Big Data and Transparency: Using MapReduce functions to increase Public Expenditure transparency
Eduardo de Paiva, Kate Cerqueira Revoredo · IEEE International Conference on Cloud Computing Technology and Science · 2016
Nowadays all government entity must maintain transparency portals that shows the all revenue and expenditure carried out daily. However, the mere availability of such information in government portals does not ensure an effective increase in the degree of transparency of these entities, because the large volume of data combined with the lack of standards makes it impossible any systematic monitoring of such data. This paper suggests the application of parallel programming techniques based on mapreduce programming paradigm to the identification of a predetermined set of products purchased by the Public Administration. It also proposes a way to consolidate this information to make easy viewing of disparities found in the large volume of data presented. The proposed solution was tested in a case study performed in the Transparency Portal of the Federal Government. The results suggest that the presented techniques constitute a promising approach to issues related to transparency areas, which normally handles large volumes of data, but it does not always provide quality information.