Design and Application of the AHP-TOPSIS-2N to Evaluate (Linked) Open Government Data from the Electricity Datasets

Abstract

This study proposes to simplify and automate this process, combining two different methods of decision support through multicriteria analysis in a model capable of judging and prioritizing risk criteria in the context of Open Data, presenting the results via iterative online dashboards developed in R. The methodology followed combines the AHP and TOPSIS-2N methods, creating a ranking of the open governmental dataset of the electricity sector in light of the risk criteria evaluated by the proposed model. The AHP technique was used to specify and normalize the importance of each criterion, considering the consistency aspects of the decision matrix. The next step was to apply the TOPSIS-2N method to sort and prioritize these datasets. The results present the datasets that should be improved concerning the respective metadata and the prioritized themes to make the decision-making for the management of the respective bases more agile and assertive.