Every day, millions of people take photos, make videos and send texts. Across the globe, businesses collect data on consumer preferences, purchases and trends. Governments regularly collect all sorts of data ranging from census data to police incident reports. Furthermore we are increasingly being surrounded by new devices and sensors that empower us to measure and record the world around us with increasing precision. The abilities provided by these technologies affect us deeply and broadly, including in the way we communicate and socialise. The more we can connect and share, the more data we create.
This deluge of data is growing fast. The total amount of data in the world was 4.4 zettabytes in 2013. That is set to rise steeply to 44 zettabytes by 2020. To put that in perspective, one zettabyte is equivalent to 44 trillion gigabytes. The sheer volume, variety and velocity (through data streams) of the data are the main reasons it is termed as Big Data. However, for certain kinds of data, it is also possible to take advantage of the connections between the entities in the data and to analyse the underlying graph or network structures to glean further insight from this data.
The basic model of a graph consists of entities, referred to as nodes or vertices, and the connections between them, referred to as edges or links. Once we understand the expressive nature of graphs, it is easy to see them in all sorts of situations: a system of roads, the World Wide Web, social interactions on Facebook or Twitter, an electrical circuit on a printed circuit board, interactions between proteins or interactions between elected Members of Parliament and much more.
The science of networks has advanced our understanding of complex systems. But the power that comes from analysing networks is usually computationally expensive and introduces new challenges and specific tools.
One of the most relevant features of networks representing real systems is their underlying community structure: the organisation of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such communities can be considered as fairly independent compartments that play a similar role, like a group of friends with similar interests or a group of proteins that all combine with similar molecules. Detecting such communities is of great importance. But it is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it.
Dr Charlie Abela and Dr Joel Azzopardi from the Department of Artificial Intelligence at the University of Malta are conducting research that uses Big Data technologies to analyse graphs and to identify communities across different networks, including networks of sensors, academic collaborations and political networks. In the case of the latter, research is focused on identifying communities by exploiting the interactions between Members of Parliament from the different political parties and representing these interactions through interesting and interactive visualisations.
Dr Charlie Abela and Dr Joel Azzopardi are both lecturers at the Department of Artificial Intelligence at the University of Malta.
Did you know?
• Mars is red because there is an excessive amount of iron oxide which causes rust dust to form, and this floats in the air, covering most of its landscape.
• Mars has the biggest volcano that we know of in our solar system. Olympus Mons is 602 km wide (the size of Arizona) and 25km high (triple the height of Mount Everest).
• Neptune radiates more heat than it gets from the sun, which is bizarre since it is very far from the sun. Scientists still have no idea why this is so.
• For many years, scientists believed that the Earth was the only tectonically active planet in the solar system. High-resolution images from a spacecraft that mapped Mercury showed that faults are present on the planet and that it is still contracting and shrinking in size.
For more trivia see: www.um.edu.mt/think
Sound bites
• Alzheimer’s disease (AD) begins to alter and damage the brain years, even decades, before symptoms appear, making early identification of AD risk paramount to slowing its progression. New research is looking into whether measuring how quickly a person’s pupil dilates while they are taking cognitive tests may be a low-cost, low-invasive method to aid in screening individuals at increased genetic risk for AD before cognitive decline begins, and finding a link between the two.
https://www.sciencedaily.com/releases/2019/09/190910154659.htm
• About 466 million years ago, long before the age of the dinosaurs, the Earth froze, and new species evolved with the new temperatures. The cause of this Ice Age was a mystery, until now: a new study suggests that the Ice Age was caused by global cooling, triggered by extra dust in the atmosphere from a 150-kilometre-wide asteroid collision that happened between Mars and Jupiter.
https://www.sciencedaily.com/releases/2019/09/190918142025.htm
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