Networks & Big Data
Date and Venue 18th December at the British Library
Main organisers: Patrick Wolfe, Natalia Bochkina, Jon Crowcroft, Artur Czumaj, Richard Gibbens, Peter Grindrod, Mark Handley
The interplay between theory, algorithms and systems is key to our ability to manage massive heterogeneous datasets and extract information from them, both at scale and in real time. This workshop will scope data science at the interface between mathematical and computational sciences, in the specific context of networks. On one hand, the mathematical sciences have seen an explosion of interest in both network data and network models, motivating new fundamental research in algorithms. On the other hand, parallel, distributed or multicore implementations of algorithms and data access for network problems is a key driver of computer science research in systems. This workshop seeks to elucidate, through the following 3 key questions, the natural interplay between these two points of view.
1. What mathematical advances are required to fundamentally change our understanding of networks in an era of big data?
2. What are the key algorithmic primitives for next-generation graph analytics, and how can next-generation systems best support and drive these needs?
3. How do we move towards a more mature understanding of parallel, distributed or multicore implementations of algorithms and data access for network problems?