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Investigating the impact of Blockchain technology on the Relational Database infrastructure to improve key business operations such as Supply Chain Management and Logistics

Project Code: BC_RDB_SCM 

Project Description:

Relational databases are used by over 80% of global enterprises. The fundamental design aspects of these databases were determined by computer technology as it was in the 1970s and 1980s. Relational theory will continue to be a key driver for the development of database technology, but significant aspects of relational database implementations will now be remodelled given the emergence of blockchain and the exponential improvements which have emerged and continue to increase in the areas of compute power, memory, and storage systems. 

The spread of crypto currencies globally has led to blockchain technology receiving greater attention in recent times in the form of ledger databases (Fekete & Kiss 2021). Verifiability is the backbone of most ledger systems to realize credible authentication at minimum cost. The standard architecture of a relational database kernel comprises modules which manage the insertion, update, and deletion of data. The relational kernel architecture of the future will be insert only, where logical updates and deletion of data will be managed as a data append only instruction, i.e., as a blockchain append. One means of achieving logical updates and deletes is using bitemporal methodologies. Temporal databases have been considered an active research topic since many decades (Gamper et al,2022). The main element of initial application development costs is the cost of managing temporal data in applications and of maintaining and enhancing existing applications. 

The aim of this research is to explore how the emergence of physical data “append only” technology can deliver the real-world enterprise requirements of logical insert, logical update, and logical data deletion. Relational theory is built on a current view modelling paradigm where most projects require access to the increasing requirements of regulatory audit showing “what was known and when it was known”. This research will aim to explore how blockchain can assist in designing and optimizing system of record solutions built with “current view” data modelling that autonomously maintains data relational integrity across both the transaction time and the effective time of the data. The aim is to show how solution development and ongoing solution operational can be improved. Specifically, the scope of PhD work will look at the importance of data sets for AI and particularly how bitemporal data and the Ld8a data model brings differing approaches to AI analysis. It is recognised that time series data sets from system of record solutions (such as in Supply Chain applications) are the basis for AI analysis. The research will compare and contrast the temporal solutions for holding time series data and the methods by which this data is derived from transactional systems of record. The ease with which time fashioned data can be produced and the overall accessibility for AI on these data sets are to be assessed. 

The expected impact of this research is that it will lead to the development of new relational database architectures that are more efficient, secure, and compliant. These new architectures will have a significant impact on the way that data is stored and managed and will make it easier for businesses to comply with regulations. The research will also lead to the development of new tools and techniques for managing temporal data, which will reduce the cost of developing and maintaining applications.

In summary, the proposal recognizes the significance of STEAM by combining scientific research on emerging technologies like blockchain, technological advancements in computing, engineering principles for database architecture, and the importance of complying with regulations. The interdisciplinary approach aims to bring together elements from multiple disciplines (such as Business, Computing and Engineering) to drive innovation and improvements in the field of database technology. 

Anticipated Findings and Contribution to Knowledge:

Anticipated Findings:
  • Blockchain technology can be used to improve the efficiency, security, and compliance of relational databases. 
  • Blockchain-enabled relational databases can be used to store and manage data more efficiently, securely, and compliantly than traditional relational databases. 
  • Blockchain-enabled relational databases can be used to address the challenges of data integrity, security, and compliance faced by businesses and organizations.
Contribution to knowledge:
  • The project will contribute to the knowledge of blockchain technology and its potential applications in the field of database management. 
  • The project will also contribute to the knowledge of relational databases and the challenges they face. 
  • The project will provide a roadmap for the development of new relational database architectures that are more efficient, secure, and compliant. 
  • The project will produce a new framework for businesses to adopt/migrate to blockchain technology 
  • The project will produce a novel application in the supply chain and logistics domain to illustrate the effectiveness of this new relational database architecture.
  • The project will demonstrate new understanding about how blockchain-enabled relational databases influence sustainability and environmental practices within supply chain and logistics. 
  • The project will offer specific knowledge on the regulatory and compliance implications of blockchain technology within the logistics and supply chain sector. 

Person Specification:

  • Masters/Bachelor's degree in computer science, data science or related discipline
  • Good familiarity with programming languages ideally C++ and be comfortable in working with 3rd parties using recognised development processes. 
  • Solid knowledge and understanding of relational databases.
  • Explore the implementation of existing research on blockchain/append only data technology into programmable database kernel environments such as MySQL 
  • Experience of descriptive and AI techniques suitable for temporal data 
  • Liaise with 3rd party database and supply chain management solution providers, multidisciplinary teams of data architects, data scientists and programmers. 
  • The candidate will be responsible for designing, developing, and maintaining the coding infrastructure.
  • Develop executable code to underpin a new database offering with strategic commercial importance. 
  • Potential to develop expertise in new areas of the subject 

Contact (and Director of Studies for this project): Professor Jagdev Bhogal, Jagdev.Bhogal@bcu.ac.uk 

How to Apply

To apply, please complete the project proposal form, ensuring that you quote the project reference, and then complete the online application where you will be required to upload your proposal in place of a personal statement as a pdf document. 

You will also be required to upload two references, at least one being an academic reference, and your qualification/s of entry (Bachelor/Masters certificate/s and transcript/s).