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

Ahmad Luthfi, Marijn Janssen, Joep Crompvoets

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

The public expects government institutions to open their data to enable society to reap the benefits of these data. However, governments are often reluctant to disclose their data due to possible disadvantages. These disadvantages, at the same time, can be circumstances by processing the data before disclosing. Investments are needed to be able to pre-process a dataset. Hence, a trade-off between the benefits and cost of opening data needs to be made. Decisions to disclose are often made based on binary options like “open” or “closed” the data, whereas also parts of a dataset can be opened or only pre-processed data. The objective of this study is to develop a decision tree analysis in open data (DTOD) to estimate the costs and benefits of disclosing data using a DTA approach. Experts’ judgment is used to quantify the pay-offs of possible consequences of the costs and benefits and to estimate the chance of occurrence. The result shows that for non-trivial decisions the DTOD helps, as it allows the creation of decision structures to show alternatives ways of opening data and the benefits and disadvantages of each alternative.

Original languageEnglish
Title of host publicationDigital Transformation for a Sustainable Society in the 21st Century - 18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019, Proceedings
EditorsIlias O. Pappas, Ilias O. Pappas, John Krogstie, Letizia Jaccheri, Patrick Mikalef, Yogesh K. Dwivedi, Matti Mäntymäki
PublisherSpringer
Pages205-217
Number of pages13
ISBN (Print)9783030293734
DOIs
Publication statusPublished - 2019
Event18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019 - Trondheim, Norway
Duration: 18 Sep 201920 Sep 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11701 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019
CountryNorway
CityTrondheim
Period18/09/1920/09/19

Keywords

  • Benefits
  • Costs
  • Decision tree analysis
  • Estimation
  • Investments
  • Open data
  • Open government

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  • Cite this

    Luthfi, A., Janssen, M., & Crompvoets, J. (2019). Decision Tree Analysis for Estimating the Costs and Benefits of Disclosing Data. In I. O. Pappas, I. O. Pappas, J. Krogstie, L. Jaccheri, P. Mikalef, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Digital Transformation for a Sustainable Society in the 21st Century - 18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019, Proceedings (pp. 205-217). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11701 LNCS). Springer. https://doi.org/10.1007/978-3-030-29374-1_17