Process for contributing and accessing FAIR data

Data in the energy domain is dispersed currently across various stakeholders, such as energy providers, grid operators and consumers. A data sharing platform can be used to overcome these challenges and provide a contact point for collecting, processing, and sharing energy-related data among different actors [1]. As a key element for the successful establishment of community services in energy research, industry involvement is important. Industry partners can not only contribute important technical and business datasets, but also utilize the platform as users to access existing data. However, the current contributing and accessing data process is complicated and hard for industry partners to use [2]. According to the FAIR data principle [3], these requirements play a crucial role in the implementation and use of data in the energy sector. To address these requirements, this paper proposes a process for contributing and accessing FAIR data. As shown in Figure 1, users begin by collecting and preparing the data they wish to upload in the Data Preparation step. Once prepared, the data is forwarded to the Access Mechanism, managed by the admin, who configures access control policies for data security and compliance. The data is then officially registered on the platform, where first legal conditions are checked and verify adherence to data protection laws and privacy policies to mitigate legal risks. Next, an anonymization framework is applied to protect sensitive information based on previous results and requirements. The metadata management process collects relevant metadata and designs efficient storage and indexing mechanisms for quick retrieval via database queries or API calls. Additionally, Data Provenance Information records the source, transformation history, and processing steps of the data. Finally, a robust archiving process ensures that data remains accessible when needed while protecting it from unauthorized access or loss. The process of accessing FAIR data is shown in Figure 2. The Data Search step involves a search functionality to efficiently locate datasets using keywords, metadata, or data attributes. Once users identify the desired datasets, the access mechanism defines how they can request and obtain these datasets, supporting various methods including API access. Following data retrieval, effective data visualization becomes essential for presenting datasets in a clear and actionable manner. This enables users to create visual representations. Finally, the multi-format data step provides service to ensure the platform supports various data formats to accommodate diverse user needs and facilitate seamless integration across multiple systems. In summary, this paper presents a framework that implements FAIR data principles and incorporates industrial stakeholders into contributing and accessing data. To evaluate "FAIRness" of defined process, we used the FAIR data self-assessment tool [4]. The defined process achieved an 88% compliance score, with identified enhancement opportunities in two main areas: improving the Accessibility of metadata records and strengthening Reusability by expanding the provenance information documentation to better facilitate data reuse. Future work will focus on adapting the process to accommodate various services.