A Fuzzy Multi-criteria Decision Making Approach for Analyzing the Risks and Benefits of Opening Data

Abstract

Governments are releasing their data to the public to accomplish benefits like the creation of transparency, accountability, citizen engagement and to enable business innovation. At the same time, decision-makers are reluctant to open their data due to some potential risks like misuse, sensitivity, ownership, and inaccuracy of the data. The goal of the study presented in this paper is to develop a Fuzzy Multi-Criteria Decision Making (FMCDM) approach to analyze the risks and benefits to determine the decision to open a dataset. FMCDM is chosen due to its capability to measure and weight the relative importance of the criteria. FMCDM need the weighting of criteria as input. For this Fuzzy Analytical Hierarchy Process (FAHP) is utilized by collecting input from experts' knowledge and expertise. The scores for each criterion are summed up to rank the importance of the alternatives. Four main criteria are used, e.g. data sensitivity and data ownership representing risks criteria, and data availability and data trustworthy as benefits criteria. For each criterion, there were two sub-criteria identified. Four types of decisions to open data can be made: completely open, maintain suppression, provide limited access, and remain closed. A health patient record dataset is used to illustrate the approach. In further research, we recommend to develop automated approaches that take a dataset as an input and can provide an advice.

A Comparative Study of Methods for Deciding to Open Data

“…The following Table 1 gives a summary of comparative study using three methods in open data domain. [6,10] Data is summarized based on the pairwise comparison matrix [7] Data is summarized based on the assign payoffs process of possible investments [19] Data type Numerical and categorical [27] Numerical and categorical [17] Numerical and categorical [20] Probability Posterior probability distribution [10] Posterior probability distribution [17] Posterior and conditional probability distribution [28…”

“…There have been works of literature introduce the methods to analyze the potential advantages and disadvantages of opening data and its consequences [6][7][8]. Methods like Bayesian-belief networks, Fuzzy multi-criteria decision-making, Decision tree analysis, and privacy risks scoring model were used to analyze the potential risks and benefits of opening data [6,7,9]. However, none of them provides insight into the comparative studies in terms of strengths and weaknesses.…”

Decision Tree Analysis for Estimating the Costs and Benefits of Disclosing Data

“…There is no evaluation and assessment model introduced in this framework. 4 A fuzzy multi-criteria decision making (FMCDM) [16,17] As a practical methodology for dealing with fuzziness and uncertainty in Multiple Criteria Decision-making (MCDM), Fuzzy AHP (FAHP) has been applied to a wide range of applications. Fuzzy AHP has been implemented to a broader domain of studies.…”

Modelo de Apoio à Decisão para Avaliar Dados Governamentais Abertos do Setor Elétrico

“…Análise qualitativa de dados de entrevistas semiestruturadas foi realizada por [Buda et al 2015] e [Luthfi et al 2018b] na proposição de estruturas conceituais, Frameworks Qualitativos, de suporte à decisão para abertura de dados, oferecendo, respectivamente, recomendações e estratégias de abertura de bases sob as Dimensões Custo e Ecossistema (fechado, restrito ou aberto) e para comparar políticas de dados abertos.…”