#publisher alternate (BUTTON) Close Skip to main content sign in * Saved for later * Comment activity * Edit profile * Email preferences * Change password * Sign out subscribe search dating more from the guardian: * dating * jobs change edition: * switch to the UK edition switch to the US edition switch to the AU edition International * switch to the UK edition * switch to the US edition * switch to the Australia edition The Guardian * home * home * UK * world * sport * football * opinion * culture * business * lifestyle * fashion * environment * tech * travel browse all sections close Higher Education Network big data in universities How big data has transformed research We speak to the academics behind four inspiring projects to see how big data is being used to develop and enhance research Claire Shaw Interviewed by Claire Shaw @clurshaw email Friday 10 July 2015 07.45 BST Last modified on Friday 10 July 2015 10.26 BST * Share on Facebook * Share on Twitter * Share via Email * Share on Pinterest * Share on LinkedIn * Share on Google+ * Share on WhatsApp Illustris Simulation Facebook Twitter Pinterest The picture shows dark matter density overlaid with the gas velocity field. Photograph: Illustris Simulation Shy Genel, Hubble fellow at the astronomy department of Columbia University, US Describe your research project: Illustris is a computer simulation of the evolution of the universe, through which we study how galaxies and their constituent stars and black holes form and evolve over cosmic time. IFRAME: https://www.youtube.com/embed/GPyNqagzFr0 Illustris simulation of the universe. How did you involve big data? For the project we had to simulate as large a portion of the universe as possible and resolve each individual galaxy in this simulated universe in as much detail as possible. The calculation was performed on a supercomputer where 8,192 processors shared the memory and the computations between them, constantly communicating and reporting to each other on their respective up-to-date results. The calculation also produced a big amount of data, over 300,000 gigabytes, to be stored for long term, which requires hundreds of hard drives to be joined together into a single huge virtual storage space. What challenges did you face? Performing the simulation on thousands of processors in parallel was difficult. It requires sophisticated calculations as well as a strong and stable supercomputer, of which there are only a few in the world. What do you think the future holds for big data and research? Big data is allowing us to build more realistic models of various systems in nature. As big data capabilities improve, we will be able to connect those different scales in a more self-consistent way – these advances are guaranteed to provide us with new insights into the workings of nature. science lab Facebook Twitter Pinterest Researchers at the Institute for Computational Health Sciences are looking at the difference between cancer and normal to help provide changes in clinical treatment given today to cancer patients. Photograph: Stefan Wermuth/Reuters Idit Kosti, postdoctoral fellow at the Institute for Computational Health Sciences, University of California, San Francisco Describe your research project: I’m working on improving clinical treatment and basic biological knowledge in various types of cancer tumors using big data. How did you involve big data? Big data, in my case, is gene and protein expression levels coming from cancer tumors and normal tissues from patients and healthy volunteers. Using this information I’m able to study the difference between cancer and normal, verify my hypothesis, create models and suggest changes in clinical treatment given today to cancer patients. The remarkable part is that DNA and RNA sequencing (the technology used for gene expression) has been around since the 70s, but the method we use today, next generation sequencing, was fully developed only around 2004 and became commercially available around 2006-2007. The development of this technology is the only reason we have access to the large amount of data. What challenges did you face? First challenge is finding data sources – patients and healthy volunteers. For that we need either patient or family consent, depending on data type. Second challenge is collecting the data. This process is an expensive and time-consuming one, and requires not only the data collection, but also reducing noise levels coming from both technology limitations and natural human variation. What do you think the future holds for big data and research? A future with medical and biological big data holds a great promise for human health and research. I imagine a world where our genetic profiles, combined with physical measurements, is a key element in medical decisions: from simple ones, such as everyday dosage of headache pills using genetic profile, to complex ones such as designing cancer treatment by using the gene and protein expression taken from a tumour biopsy. YARN Facebook Twitter Pinterest Examples of online stories created by the community. Simon Popple, deputy head, school of media and communication, University of Leeds Describe your research project: YARN is a new community designed digital storytelling platform. It was produced through the AHRC-funded Pararchive Project and allows communities and organisations to create online stories and do research by sharing archive material, as well as their own interesting possessions. It does this by making institutional big data, such as museum collections, available for anyone to access. How did you involve big data? By partnering with the Science Museum Group and BBC archives, we wanted to create connections between large collections of data held in traditionally closed archives and allow communities to explore, experience and be creative with these resources. Organisations can directly make recourses available through the platform and allow people to incorporate them directly in their stories, providing illustrations, evidence and creative resources. What do you think the future holds for big data and research? Big data is something of a catch-all concept and an obvious buzzword at the moment. It is a term often and simply defined in terms of scale rather than content, accessibility and intelligibility. For it to be really useful to communities it needs to be carefully translated and made relevant. Data needs humanising and stories help to do that. MobileMiner The picture shows how MobileMiner can track a train journey from London to Cardiff by using open source information on cell tower locations. Tobias Blanke, senior lecturer, department of digital humanities, King’s College London, UK Describe your research project: The growing use of mobile and digital devices has led to a massive increase in the amount of data each of us generates, but until now, access to mobile data has been restricted to just a handful of companies and government agencies. And for this reason, we have little knowledge about the kinds of data that our mobile phones collect and transmit. The project – Our Data, Ourselves (ODO) – aims to reverse this. It makes the data and how it’s transmitted visible in order to develop new modes of citizen engagement, as well as new avenues for research and creativity. How did you involve big data? In order to trace and make visible the digital breadcrumbs we leave behind through our mobile devices, we have developed a mobile app called MobileMiner, which tracks incoming and outgoing communications in mobile devices. For example, we can understand how mobile phones track the movement of people using cell tower location information or how gaming apps leak data to marketers around the world without our knowledge. If big data is increasingly collected by companies through everyday sensors and mobile phones, we want to show the flows of this data and reclaim ownership of our data. What challenges did you face? Collaboration with those who produce the data was key to our research but also our biggest challenge; as using and understanding what happens to data requires both data and computer knowledge. We worked together with Young Rewired State, an organisation that teaches young people how to code through collaborative events. Together we developed a toolkit to help others understand what happens to their data and how to take ownership of it. What do you think the future holds for big data and research? There is a lot of potential for understanding history and society through the big data we leave behind. An often-quoted example is the George W. Bush Presidential Center holdings of 200 million White House emails of the second Bush administration, which are only just becoming available for access under the US Freedom of Information Act. It is here that big data can be useful to researchers in the humanities and social science, who can trace how emails appear around events and understand from their content the mindset of decision makers. The big data that business companies and state agencies collect from real-life sensors and mobile devices could also become an important object for research. The question remains, however, how to ensure access to this data, particularly when the institutions that collect it have little incentive to make it available for research. Join the higher education network for more comment, analysis and job opportunities, direct to your inbox. Follow us on Twitter @gdnhighered. __________________________________________________________________ More features Topics * Research (Higher Education Network) * Academics * Higher education * Science (Education) * Big data * Research (Education) __________________________________________________________________ * Share on Facebook * Share on Twitter * Share via Email * Share on Pinterest * Share on LinkedIn * Share on Google+ * Share on WhatsApp * Reuse this content View all comments > comments Sign in or create your Guardian account to join the discussion. This discussion is closed for comments. We’re doing some maintenance right now. You can still read comments, but please come back later to add your own. 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