Data in itself is a collection of facts such as numbers, words, measurements and observations that computers can process and analyse to extract insights. For example, personal data, covering aspects ranging from your demographics to location and email address, created when you make a purchase at a shop, accept a hotel reservation or rent a car. These datasets are a commodity for businesses and public authorities because they can be used to address complex social issues such as economic development, health and climate change. However, there is a risk that the collected data is incomplete or no longer valid, meaning that insights extracted after analysis are flawed or not applicable.
Thus, there is a need to distinguish between data and high-quality data. There are five identified factors that can classify high-quality data, namely: data completeness, data consistency, data accuracy, data validity and data timeliness. By focusing on collecting, analysing and re-using high-quality data, organisations can create further impact and improve their decision-making process by lowering risk in outcomes, increase productivity and enable better marketing through accurate targeting and communication.
An example of a Directive to further promote the use and re-use of high-value data is the new Open Data and Public Sector Information (PSI) Directive, which makes available high-value data for re-use.