Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain

Kenji Koga, Maria Spichkova, Nitin Mantri

2019

Abstract

Cannabinoid research requires the cooperation of experts from various field biochemistry and chemistry to psychological and social sciences. The data that have to be managed and analysed are highly heterogeneous, especially because they are provided by a very diverse range of sources. A number of approaches focused on data collection and the corresponding analysis, restricting the scope to a sub-domain. Our goal is to elaborate a solution that would allow for automated management and analysis of heterogeneous data within the complete cannabinoids domain. The corresponding integration of diverse data sources would increase the quality and preciseness of the analysis. In this paper, we introduce the core ideas of the proposed framework as well as present the implemented prototype of a cannabinoids data platform.

Paper Citation

in Harvard Style

Koga K., Spichkova M. and Mantri N. (2019). Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain.In Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-375-9, pages 539-546. DOI: 10.5220/0007767405390546

in Bibtex Style

@conference{enase19,
author={Kenji Koga and Maria Spichkova and Nitin Mantri},
title={Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain},
booktitle={Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2019},
pages={539-546},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007767405390546},
isbn={978-989-758-375-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain
SN - 978-989-758-375-9
AU - Koga K.
AU - Spichkova M.
AU - Mantri N.
PY - 2019
SP - 539
EP - 546
DO - 10.5220/0007767405390546