- General objective: Build an interdisclipnary science and technology data sharing platform.
- Specific objectives:

• Build an interdisclipnary science and technology data storing and managing software.
• Build toolkits to support data mining, data sharing and data integration.
• Build a storage to support teaching and researching at University of Science and Technology of Hanoi.

Theoretical results:
- Lung Medical Image Database: The research team has collected and synthesized a database of chest X-ray images and CT scan images of the lungs from open source on the Web platform and also from the hospital. The databases can be used for future research on the application of artificial intelligence in medical images.
- The Red River Surface Water Quality Database: The research team has synthesized and pre-processed raw data of some scientific research projects on the surface water quality of the Red River of USTH and the Vietnam Academy of Science and Technology to obtain The Red River Surface Water Quality Database, which can be useful for future research on predicting the Red River water quality.
- Image smoothing method: The group has proposed a new method called image smoothing algorithm to improve the Kuwahara filter that accelerates the processing speed of the Kuwahara algorithm regardless of the size of the input image. This method has been published in an SCI-E journal.
- A data-centric deep learning method for lung nodule detection on CT scan images. This method is accepted to be published in Vietnamese national journal indexed by VAST2.
Applied results:
- The data storage and management software system is a sample product that allows storing interdisciplinary scientific and technological data in many different formats (in the topic, demo formats were in digital and image). The system provides data mining services including the toolkits for data collection and data integration, data retrieval, data extraction and data sharing, querying and indexing based on content toolkits. The software system that the team built is based on a microservice architecture that can expand horizontally at a large scale to serve scientific and technological problems dealing with big data.
- Software to support remote diagnosis of lung cancer is a sample product that assists doctors in using built-in deep learning models as well as storing and exploiting data, which is stored in the software system and manage data built by the topic.
- Specification documents and user manual: Describe in detail the functions and usage of the data storage software system and the software to support remote lung cancer diagnosis.
- Providing a user interface for data collection and analysis of a research team of ICT department. The analyzed results are published in a VAST2 journal.

- Collecting and synthesizing 2 sets of lung medical image databases and digital data on Red River surface water quality to help provide data for future studies on the application of artificial intelligence in medical imaging and prediction Red River water quality.
- Proposing a new method called image smoothing algorithm to improve the Kuwahara in a new method to speed up the processing of the Kuwahara algorithm regardless of the size of the input image. This method has been published in an SCI-E journal.
-  A data-centric deep learning method for lung nodule detection on CT scan images. This method is accepted to be published in Vietnamese national journal indexed by VAST2.
- Building an interdisciplinary science and technology data storage and management platform that can scale horizontally at large scale to support large interdisciplinary data storage and mining.

- Scientific papers in international and national journals: 01 paper indexed by SCI-E Q2 and 02 national paper indexed by VAST2.

• Huy Duc Le, Giang Son Tran*, “Free-size accelerated Kuwahara filter”, in Journal of Real-Time Image Processing 18, no. 6 (2021): 2049-2062 [SCI-E].
• Chi Cuong Nguyen, Long Giang Nguyen, Giang Son Tran*, “A data-centric deep learning method for pulmonary nodule detection”, in Journal of Computer Science and Cybernetics, vol. 38, no. 3, p. 229–243, Sep. 2022 [VAST2].
• Giang Son Tran*, Axel Carlier, Daniel Hagimont, “An in-depth evaluation of frequency-aware scheduler for improving user experience on mobile devices”, in Journal of Computer Science and Cybernetics (accepted September 28th, 2022) [VAST2].

- Training: Support training for 02 PhD students, successfully train 02 master students, support training for 02 master students.
- Specific products (product description, storage location)

• Software system for storing and managing data
• Lung Medical Image Database
• The Red River Surface Water Quality Database
• Software to support remote lung cancer diagnosis
• Specification documents and manuals