Scientific Lenses over Linked Data: An approach to support multiple integrated views

When are two entries about a concept in different datasets the same? If they have the same name, properties, or some other criteria? The choice depends upon the application to which the data will be put. However, existing Linked Data approaches provide a single global view over the data with no way of varying the notion of equivalence to be applied.

In this presentation, I will introduce Scientific lenses, an approach that enables applications to vary the equivalence conditions between linked datasets. They have been deployed in the Open PHACTS Discovery Platform – a large scale data integration platform for drug discovery. To cater for different use cases, the platform allows the application of different lenses which vary the equivalence rules to be applied based on the context and interpretation of the links.

Bio: 

Alasdair is a Lecturer in Computer Science at Heriot-Watt University, Edinburgh. He previously held postdoc positions in the Information Management Group at the University of Manchester and and the Information Retrieval Group at the University of Glasgow. His research focuses  on practical data management and its application in information systems –  utilising and extending advances in knowledge management technologies to improve information systems. This approach has supported advances in science while deepening the understanding of knowledge based systems to support future applications. He has collaborated with a large range of scientists – from astronomers through the life sciences to environmental scientists – working with both academic research labs and industrial partners.