Multidisciplinary research undertaken by the Web and Internet Science research group identified societal and technical barriers to data-driven innovation, and ways to overcome them.
The researchers learned that diverse frameworks and techniques, including big data, sensors and non-public data, were required to solve real-world problems, and that data users needed support to identify and extract value from their datasets. Trust was needed that data processing would be ethical and privacy-preserving. Research into Web Observatories – global resources for holding and sharing datasets and the tools used to visualise and interrogate them – resulted in frameworks to manage the risks related to data sharing.
Analysis of the use of data across 78 portals (the interfaces through which users access datasets) in 35 countries led to the production of guidelines to help designers make portals more user-friendly. Researchers also proposed new frameworks to enable people with non-technical backgrounds in small and medium-sized enterprises (SMEs) to exploit this rich resource.