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Authors: Kenji Koga 1 ; Maria Spichkova 2 and Nitin Mantri 2

Affiliations: 1 iSelect, Cheltenham and Australia ; 2 School of Science, RMIT University, Melbourne and Australia

Keyword(s): Software Engineering, Data Integration, Health Systems, Biomedicine, Bioinformatics.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Engineering ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Software Engineering ; Symbolic Systems

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.

CC BY-NC-ND 4.0

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Paper citation in several formats:
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 - ENASE; ISBN 978-989-758-375-9; ISSN 2184-4895, SciTePress, pages 539-546. DOI: 10.5220/0007767405390546

@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 - ENASE},
year={2019},
pages={539-546},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007767405390546},
isbn={978-989-758-375-9},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Towards Automated Management and Analysis of Heterogeneous Data within Cannabinoids Domain
SN - 978-989-758-375-9
IS - 2184-4895
AU - Koga, K.
AU - Spichkova, M.
AU - Mantri, N.
PY - 2019
SP - 539
EP - 546
DO - 10.5220/0007767405390546
PB - SciTePress