Abstract
Geographic decision support systems aim to integrate and process data originating from different sources and different data providers in order to create suitability models. A suitability model denotes how suitable geographic locations are for a specific purpose on which decision-makers need to make a decision. Particularly in the presence of volunteered information, data quality assessment becomes an important aspect of a decision-making process. Geographic data are commonly prone to incompleteness, imprecision and uncertainty, and this is even more the case with volunteered data. To correctly inform the users, it is essential to communicate not only the suitability degrees highlighted in a suitability model, but also the confidence about these suitability degrees as can be derived from data quality assessment. In this chapter, a novel hierarchical approach for data quality assessment, supporting the computation of associated confidence degrees, is introduced. To illustrate its added value, aspects of the project Transnational and Integrated Long-term marine Exploitation Strategies (TILES) are used. Providing confidence information adds an extra dimension to the decision-making process and leads to more sound decisions.
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References
Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis. Dordrecht, The Netherlands: Kluwer Academic Publ.
Zeleny, M. (1982). Multiple Criteria Decision Making. New York, USA: McGraw Hill.
Jankowski, P., & Richard, L. (1994). Integration of GIS-based suitability analysis and multicriteria evaluation in a spatial decision support system for route selection. Environment and Planning B, 21(3), 326–339.
Rinner, C., & Raubal, M. (2004). Personalized Multi-Criteria Decision Strategies in Location-Based Decision Support. Journal of Geographic Information Sciences, 10(2), 149–156.
Kangas, A., Kangas, J., & Pykäkäinen, J. (2001). Outranking Methods as Tools in Strategic Natural Resources Planning. Silva Fennica, 35(2), 215–227.
Keeney, R. L. (1996). Value-focused thinking: identifying decision opportunities and creating alternatives. European Journal of Operational Research, 92, 537–549.
Janssen, R., & Rietveld, P. (1990). Multicriteria analysis and geographical information systems: an application to agricultural land use in the Netherlands. In H. J. Scholten & J. C. H. Stillwell (Eds.), Geographical information systems for urban and regional planning (pp. 129–139). Dordrecht, The Netherlands: Kluwer Academic Publ.
Banai, R. (1993). Fuzziness in geographic information systems: contributions from the analytic hierarchy process. International Journal of Geographical Information Systems, 7(4), 315–329.
Dujmović, J. J., De Tré, G., & Van de Weghe, N. (2010). LSP suitability maps. Soft Computing, 14, 421–434.
Triantaphyllou, E. (2000). Multi-Criteria Decision Making Methods: A Comparative Study. Dordrecht, The Netherlands: Kluwer Academic Publ.
Dujmović, J. J., & De Tré, G. (2011). Multicriteria Methods and Logic Aggregation in Suitability Maps. International Journal of Intelligent Systems, 26(10), 971–1001.
Van Lancker, V., Francken, F., Kint, L., Terseleer, N., Van den Eynde, D., De Mol, L., et al. (2017). Building a 4D Voxel-Based Decision Support System for a Sustainable Management of Marine Geological Resources. In P. Diviacco, A. Leadbetter, & H. Glaves (Eds.), Oceanographic and Marine Cross-Domain Data Management for Sustainable Development (pp. 224–252). Hershey, USA: IGI Global.
Kint, L., & Van Lancker, V. (2016). SediLITHO@SEA v2 (06/10/2016). Database lithological descriptions, with relevance to Belgian part of the North Sea. Brussels: Royal Belgian Institute of Natural Sciences (internal report).
Van Lancker, V. (2009) SediCURVE@SEA: a multiparameter sediment database, in support of environmental assessments at sea. In: Van Lancker V. et al. (eds.) Quantification of Erosion/Sedimentation patterns to Trace the natural versus anthropogenic sediment dynamics (QUEST4D). Final Report Phase 1. Science for Sustainable Development. Brussels: Belgian Science Policy 2009, 63p + Annexes.
van Heteren, S., & Van Lancker, V. (2015). Collaborative seabed-habitat mapping: uncertainty in sediment data as an obstacle in harmonization. In P. Diviacco, P. Fox, A. Leadbetter, & C. Pshenichny (Eds.), Collaborative Knowledge in Scientific Research Networks (pp. 154–176). Hershey, USA: IGI Global.
Dujmović, J. J. (2007). Preference Logic for System Evaluation. IEEE Transactions on Fuzzy Systems, 15(6), 1082–1099.
Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.
Dujmović, J. J., & Larsen, H. L. (2007). Generalized Conjunction/Disjunction. International Journal of Approximate Reasoning, 46(3), 423–446.
De Mol, R., Tapia-Rosero, A., & De Tré G. (2015) An Approach for Uncertainty Aggregation using Generalised Conjunction/Disjunction Aggregators. In: Proc. of the IFSA/EUSFLAT 2015 conference, pp. 1499-1506, Gijón, Spain.
Chilès, J.-P., & Delfiner, P. (2012). Geostatistics – Modeling Spatial Uncertainty. New Jersey, USA: Wiley & Sons.
Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. New York, USA: Oxford University Press.
Stafleu, J., Maljers, D., Gunnink, J. L., Menkovic, A., & Busschers, F. S. (2011). 3D modelling of the shallow subsurface of Zeeland, the Netherlands. Netherlands Journal of Geosciences, 90(4), 293–310.
Soares, A. (1992). Geostatistical estimation of multi-phase structure. Mathematical Geology, 24, 149–160.
Wellmann, J. F., & Regenauer-Lieb, K. (2012). Uncertainties have a meaning: Information entropy as a quality measure for 3-D geological models. Tectonophysics, 526–529, 207–216.
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De Tré, G. et al. (2018). Data Quality Assessment in Volunteered Geographic Decision Support. In: Bordogna, G., Carrara, P. (eds) Mobile Information Systems Leveraging Volunteered Geographic Information for Earth Observation. Earth Systems Data and Models, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-319-70878-2_9
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DOI: https://doi.org/10.1007/978-3-319-70878-2_9
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