Publications Database

Welcome to the new Schulich Peer-Reviewed Publication Database!

The database is currently in beta-testing and will be updated with more features as time goes on. In the meantime, stakeholders are free to explore our faculty’s numerous works. The left-hand panel affords the ability to search by the following:

  • Faculty Member’s Name;
  • Area of Expertise;
  • Whether the Publication is Open-Access (free for public download);
  • Journal Name; and
  • Date Range.

At present, the database covers publications from 2012 to 2020, but will extend further back in the future. In addition to listing publications, the database includes two types of impact metrics: Altmetrics and Plum. The database will be updated annually with most recent publications from our faculty.

If you have any questions or input, please don’t hesitate to get in touch.

 

Search Results

Andrei Tara, Hjalmar K. Turesson, Nicolae Natea, Henry M. Kim (2023). "An Evaluation of Storage Alternatives for Service Interfaces Supporting a Decentralized AI Marketplace", IEEE Access, 11, 116919 - 116931.

Open Access Download

Abstract Given the exploding interest in generative AI and the concern that a few companies like Microsoft will monopolize access to such models, we address this centralization risk in the context of a DApp that matches buyers and sellers of various AI services. A key question for a decentralized marketplace is where and how to store the metadata that specifies the services’ properties in human and machine-readable formats. Having one or a few actors controlling access to that data constitutes undesirable centralization. We explore data storage alternatives to ensure decentralization, equitable match-making, and efficiency. Classifying decentralized storage alternatives as simple peer-to-peer replication, replication governed by a permissionless consensus, and replication governed by a private consensus, we select an exemplar for each category: IPFS, Tendermint Cosmos and Hyperledger Fabric. We conduct experiments on performance and find that read and write speeds are fastest for IPFS, about two times slower for Tendermint and slowest for Hyperledger. Writing using IPFS and Tendermint takes significantly longer than reading, and finally, specifically with IPFS, write speeds strongly depend on configuration. Given these results and the properties of the storage technologies, we conclude that simple peer-to-peer storage is the best option for the proposed AI marketplace.

Kim, Henry M. and Marek Laskowski (2018). "Towards an Ontology-Driven Blockchain Design for Supply Chain Provenance", Intelligent Systems in Accounting, Finance, and Management, 25(1), 18-27.

Open Access Download

Abstract An interesting research problem in our age of Big Data is that of determining provenance. Granular evaluation of provenance of physical goods--e.g. tracking ingredients of a pharmaceutical or demonstrating authenticity of luxury goods--has often not been possible with today's items that are produced and transported in complex, inter-organizational, often internationally-spanning supply chains. Recent adoption of Internet of Things and Blockchain technologies give promise at better supply chain provenance. We are particularly interested in the blockchain as many favoured use cases of blockchain are for provenance tracking. We are also interested in applying ontologies as there has been some work done on knowledge provenance, traceability, and food provenance using ontologies. In this paper, we make a case for why ontologies can contribute to blockchain design. To support this case, we analyze a traceability ontology and translate some of its representations to smart contracts that execute a provenance trace and enforce traceability constraints on the Ethereum blockchain platform.