py-meteo-num: Dockerized Python Notebook environment for portable data
analysis workflows in Indonesian atmospheric science communities
- Sandy Herho,
- Dasapta Irawan
Sandy Herho
Weather and Climate Prediction Laboratory ITB, Institute for Globally Distributed Open Research and Education (IGDORE)
Corresponding Author:[email protected]
Author ProfileDasapta Irawan
Bandung Institute of Technology, Bandung Institute of Technology
Author ProfileAbstract
Reproducibility and replicability in analyzing data is one of the main
requirements for the advancement of scientific fields that rely heavily
on computational data analysis, such as atmospheric science. However,
there are very few research activities that field in Indonesia that
emphasize the principle of transparency of codes and data in the
dissemination of the results. This issue is a major challenge for the
Indonesian scientific community to verify the output of research
activities from their peers. One common obstacle to the reproducibility
of data-driven research is the portability issue of the computing
environment used to reproduce the results. Therefore, in this article,
we would like to offer a solution through Debian-based dockerized
Jupyter Notebook that have been installed with several Python libraries
that are often used in atmospheric science research. Through this
containerized computing environment, we expect to overcome the
portability and dependency constraints that often faced by atmospheric
scientists and also to encourage the growth of research ecosystem in
Indonesia through an open and replicable environment.