Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank

BANGUI, Hind, Mouzhi GE and Barbora BÜHNOVÁ. Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank. Online. In Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1. Crete, Greece: SciTePress, 2019, p. 286-293. ISBN 978-989-758-369-8. Available from: https://dx.doi.org/10.5220/0007717402860293.

Basic information

• Original name: Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank
• Authors: BANGUI, Hind (504 Morocco, belonging to the institution), Mouzhi GE (156 China, guarantor, belonging to the institution) and Barbora BÜHNOVÁ (203 Czech Republic, belonging to the institution).
• Edition: Crete, Greece, Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1, p. 286-293, 8 pp. 2019.
• Publisher: SciTePress

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: Portugal
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14610/19:00109111
• Organization unit: Institute of Computer Science
• ISBN: 978-989-758-369-8
• Doi: http://dx.doi.org/10.5220/0007717402860293
• UT WoS: 000570344500029
• Keywords in English: Big Data; 3D Data Quality; Data Cleaning; 3D Data Processing; Data Analytics; Protein Data Bank
• Tags: firank_B, rivok
• Tags: International impact, Reviewed

Abstract

3D data have been widely used to represent complex data objects in different domains such as virtual reality, 3D printing or biological data analytics. Due to complexity of 3D data, it is usually featured as big 3D data. One of the typical big 3D data is the protein data, which can be used to visualize the protein structure in a 3D style. However, the 3D data also bring various data quality problems, which may cause the delay, inaccurate analysis results, even fatal errors for the critical decision making. Therefore, this paper proposes a novel big 3D data process model with specific consideration of 3D data quality. In order to validate this model, we conduct a case study for cleaning and analyzing the protein data. Our case study includes a comprehensive taxonomy of data quality problems for the 3D protein data and demonstrates the utility of our proposed model. Furthermore, this work can guide the researchers and domain experts such as biologists to manage the quality of their 3D protein data.

Links

• EF16_013/0001802, research and development project: Name: CERIT Scientific Cloud