The provenance of data is central in drawing conclusions from raw data . This necessitates active tracking of acquisition and processing. To address the challenge of managing these complexities, our DMS implements a real-time approach in the context of the DataHub which is backed by our local PostgreSQL Database, designed to dynamically handle meta, raw, and analyzed data. It consists of several interconnected tables that capture specific details of the experiments. The experiments table forms the core of the database, stores essential metadata, such as material, date, and operator information (Fig. , Section DMS). This is complemented by the users table, which details the researchers involved, ensuring traceability and accountability. The motor-positions table logs the specific operational data such as precise motor positions for the SDC head, adding further detail to the experimental records. Each type of electrochemical measurement in the database features paired procedure and raw tables. The procedure tables encapsulate the unique parameters and settings of every measurement, while the raw tables record granular empirical data. Key metrics, provided by MADAP and passed to HELAO, support the facilitation of ML algorithm usage when handling large data volumes through web server communication. Robust data integrity is ensured through primary and foreign keys, enabling complex queries that link procedures raw data, and experimental metadata. Additionally, the database incorporates sequences for auto-generating Unique Identifiers (UIDs), streamlining data entry and retrieval. This cohesive database system adheres to FAIR principles , to establish the integrity of experimental data while enhancing its accessibility, usability and interpretability . This infrastructure minimizes human error in automated settings and is engineered to facilitate the correlation of electrochemical and spectroscopic tests, offering a unified platform for comprehensive multi-modal data analysis.