UK Data Service – visualising data

We are pleased to announce the launch of a new interactive data visualisation feature on UKDS.Stat, the data dissemination platform for international data at the UK Data Service. We have added a ‘Featured data’ section to the UKDS Stat homepage where we will highlight significant/topical news or events and showcase relevant international data. To launch this feature we have chosen to highlight #WorldPopulationDay which takes place on 11 July each year. The theme for this year is Family Planning: Empowering People, Developing Nations which has the aim of raising awareness that access to safe, voluntary family planning is a human right, is central to gender equality and women’s empowerment, and is a key factor in reducing poverty.

The scatterplot displayed includes two data series from the World Bank World Development Indicator dataset (April 2017 edition) – ‘Birth rate (per 1000 people) vs GDP per capita, PPP, 2015’. A link to the data visualisation can be tweeted and a link to the correct citation information is displayed. In addition, the scatterplot data can be viewed within a UKDS.Stat table and any update to the underlying dataset will be immediately reflected in the interactive data visualisation. The scatterplot is generated by extracting data via the UKDS.Stat Application Programming Interface (API) using the SDMX-JSON web service, which is then fed into an appropriate visualisation tool; it is the result of work carried out by the international data team looking at how people can use the UKDS.Stat API to access data and generate a variety of interactive visualisations. Presenting data in a visual context can help people to understand the significance of the data. As well as highlighting the data we host on UKDS.Stat, we are keen to help others to build their own visualisations using our data. We have added some information describing how to create both static data visualisations within UKDS.Stat and also how to generate interactive data visualisations from API queries and from CSV formatted data. We would love to see any data visualisations you develop, so please do let us know and remember to #citethedata.

 

 

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