Professor Ooi Beng Chin and research collaborators win 2020 ACM SIGMOD Research Highlight Award

24 June 2020
From left: Professor Ooi Beng Chin, Computer Science PhD student Ruan Pingcheng and Senior Research Fellow Dr Lin Qian, received the 2020 ACM SIGMOD Research Highlight award for their paper, which offers a solution for blockchain vendors to improve their products. It was co-authored with three researchers from other universities.

24 June 2020 – NUS Computing Distinguished Professor Ooi Beng Chin and his team have won a 2020 ACM SIGMOD Research Highlight Award at the 2020 ACM SIGMOD/PODS International Conference on Management of Data, which was held online from 14 to 19 June. The conference is a leading international forum for researchers who explore and advance research on data management.

Prof Ooi and five other research collaborators received the award for their paper, titled ‘Revealing Every Story of Data in Blockchain Systems’. The award recognises research projects that address important problems with solutions that have considerable impact on the industry and the community.

The researchers explored combining two current, separate uses of blockchains — supporting online transactions between parties, and resolving transaction disputes — by introducing data provenance (a record trail of a data’s origin) to smart contracts (programs that run on a blockchain), explained NUS Computer Science PhD student Ruan Pingcheng, one of the paper’s co-authors.

This produces a feature that enriches the expressiveness of an application’s business logic (the algorithms dictating the flow and processing of information between a user interface and database). Expressive business logic thus refers to the ability for the smart contract to make better decisions for the client based on historical data.

For instance, a supply chain may utilise a smart contract that places orders for a product based on the company’s current stock. With the team’s solution, the smart contract relies on historical data to make better decisions for the company, such as referring to the monthly number of products recorded in the inventory in the previous year, to determine when orders should be placed or stopped.

Pingcheng added that the feature the team has come up with is secure, requires minimal additional resources, and offers a solution for blockchain vendors to improve their products and tailor it to their clients’ needs.

The paper’s other research collaborators include Dr Lin Qian, a Senior Research Fellow from NUS Computing’s Department of Computer Science, as well as computer science professors from the Singapore University of Technology and Design, Beijing Institute of Technology and Zhejiang University.

“We are very pleased that this research work has attracted a great deal of interest from database and blockchain communities. This means that our work is of practical importance to both databases and blockchains,” said Pingcheng, on behalf of the team.

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