by Panos Charitos. Published: 29 July 2015

The University of Derby is a modern, innovative university, comprising seven colleges that offer high quality education in cutting-edge subjects. With more than 20,000 students and over 3000 members of staff, the University of Derby has one of the highest staff to student ratio among UK universities, hence offering high quality teaching and research supervision both to undergraduate and graduate students. 

The College of Engineering and Technology comprises two departments: the Department of Engineering which employs over fifty full time academics in the fields of electronic engineering, manufacturing engineering, civil engineering as well as architecture, and the Department of Computing and Mathematics that has over thirty full-time staff, specializing in the fields of computer science, data and network science, cybersecurity and mathematics. The College has a total of 2,500 students, the vast majority being undergraduates from the UK and the rest of Europe. The college offers a number of specialized engineering and technology courses that enable students to study advanced areas of expertise and improve their technical and strategic skills.

The College has recently kicked off a collaboration with the ALICE Experiment, following the initiative of one of the senior academics in the Department of Computing and Mathematics, Dr. Ashiq Anjum and with the support of Prof. Nick Antonopoulos, Dean of the College of Engineering and Technology of the University of Derby in the UK.

Dr. Anjum is a specialist in distributed computing and he has spent a significant amount of time at CERN working on his PhD thesis. He joined the University of Derby three and a half years ago and at that time the department started exploring the possibility of building a relationship with a suitable experiment at CERN, as a number of academics working on “Big Data and Cloud Computing” were interested in such a partnership. Prof. Antonopoulos says: “The four large scale experiments taking place at CERN could provide a fruitful first background for us to apply our expertise on Big Data and further develop them,” and continues “We identified ALICE as a very relevant experiment and so I, Ashiq, and the Heads of the two Departments, namely Angela Dean and Prof. Richard Hill organized a visit to CERN in May”. 
During their visit, they had the chance to meet the ALICE Spokesperson as well as Predrag Buncic, the Computing Coordinator of ALICE, and Pierre Vande Vyvre, who is heavily involved in the O2 upgrade project. They tried to understand the nature of the experiment—particularly how ALICE handles the large amount of data produced during heavy-ion collisions—as well as identify the areas in which their expertise could better fit in. “Our aim was to identify areas or open problems that we could support in the best way possible as a College,” Prof. Antonopoulos explains. “It seems that there is a significant number of subgroups within the ALICE Experiment that are very relevant to the expertise of the College, particularly the groups working on data flow, data simulation and analysis, and computing platforms, while we are obviously very interested in the online and offline aspects involved in the O2 project.” Finally, the group also discussed some possibilities in the field of electronic engineering and hopefully some interesting projects will come up in the future.

Following their visit, a formal letter was sent to Paolo Giubellino, expressing the College’s interest in joining ALICE as an associate member, which was discussed at the ALICE Management Board and finally approved during the last collaboration board in GSI.

In the beginning of July, a group of academics visited CERN to meet up with the relevant groups and forge stronger bonds between ALICE and the University of Derby. It was a very interesting visit that brought about many activities and thoughts on collaborative projects that could be carried out. Prof. Antonopoulos adds: “I believe that in the next six to twelve months the College will be in a position to commit a significant percentage of a full time equivalent of two to three academics and two to four postgraduates to work jointly on tasks and challenges related to ALICE. I do anticipate that we will work closely with the ALICE collaboration and support the future needs of the experiment”.

“CERN in many ways epitomizes the vision I have for the future of the College—and this can also be seen in the many partnerships we have developed with R&D departments of industries like Lockheed Martin, Rolls Royce, Roche pharmaceutical a.o. Effectively we aim to apply our knowledge in managing huge datasets and learning how to discover hidden patterns in these datasets in real time. We want to do that in real world applications. In other words, instead of developing synthetic datasets to apply algorithms, having access to the ALICE data and facing real challenges the moment they happen, provides us with the best opportunity to make an impact.”

Finally we asked Prof. Antonopoulos about the challenges of Big Data. Big Data is a broad term that describes huge datasets both in terms of size and complexity, for which traditional data processing applications are simply inadequate. There are Big Challenges involved in Big Data, from how this data is recorded and checked for its consistency to the way it is visualized or stored. “One of the biggest challenges,” according to Prof. Antonopoulos, “is processing the data, because they are characterized by high-velocity. A solution to this problem is very powerful algorithms which do the processing within a reasonable timescale without overwhelming the computational infrastructure.” However, as the size of data increases faster than the capabilities of infrastructures, the effectiveness of algorithms is mainly responsible for keeping the data size controllable within time constraints. Prof. Antonopoulos concludes: “These are the two main challenges for the following years and I believe that our collaboration with ALICE could further develop our techniques and knowledge, as well as help the Experiment deal with the data expected during the Run3 of the LHC.”