Analytics for citizens: A linked open data model for statistical data exploration

A growing number of public institutions all over the world have recently started to make government statistical data available in open formats, thus enhancing transparency and accountability, stimulating innovation, and promoting civic awareness and engagement. Integration issues related to fragmentation and heterogeneity of these datasets can be partially addressed by referring to the Linked Data approach, which also enables easier access and consumption by users. However, the lack of an explicit representation of how statistical indicators are calculated still hinders their interpretation, and hence the development of applications and services especially useful for citizens, who do not have full knowledge and control over the underlying data and analysis models. In the present work, we discuss an approach to ease the interaction of communities of citizens with statistical Linked Open Data. We define a model and a set of services allowing people to recognize the mathematical structure of statistical indicators, improving in this way user awareness of the meaning of indicators and their mutual relations. Through such services, it is possible to enable interactive browsing of indicator formulas and novel typologies of data exploration, including dynamic computation of indicators not explicitly stored and comparison of different Linked Data resources.