Abstract
We present a framework for easy annotating, archiving, retrieving, and searching measurement data from a large-scale data archival system. Our tool extends and simplifies the interaction with the database and is implemented in popular scientific applications used for data analysis, namely MATLAB, and Python. This allows scientists to execute complex interactions with the database for data curation and retrieval tasks in a few simple lines of accessible templated code. Scientists can now ensure their measurement data is well curated and FAIR (findable, accessible, interoperable, and reusable) compliant without requiring specific data skills or knowledge. Our tools allow users to perform SQL-type (Structured Query Language) queries on the data from simple templated scripts allowing data retrieval from long-term storage systems.