Over the past few months I’ve started a new job working at the Geomatics and Cartographic Research Centre (GCRC) at Carleton University. It’s been a splendid place to work and learn, and it has helped me think about the world in fascinating ways. The project I’ve been working on with the GCRC over the past few months has been a knowledge mobilization application in genomic research and it has inspired me to create a similar model that will be directed towards my interest in climate change, specifically energy and AI.
What is a knowledge graph?
Briefly, a knowledge graph is a interconnected set of nodes and relations that help users understand relationships between concepts. This graph structure allows for a clear understanding of how two elements are connected and through these connections we can easily develop novel understandings of the field we are trying to study. For example, I’ve made a dummy knowledge graph about me and my cat Jeeves, and my imaginary friend Bobby Bobbertson and their pet Rob seen in fig. 1. In the knowledge graph provided you can see how the connectedness of the graph allows us to generate ideas about the topic we are exploring. For example, by looking at fig. 1, someone might come to the conclusion that pets generally like eating and going to the park. Clearly the knowledge graph I’ve made is quite small, but as we increase the number of data points novel discoveries that were otherwise shrouded in complexity present themselves with clarity.
My goal over the next few months is to create a knowledge graph that looks at climate change, energy, and artificial intelligence. Through this graph I hope to help users get a better understanding of each field individually, but also how these fields connect. During this process I will also continue to be writing pieces that give a deep dive into specific topics, and I hope by the end of this project you will be better informed about the world, and how you can contribute to solving climate change.
Mako
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