A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.Read moreRead less
Next-generation spatial keyword search. Spatial keyword search is like a normal web search plus additional location information, which helps users to obtain a better ranking of results by considering the spatial proximity. The success of this project will deliver a next-generation spatial keyword search system that overcomes the severe usability limitations experienced by users today.
Escaping the concurrency trade-off: a new approach to enterprise software. Enterprise software manages the operations of all business and government organisations. Designers of this often rely on their intuition or luck, by using high-performance database facilities whose correctness is not guaranteed. This project will show designers how to use these facilities while still having the assurance that the data will not be corrupted. This will improve the quality of the data used by Australian ent ....Escaping the concurrency trade-off: a new approach to enterprise software. Enterprise software manages the operations of all business and government organisations. Designers of this often rely on their intuition or luck, by using high-performance database facilities whose correctness is not guaranteed. This project will show designers how to use these facilities while still having the assurance that the data will not be corrupted. This will improve the quality of the data used by Australian enterprises, and thus improve their operations. Australian software designers will also benefit, as they will be able to produce software that combines high performance with assurance that concurrency errors will not occur.Read moreRead less
Efficient databases for flash memory. This project will bring significant benefits to Australia. It will place Australia at the fore-front of the emerging field of flash memory databases. The lack of prior research in this field, coupled with the significant performance benefits of flash memory, means this project will make significant breakthroughs in this frontier technology. The algorithms developed will be directly incorporated into a state-of-the-art open source database and disseminated ....Efficient databases for flash memory. This project will bring significant benefits to Australia. It will place Australia at the fore-front of the emerging field of flash memory databases. The lack of prior research in this field, coupled with the significant performance benefits of flash memory, means this project will make significant breakthroughs in this frontier technology. The algorithms developed will be directly incorporated into a state-of-the-art open source database and disseminated throughout the international community, thereby boosting Australia's international research reputation. The database developed will significantly increase the speed of large database servers as well as bring significant energy savings to databases running on small portable devices.Read moreRead less
Improving the Effectiveness of Conceptual Model Validation Work. Errors or omissions in conceptual models often lead to significant problems when information systems are being built. Prior research has shown the cost of fixing the consequences of such errors or omissions grows exponentially as a function of how late they are discovered. Thus, significant economic benefits arise if they are identified early in the system development process. The project outcomes will facilitate early prevention ....Improving the Effectiveness of Conceptual Model Validation Work. Errors or omissions in conceptual models often lead to significant problems when information systems are being built. Prior research has shown the cost of fixing the consequences of such errors or omissions grows exponentially as a function of how late they are discovered. Thus, significant economic benefits arise if they are identified early in the system development process. The project outcomes will facilitate early prevention and detection of errors of omissions in conceptual models. They will also contribute to attainment of the national priority goal of smart information use through improved data management.Read moreRead less
Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage ....Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage capabilities, including graphics processor and flash-based memory. This project will devise an adaptive key-value store framework for heterogeneous systems. Our new framework will adaptively harvest the performance potential of future hardware such that applications can cope with fast-growing data sets.Read moreRead less
Managing private location data in a mobile and networked world: getting the balance right. Location based data are transforming the mobile service industry and this project will develop novel approaches to safeguard the location privacy of mobile individuals. This will facilitate the development of privacy-aware services which can be used for real time traffic monitoring, care for the elderly and smartphone enabled location services.
Effective and efficient record linkage with transformation rules. Record linkage is an enabling technology for organisations to identify and remove 'redundant' entries in their databases; this helps prevent data quality problems that may cost millions. This project will deliver the next-generation record linkage methodology that enables cost and time economical linkage beyond what is currently possible.
Locality sensitive hashing for big data. This project aims to solve problems to applying locality sensitive hashing (LSH) to Big Data, namely handling new similarity functions, large data volume and better efficiency. LSH is one of the most widely adopted methods for answering similarity queries, and used widely in computer science. The project is expected to provide frontier technology to applications to combat crimes in the cybersecurity space, and lead to more intelligent and real-time analys ....Locality sensitive hashing for big data. This project aims to solve problems to applying locality sensitive hashing (LSH) to Big Data, namely handling new similarity functions, large data volume and better efficiency. LSH is one of the most widely adopted methods for answering similarity queries, and used widely in computer science. The project is expected to provide frontier technology to applications to combat crimes in the cybersecurity space, and lead to more intelligent and real-time analysis of Big Data.Read moreRead less
Algorithms for collaborative micro-navigation based on spatio-temporal data management and data mining. Traffic congestion coupled with greenhouse gas emissions is a major challenge for modern society. This project will tackle this challenge by developing computer-assisted smart vehicles that can access and exchange real-time information about traffic conditions, leading to improved driving experience, safety and environmental sustainability.