Data Science

Data science seeks to understand how we can extract and exploit knowledge from data of all kinds. It is primarily concerned with modern scenarios in which data sources are increasingly complex, large and rich (i.e. ‘big data’). It encompasses many fields, ranging through information retrieval, machine learning, privacy, security, signal processing, visualization, and more. Of particular interest to data scientists are the research questions and opportunities that arise from exploiting multiple data sources. To predict the spread of an infection, for example, traditional approaches can now be enhanced with open data on weather, traffic, transport schedules, and more.

Such opportunities are leading to the emergence of new research themes within data science, such as ‘differential privacy’, linked data’ and ‘integrated analytics’.

Within SICSA, there are many groups and individuals pursuing world-class research in one or more areas of data science, covering the full spectrum from theory to application, and covering all of the enabling technologies that support current and future data science.  The Data Science theme is linking and facilitating these activities, incubating new and exciting collaborations and helping to establish a leading portfolio of data science research, enterprise and innovation to support scientists and industry in Scotland and beyond.

This theme serves as the main link for SICSA member institutions to The Data Lab Innovation Centre.

The Research Theme Leaders for Data Science are Dr Amos Storkey (a.storkey@ed.ac.uk) and Professor Mike Chantler (M.J.Chantler@hw.ac.uk).

Please complete a proposal and email to admin@sicsa.ac.uk if you wish to organise a theme activity or event in this area.

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