Computational materials databases can track the origin of data entries via annotations of the code repository used to generate the data along with specific metadata describing the computational methods. The analogue of this metadata for experimental materials science is far more complex due to the broad range of instruments and their settings, reagents and their purities, etc.. Perhaps most foundationally, the data resulting from materials experiments is often sensitive to the order of the experimental steps. Consequently, data management schema must encode the experiment provenance to uniquely represent a piece of experimental data. Recording experiment provenance is inherent to automated experiment workflows that track samples and record timestamps of experiments. Other strategies for provenance management have been introduced for spectroscopy experiments The MEKG contains a total of 52,263,968 nodes and 111,430,058 edges, and herein we its utility for high throughput electrochemistry experimentation and data exploration. We present 4 use cases, commencing with the most general applications, i) graphical exploration of data and ii) data retrieval via queries. We then describe specific implementation of database queries to iii) automate design of experiments and iv) evaluate a hypothesis from crowd-sourced data.