Data Science Seminar: The data science revolution in Physics and Astronomy

Abstract Heading into the 2020s, Physics and Astronomy are undergoing experimental revolutions that will reshape our picture of the fabric of the Universe. The Large Hadron Collider (LHC), the largest particle physics project in the world, produces 30 petabytes of data annually that need to be sifted through, analysed, and modelled. In astrophysics, the Large Synoptic Survey Telescope (LSST) will be taking a high-resolution image of the full sky every 3 days, leading to data rates of 30 terabytes per night over ten years. These experiments endeavour to answer the question why 96% of the content of the universe currently elude our physical understanding. Both the LHC and LSST share the 5-dimensional nature of their data, with position, energy and time being the fundamental axes. This talk will present an overview of the experiments and data that is gathered, and outlines the challenges in extracting information. Common strategies employed are very similar to industrial data! Science problems (e.g., data filtering, machine learning, statistical interpretation) and provide a seed for exchange of knowledge between academia and industry. Speaker Biography Professor Mark Sullivan Mark Sullivan is a Professor of Astrophysics in the Department of Physics and Astronomy. Mark completed his PhD at Cambridge, and following postdoctoral study in Durham, Toronto and Oxford, now leads a research group at Southampton studying dark energy using exploding stars called "type Ia supernovae". Mark has many years' experience of research that involves repeatedly imaging the night sky to track the arrival of transient objects, involving significant challenges in data handling, processing, classification and analysis.

Web 1, 2 and 3

Lecture on IA and webdesign (1 & 2 of 3). Web 2 talk I reference Aral Balkan - talk video is included here from his presentation at the Norwegian developers conference.

Assessment and Feedback for the CIP: educational issues

This 11-minute video focuses on how self and peer assessment could be used as an integral part of CIP modules, and discusses some innovative methods for assessing written work. The first link is to the native Panopto podcast, which requires the Silverlight player to be installed. The second link is the MP4 video version of the podcast, which should play on all PCs, Macs and suitable mobile devices. This share also includes links to the papers discussed in the video - these are also provided at the end of the script.