Category: Big Data

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MoDS: Mapping Knowledge with Data Science (MSc + PhD Studentship)

Although we had some great responses to our initial call, we’re still looking for the ‘right’ candidate for this fully-funded studentship that is open to both undergraduate finalists as well as completing Masters students. The project involves the application of data science techniques (text-mining, topic modelling, graph analysis) to a large, rich data set of 450,000+ PhD theses in order to understand the evolving geography of academic knowledge production: how are groundbreaking ideas produced and circulated, and how does researcher mobility and institutional capacity shape this process?

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MoDS: Mapping Knowledge with Data Science

I’m really excited to announce the latest addition to our department’s growing stable of computational geography research: a fully-funded 1+3 ESRC CASE studentship involving the application of data science techniques (text-mining, topic modelling, graph analysis) to a large, rich data set of 450,000+ PhD theses in order to understand the evolving geography of academic knowledge production: how are groundbreaking ideas produced and circulated, and how does researcher mobility and institutional capacity shape this process?

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Geocomputation for Geoscience: The Earth System Data Cube

PhD student and King’s Geocomputation member Alejandro Coca-Castro attended Europe’s premier geosciences event, The European Geoscience Union (EGU) General Assembly, in Vienna, Austria (April 24th – 28th 2017). In addition to presenting his preliminary PhD results in the session “Monitoring the Sustainable Development Goals with the huge Remote Sensing archives”, Alejandro kindly dedicated part of his attendance at EGU to capture the emerging Geocomputation fields applied to Geosciences, and in particular for land and biosphere research. In this post Alejandro summarises the latest advances in Big Data technologies presented at EGU, which he sees as one of the two main emerging fields revolutionizing the data-driven analysis allows knowledge-production.