are listed in https://github.com/ENEROFoundry/ENEROFoundry/blob/production/CITATION.cff
Climate and Energy Policy Ontology
What does the resource contain?
The Climate and Energy Policy Ontology (CEPO) is a common set of definitions and relationships which can be used to structure information about climate and energy policy instruments. It was created as a collaborative effort between different researchers, from academia and civil society, to map and clearly define different kinds of policy instruments.
CEPO encompasses instruments at a sufficient level of detail to code in-depth policy data. For example, rather than coding all “tax instruments” together, CEPO differentiates between a tax reduction, tax deduction, tax credit, tax exemption, and tax rebate (all of which are types of tax incentives). This level of granularity is important in being able to compare policies across jurisdictions and time. In order to ensure interoperability with other ontologies, it makes use of the Basic Formal Ontology (BFO) and its principles. It also maps its alignment with the CPDB and CPR policy instrument typologies.
How can the resource be applied?
- Code texts with information about the policy instruments that they contain.
- Use coded policy documents to answer questions such as:
- Which countries tend to use the most regulatory instruments vs economic instruments to introduce electric vehicles?
- What are the most common types of tax incentives to promote renewable energy, and how have these changed over time?
- Which policy instruments (or mixes of policy instruments) have been the most effective at promoting decarbonization outcomes (emissions reductions, growth in clean energy generation, etc.)?
- How do energy scenarios change when using real policy data on spatial regulations instead of assumptions?
Credits
This resource was developed by:
- Climate Policy Atlas research team: Silvia Weko, Puru Malhotra, Aksornchan Chaianong, Ioannis Milioritsas, Franziska Bold, Johan Lilliestam
- Additional contributors to CEPO development: German Bersalli, Ludwig Hülk, Mirjam Stappel, Amanda Wein, Open Energy Ontology developer team, Climate Policy Radar team
What does the resource contain?
The linked Train the Trainer concept encompasses various materials that can be utilized in educational contexts related to research data management. It was originally developed in the FDMentor project and is now maintained by the DINI / nestor-AG “Forschungsdaten”.
The topics covered include both the content-related aspects of research data management and units on didactic principles and the development of teaching and workshop concepts. In addition, the concept includes a collection of didactic methods.
How can the resource be applied?
- Prepare RDM workshops with ready-to-use unit scripts.
- Train new trainers at research institutions.
- Combine with online learning (e.g. LiaScript course).
- Customize content with CARE/FAIR modules for specific contexts.
Credits
This resource was developed by:
- Biernacka, K., Dockhorn, R., Engelhardt, C., Helbig, K., Jacob, J., Kalová, T., Karsten, A., Meier, K., Mühlichen, A., Neumann, J., Petersen, B., Slowig, B., Trautwein-Bruns, U., Wilbrandt, J., & Wiljes, C. (2023). Train-the-Trainer-Konzept zum Thema Forschungsdatenmanagement (Version 5) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.10122153
What does the resource contain?
FAIR Assessment Tools help researchers and developers systematically evaluate how well their research outputs align with the FAIR principles. FAIR stands for Findable, Accessible, Interoperable, and Reusable, which are guiding principles for improving the management and stewardship of scientific data and digital objects.
By running datasets or software through FAIR assessment tools, users obtain structured reports, quantitative scores, and actionable feedback. This helps identify gaps in compliance with FAIR principles and provides guidance for making research outputs more discoverable, usable, and sustainable over the long term.
On the linked website of FAIR-IMPACT, you find a list of FAIR-assessment tools, each with a different focus: While F-UJI is a web service to programmatically assess FAIRness of research data objects at the dataset level, FAIR-Aware helps you assess your knowledge of the FAIR Principles, O’FAIRe (Ontology FAIRness Evaluator) is a metadata-based automatic FAIRness assessment methodology for ontologies and semantic artefacts, and FOOPS! (Ontology Pitfall Scanner for FAIR) is a tool for assessing FAIRness level for ontologies.
Since software requires different considerations when it comes to theoretically and practically designing FAIR, specified metrics for software are necessary. The linked FAIR-impact metrics for software guide this specified assessment.
How can the resource be applied?
- Check a dataset before publication to improve metadata and accessibility.
- Demonstrate FAIR compliance in project deliverables.
- Teach FAIR principles in workshops with hands-on assessments.
- Evaluate software sustainability using dedicated FAIR metrics.
Credits
All information and tools listed above stem from the FAIR-IMPACT website.
RDM online course for energy researchers
What does the resource contain?
The “Research Data Management (RDM) for Energy Research” course offers a detailed exploration of how to handle research data in the energy sector. The course introduces participants to the FAIR data principles — ensuring data is Findable, Accessible, Interoperable, and Reusable. It emphasizes practical steps for managing data efficiently, from the creation of data management plans to handling complex data from simulations and software in energy projects. The interactive nature of the course, along with real-world examples, ensures a comprehensive understanding of RDM tailored specifically for energy researchers.
The course is hosted on LiaScript, an interactive learning platform, and covers essential topics such as data lifecycle management, data preservation, and sharing practices. Participants will learn about the legal and ethical considerations related to data management in energy research, including open-access strategies and the use of metadata for enhanced collaboration.
How can the resource be applied?
- Self-paced learning for students, PhD students, or early-career researchers.
- Introductory module in workshops or summer schools.
- Supplementary material for trainers preparing lectures or tutorials.
Credits / Source
The initial development of the course was funded by the EFZN’s (Energy Research Centre of Lower Saxony), a broader initiative to foster efficient and transparent research practices in the energy sector, implemented by the Carl von Ossietzky University of Oldenburg, and supported by ZDIN and NFDI4Energy.
What does the resource contain?
Forschungsdaten.info is a central German-language portal for research data management. It provides reliable guidance on technical, organizational, and legal aspects of handling research data.
In addition to in-depth articles and case studies, it features Spiele mit FDM-Bezug — interactive games and playful exercises designed to make RDM concepts more tangible and engaging for learners. These games can be used in teaching, workshops, or self-study.
The portal is maintained collaboratively by research organizations and libraries, ensuring that information remains up to date and trustworthy.
How can the resource be applied?
- Use it as a foundational reference in training or onboarding.
- Integrate the “Spiele” section in workshops to create interactive learning moments.
- Assign specific articles to newcomers as introductory reading.
Credits
The Website Forschungsdaten.info is operated and hosted by the University of Konstanz within the Baden-Württemberg state initiative for research data management (bwFDM).
