A $Li$ne $Me$asuring library for large and complex spectroscopic data sets: Implementation of a virtual observatory for JWST spectra

The upcoming generation of telescopes, instruments, and surveys is poised to usher in an unprecedented "Big Data" era in the field of astronomy. Within this context, even seemingly modest tasks such as spectral line analyses could become increasingly challenging for astronomers. In this paper, we announce the release of ${\rm L{\small I}M{\small E}}$. This package is tailored for multidisciplinary observations with long-slit and integral field spectroscopy (IFS) support. ${\rm L{\small I}M{\small E}}$ functions encompass the reading of observational files, detecting lines, conditioned line fitting, and the plotting and storage of results. Most importantly, these measurements are structured to support the subsequent chemical and kinematic analyses. To reduce the coding effort required from users, we introduced a notation system for atomic transitions that is accessible to humans and machine-readable. Along with this system, we present an extensive database of line bands, spanning from the ultraviolet to the infrared wavelength range. Additionally, we propose a model designed to train machine learning algorithms in line detection. ${\rm L{\small I}M{\small E}}$ features a comprehensive online documentation, which details the command attributes and includes several tutorials. These tutorials range from measuring a single line to analyzing an entire IFS data cube. This library functions and measurements are showcased in an online virtual observatory. The data in this interactive website come from the JWST NIRSpec observations of the CEERs survey. In this regard, ${\rm L{\small I}M{\small E}}$ offers improvements related to the dissemination and accessibility of astronomical spectra.