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The Cooperative Management of Complex Knowledge in Planning: Building a Semantic-Based Model for Hydrological Issues

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Cooperative Design, Visualization, and Engineering (CDVE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12341))

Abstract

The management of issues related to water resources, a highly complex domain, has increasingly highlighted the critical role of knowledge towards shared, useful and effective planning decisions.

Hydrology is an applied science with a very large theoretical base, its corpus borders with many others science domains. The clarification of theoretical, methodological, data, language and meaning issues and differences is of central importance. Therefore, the development of a knowledge management system with semantic extensions can meet some of the needs described.

The main objective of this work is to investigate the potential for implementing a knowledge management system with semantic extensions, as well as to propose a functional architecture.

To achieve that, first a KMS with semantic exstensions has been implemented and then the same system has been populated with an experimental knowledge content.

Furthermore, a bottom-up extraction from the KMS of a simple ontology representing the data inserted in the KMS is considered, in order to show the KMS feature of clarifying and improving inter-domain communication, to enhance a common semantic understanding.

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References

  1. Apache. https://httpd.apache.org/

  2. Extension: page\(\_\)forms. https://www.mediawiki.org/wiki/Extension:Page_Forms

  3. Extension: scribunto. https://www.mediawiki.org/wiki/Extension:Scribunto

  4. Extensions: parserhooks. https://github.com/JeroenDeDauw/ParserHooks

  5. Extensions: validators. https://github.com/DataValues/Validators

  6. Extension: templatedata. https://www.mediawiki.org/wiki/Extension:TemplateData

  7. Extension: wikieditor. https://www.mediawiki.org/wiki/Extension:WikiEditor

  8. Icu. http://site.icu-project.org/

  9. Lua. http://www.lua.org/

  10. Mediawiki. https://www.mediawiki.org/

  11. Mysql. https://www.mysql.com/

  12. Php. https://php.net/

  13. Semantic-mediawiki. https://www.semantic-mediawiki.org/

  14. Ubuntu. https://www.ubuntu.com/

  15. Virtualbox. https://www.virtualbox.org/

  16. Baldassarre, G.D., Brandimarte, L., Beven, K.: The seventh facet of uncertainty: wrong assumptions, unknowns and surprises in the dynamics of human–water systems. Hydrol. Sci. J. 61(9), 1748–1758 (2016). https://doi.org/10.1080/02626667.2015.1091460

  17. Beven, K.: Facets of uncertainty: epistemic uncertainty, non-stationarity, likelihood, hypothesis testing, and communication. Hydrol. Sci. J. 61(9), 1652–1665 (2016). https://doi.org/10.1080/02626667.2015.1031761

  18. Beven, K., Freer, J.: A dynamic TOPMODEL. Hydrol. Process. 15(10), 1993–2011 (2001). https://doi.org/10.1002/hyp.252

    Article  Google Scholar 

  19. Beven, K., Kirkby, M.: A physically based, variable contributing area model of basin hydrology/un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrol. Sci. Bull. 24(1), 43–69 (1979). https://doi.org/10.1080/02626667909491834

  20. Beven, K., Kirkby, M., Schofield, N., Tagg, A.: Testing a physically-based flood forecasting model (TOPMODEL) for three U.K. catchments. J. Hydrol. 69(1–4), 119–143 (1984). https://doi.org/10.1016/0022-1694(84)90159-8

  21. Beven, K., Lamb, R., Quinn, P., Romanowicz, R., Freer, J.: TOPMODEL, pp. 627–668. Water Resources Pubns (1995)

    Google Scholar 

  22. Borri, D., Camarda, D., Grassini, L.: Complex knowledge in the environmental domain: building intelligent architectures for water management. In: Ali, M., Esposito, F. (eds.) IEA/AIE 2005. LNCS (LNAI), vol. 3533, pp. 762–772. Springer, Heidelberg (2005). https://doi.org/10.1007/11504894_106

    Chapter  Google Scholar 

  23. Devia, G.K., Ganasri, B., Dwarakish, G.: A review on hydrological models. Aquat. Procedia 4, 1001–1007 (2015). https://doi.org/10.1016/j.aqpro.2015.02.126

    Article  Google Scholar 

  24. Endrizzi, S., Gruber, S., Dall’Amico, M., Rigon, R.: GEOtop 2.0: simulating the combined energy and water balance at and below the land surface accounting for soil freezing, snow cover and terrain effects. Geosci. Model Dev. 7(6), 2831–2857 (2014). https://doi.org/10.5194/gmd-7-2831-2014

