ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles

Andreas Schmidt, Andreas Schmidt, Mohamad Koubaa, Jan Schweikert, Karl-Uwe Stucky, Wolfgang Süß, Veit Hagenmeyer

2023

Abstract

An important point for the widespread dissemination of FAIR-data is the lowest possible entry barrier for preparing and providing data to other scientists according to the FAIR criteria. If scientists have to manually extract, transform and annotate the data according to the FAIR criteria and then export it to make it available to the public, this requires a significant investment of time that does not primarily reward the scientist who prepares and provides the data. The Energy Lab at KIT is running a large cluster of an Influx database management system with energy related time series data being stored in a variety of individual databases over periods of up to 15 years. In order to increase the willingness to make data available to the scientific public, we develop a tool that greatly supports and automates the publication and annotation process of time series data stored in Influx databases.

Paper Citation

in Harvard Style

Schmidt A., Koubaa M., Schweikert J., Stucky K., Süß W. and Hagenmeyer V. (2023). ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-671-2, SciTePress, pages 303-310. DOI: 10.5220/0012254300003598

in Bibtex Style

@conference{kmis23,
author={Andreas Schmidt and Mohamad Koubaa and Jan Schweikert and Karl-Uwe Stucky and Wolfgang Süß and Veit Hagenmeyer},
title={ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2023},
pages={303-310},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012254300003598},
isbn={978-989-758-671-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles
SN - 978-989-758-671-2
AU - Schmidt A.
AU - Koubaa M.
AU - Schweikert J.
AU - Stucky K.
AU - Süß W.
AU - Hagenmeyer V.
PY - 2023
SP - 303
EP - 310
DO - 10.5220/0012254300003598
PB - SciTePress