Preparation and publication of measurement data from the Wallbox Inspection research project

In this project, researchers from the Reiner Lemoine Institute are supporting the publication of measurement data from the “Wallbox Inspection” research project. The aim of the project is to process the resulting data in a structured way and to publish the collected measurement data on the Open Energy Platform (OEP), an established research data infrastructure for energy research.

Measurement data from the “Wallbox Inspection” research project

In the main project “Wallbox Inspection”, a consortium of the Berlin University of Applied Sciences (HTW Berlin), Fraunhofer ISE and the General German Automobile Club (ADAC) is developing a test procedure for solar-optimised and bidirectional charging. This generates large amounts of measurement data for the analysis and evaluation of charging infrastructure for electric vehicles. The RLI supports close, comprehensible and accessible data publication through standardised processes and established infrastructures.

Structured preparation and publication of data

The amount of data amounts to over 10 TB. This makes it difficult to publish easily and requires sophisticated data management, including storage optimization and compression. The project team analyzes the raw data and develops an optimized target schema as well as suitable compression and transfer methods. The processed data is then imported into the Open Energy Platform.

Sustainable research data management according to the FAIR principle

The Open Energy Platform is a research database in which all information is made available in an open and structured way. For the project, the scientists are creating standardized metadata according to the FAIR principles (Findable, Accessible, Interoperable, Reusable) based on the OEMetadata standard. The publication on the Open Energy Platform creates a transparent basis for further research on charging infrastructure and electromobility.

Project period: May 2026 – Juni 2026

• Analysis of raw data structures and development of an optimized target schema
• Implementation of validation mechanisms to ensure data consistency and quality
• Establishment of robust processes as well as backup and restore scenarios