Professor Gill Dobbie
Gill worked in industry for a couple of years before she became an academic. She has held permanent and visiting positions at the University of Melbourne, Victoria University of Wellington and the National University of Singapore.
Research | Current
Gill has a wide range of research interests, including databases, the web, and software engineering.
She is interested both in structured and semistructured data. More specifically, she is interested in how data can best be organized and managed, how the semantics of the data can be retained and expressed, and how querying can be carried out efficiently.
Her main areas of interest pertain to databases and the web. She has worked in the foundations of database systems, defining logical models for various kinds of database systems, and reasoning about the correctness of algorithms in that setting. With colleagues at the National University of Singapore, she has defined a data model for semistructured data (called ORA-SS), providing a language independent description of the data. The group she was working with has used the ORA-SS data model to define a normal form for ORA-SS schema, defined valid views for semistructured databases, and described a storage structure for semistructured databases using object relational databases.
Selected publications and creative works (Research Outputs)
- Tu, Y. C., Dobbie, G., Warren, I., & Meads, A. (2018). An experience report on a boot-Camp style programming course. SIGCSE 2018 - Proceedings of the 49th ACM Technical Symposium on Computer Science Education. 10.1145/3159450.3159541
Other University of Auckland co-authors: Andrew Meads, Yu-Cheng Tu
- Gao, Q., Lee, M. L., Ling, T. W., Dobbie, G., & Zeng, Z. (2018). Analyzing Temporal Keyword Queries for Interactive Search over Temporal Databases. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10.1007/978-3-319-98809-2_22
- Chen, J. (2018). Vehicle emission prediction using remote sensing data and machine learning techniques The University of Auckland. ResearchSpace@Auckland.
Other University of Auckland co-authors: Jason Chen, Yun Sing Koh
- Venkata, S. S. K., Bharadwaj, J., Dobbie, G., & Manoharan, S. (2017). A real-time distributed hardware health monitoring framework. Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2016. 10.1109/ICATCCT.2016.7911977
Other University of Auckland co-authors: Sathiamoorthy Manoharan
- Naeem, M., Dobbie, G., Lutteroth, C., & Weber, G. (2017). Skewed distributions in semi-stream joins: How much can caching help?. Information Systems, 64, 63-74. 10.1016/j.is.2016.09.007
Other University of Auckland co-authors: Gerald Weber
- Shi, X., Cui, B., Dobbie, G., & Ooi, B. C. (2017). UniAD: A unified Ad hoc data processing system. ACM Transactions on Database Systems, 42 (1)10.1145/3009957
- Jokhio, M. S., Sun, J., Dobbie, G., & Hu, T. (2017). Goal-based testing of semantic web services. Information and Software Technology, 83, 1-13. 10.1016/j.infsof.2016.11.011
Other University of Auckland co-authors: Jing Sun
- Asghar, M. R., Lee, T., Baig, M. M., Ullah, E., Russello, G., & Dobbie, G. (2017). A Review of Privacy and Consent Management in Healthcare: A Focus on Emerging Data Sources. CoRR, abs/1711.00546.
Other University of Auckland co-authors: Giovanni Russello, Rizwan Asghar