TY - GEN
T1 - A Comparative Study of Methods for Deciding to Open Data
AU - Luthfi, Ahmad
AU - Janssen, Marijn
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2019
Y1 - 2019
N2 - Governments may have their own business processes to decide to open data, which might be supported by decision-making tools. At the same time, analyzing potential benefits, costs, risks, and other effects-adverse of disclosing data are challenging. In the literature, there are various methods to analyze the potential advantages and disadvantages of opening data. Nevertheless, none of them provides discussion into the comparative studies in terms of strengths and weaknesses. In this study, we compare three methods for disclosing data, namely Bayesian-belief networks, Fuzzy multi-criteria decision-making, and Decision tree analysis. The comparative study is a mechanism for further studying the development of a knowledge domain by performing a feature-by-feature at the same level of functionalities. The result of this research shows that the methods have different strengths and weaknesses. The Bayesian-belief Networks has higher accuracy in comparison, and able to construct the causal relationships of the selected variable under uncertainties. Yet, this method is more resource intensive. This study can contribute to the decision-makers and respected researchers to a better comprehend and provide recommendation related to the three methods comparison.
AB - Governments may have their own business processes to decide to open data, which might be supported by decision-making tools. At the same time, analyzing potential benefits, costs, risks, and other effects-adverse of disclosing data are challenging. In the literature, there are various methods to analyze the potential advantages and disadvantages of opening data. Nevertheless, none of them provides discussion into the comparative studies in terms of strengths and weaknesses. In this study, we compare three methods for disclosing data, namely Bayesian-belief networks, Fuzzy multi-criteria decision-making, and Decision tree analysis. The comparative study is a mechanism for further studying the development of a knowledge domain by performing a feature-by-feature at the same level of functionalities. The result of this research shows that the methods have different strengths and weaknesses. The Bayesian-belief Networks has higher accuracy in comparison, and able to construct the causal relationships of the selected variable under uncertainties. Yet, this method is more resource intensive. This study can contribute to the decision-makers and respected researchers to a better comprehend and provide recommendation related to the three methods comparison.
KW - Bayesian-belief networks
KW - Decision tree analysis
KW - Decision-making
KW - Fuzzy multi-criteria decision making
KW - Methods
KW - Open data
UR - http://www.scopus.com/inward/record.url?scp=85069160672&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-24854-3_14
DO - 10.1007/978-3-030-24854-3_14
M3 - Conference contribution
AN - SCOPUS:85069160672
SN - 9783030248536
VL - 356
T3 - Lecture Notes in Business Information Processing
SP - 213
EP - 220
BT - Business Modeling and Software Design - 9th International Symposium, BMSD 2019, Proceedings
A2 - Shishkov, Boris
A2 - Shishkov, Boris
A2 - Shishkov, Boris
PB - Springer
T2 - 9th International Symposium on Business Modeling and Software Design, BMSD 2019
Y2 - 1 July 2019 through 3 July 2019
ER -