The following article was published in the journal SoftwareX:
Docker Unified UIMA Interface: New perspectives for NLP on big data
2025.
Docker Unified UIMA Interface: New perspectives for NLP on big data. SoftwareX, 29:102033.
BibTeX
@article{Abrami:et:al:2025:a,
title = {Docker Unified UIMA Interface: New perspectives for NLP on big data},
journal = {SoftwareX},
volume = {29},
pages = {102033},
year = {2025},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2024.102033},
url = {https://www.sciencedirect.com/science/article/pii/S2352711024004047},
author = {Giuseppe Abrami and Markos Genios and Filip Fitzermann and Daniel Baumartz
and Alexander Mehler},
keywords = {Docker, Kubernetes, UIMA, Distributed NLP, duui, biofid, neglab, new-data-spaces, circlet, core, core_c08},
abstract = {Processing large amounts of natural language text using machine
learning-based models is becoming important in many disciplines.
This demand is being met by a variety of approaches, resulting
in the heterogeneous deployment of separate, partly incompatible,
not natively scalable applications. To overcome the technological
bottleneck involved, we have developed Docker Unified UIMA Interface,
a system for the standardized, parallel, platform-independent,
distributed and microservices-based solution for processing large
and extensive text corpora with any NLP method. We present DUUI
as a framework that enables automated orchestration of GPU-based
NLP processes beyond the existing Docker Swarm cluster variant,
and in addition to the adaptation to new runtime environments
such as Kubernetes. Therefore, a new driver for DUUI is introduced,
which enables the lightweight orchestration of DUUI processes
within a Kubernetes environment in a scalable setup. In this way,
the paper opens up novel text-technological perspectives for existing
practices in disciplines that deal with the scientific analysis
of large amounts of data based on NLP.}
}