  25. Gong, W., Gupta, H.V., Yang, D., Sricharan, K., Hero, A.O.: Estimating epistemic and aleatory uncertainties during hydrologic modeling: an information theoretic approach. Water Resour. Res. 49(4), 2253–2273 (2013). https://doi.org/10.1002/wrcr.20161

  26. Grayson, R.B., Blöschl, G., Moore, I.D.: Distributed parameter hydrologic modelling using vector elevation data: THALES and TAPES-C, Chap. 19, pp. 669–696. Water Resources Pubns (1995)

    Google Scholar 

  27. Grayson, R.B., Moore, I.D., McMahon, T.A.: Physically based hydrologic modeling: 1. a terrain-based model for investigative purposes. Water Resour. Res. 28(10), 2639–2658 (1992). https://doi.org/10.1029/92wr01258

  28. Grayson, R.B., Moore, I.D., McMahon, T.A.: Physically based hydrologic modeling: 2. is the concept realistic? Water Resour. Res. 28(10), 2659–2666 (1992). https://doi.org/10.1029/92wr01259

  29. Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing? Int. J. Hum. Comput. Stud. 43(5–6), 907–928 (1995). https://doi.org/10.1006/ijhc.1995.1081

  30. Guarino, N.: Formal ontology, conceptual analysis and knowledge representation. Int. J. Hum. Comput. Stud. 43(5–6), 625–640 (1995). https://doi.org/10.1006/ijhc.1995.1066

  31. Krueger, T., Maynard, C., Carr, G., Bruns, A., Mueller, E.N., Lane, S.: A transdisciplinary account of water research. Wiley Interdisc. Rev. Water 3(3), 369–389 (2016). https://doi.org/10.1002/wat2.1132

  32. Manfreda, S., Fiorentino, M., Iacobellis, V.: DREAM: a distributed model for runoff, evapotranspiration, and antecedent soil moisture simulation. Adv. Geosci. 2, 31–39 (2005). https://doi.org/10.5194/adgeo-2-31-2005

  33. Montanari, A., et al.: “panta rhei—everything flows”: change in hydrology and society—the IAHS scientific decade 2013–2022. Hydrol. Sci. J. 58(6), 1256–1275 (2013). https://doi.org/10.1080/02626667.2013.809088

  34. Musen, M.A.: The protégé project. AI Matters 1(4), 4–12 (2015). https://doi.org/10.1145/2757001.2757003

  35. Nearing, G.S., Tian, Y., Gupta, H.V., Clark, M.P., Harrison, K.W., Weijs, S.V.: A philosophical basis for hydrological uncertainty. Hydrol. Sci. J. 61(9), 1666–1678 (2016). https://doi.org/10.1080/02626667.2016.1183009

  36. Rigon, R., Bertoldi, G., Over, T.M.: GEOtop: a distributed hydrological model with coupled water and energy budgets. J. Hydrometeorol. 7(3), 371–388 (2006). https://doi.org/10.1175/jhm497.1

  37. Shiva, V.: Water Wars: Privatization, Pollution, and Profit. North Atlantic Books, Berkeley (2016)

    Google Scholar 

  38. Singh, V.: Hydrologic Systems, vol. 1. Prentice-Hall, New York (1988). https://books.google.it/books?id=MBVkjgEACAAJ

  39. Yates, J.S., Harris, L.M., Wilson, N.J.: Multiple ontologies of water: politics, conflict and implications for governance. Environ. Plan. D Soc. Space 35(5), 797–815 (2017). https://doi.org/10.1177/0263775817700395

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Authors and Affiliations

  1. Politecnico di Bari, Via Amendola 126/b, 70126, Bari, Italy

    Mauro Patano, Domenico Camarda & Vito Iacobellis

Authors
  1. Mauro Patano
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  2. Domenico Camarda
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  3. Vito Iacobellis
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Correspondence to Mauro Patano .

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Editors and Affiliations

  1. University of the Balearic Islands, Palma, Mallorca, Spain

    Yuhua Luo

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Patano, M., Camarda, D., Iacobellis, V. (2020). The Cooperative Management of Complex Knowledge in Planning: Building a Semantic-Based Model for Hydrological Issues. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2020. Lecture Notes in Computer Science(), vol 12341. Springer, Cham. https://doi.org/10.1007/978-3-030-60816-3_31

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  • DOI: https://doi.org/10.1007/978-3-030-60816-3_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60815-6

  • Online ISBN: 978-3-030-60816-3

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