Quality Management for Big 3D Data Analytics: A Case Study of Protein Data Bank
| Authors | |
|---|---|
| Year of publication | 2019 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 4th International Conference on Internet of Things, Big Data and Security - Volume 1 |
| MU Faculty or unit | |
| Citation | |
| web | http://dx.doi.org/10.5220/0007717402860293 |
| Doi | http://dx.doi.org/10.5220/0007717402860293 |
| Keywords | Big Data; 3D Data Quality; Data Cleaning; 3D Data Processing; Data Analytics; Protein Data Bank |
| Description | 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. |
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