DW2RDF4SDG - Modelagem multidimensional de cubos a partir de ontologias, de acordo com os Objetivos de Desenvolvimento Sustentável
DOI:
https://doi.org/10.18046/syt.v16i44.2724Palavras-chave:
Metas de Desenvolvimento Sustentável, modelo multidimensional, data warehouse, ontologia, água.Resumo
Os modelos multidimensionais e suas medidas em relação a diferentes dimensões são ferramentas poderosas para a tomada de decisões. As ontologias, na sua expressão básica como RDF [Resource Description Framework], representam a realidade a partir das relações entre classes e constituem a base dos dados vinculados da Web Semântica. Este artigo fornece uma metodologia simples para, a partir de um modelo multidimensional de Data Warehouse, obter uma ontologia RDF que possa ser facilmente vinculada a outras ontologias dos Objetivos de Desenvolvimento Sustentável até 2030, mais especificamente para a Ontologia de Interface dos Objetivos de Desenvolvimento Sustentável [SDGIO] que está emergindo através de um esforço global impulsionado pelo Programa das Nações Unidas para o Meio Ambiente [UNEP]. A metodologia oferecida, rotulada como DW2RDF4SDG, é implementada para o Objetivo de Desenvolvimento Sustentável 6 [SDG6], que visa garantir a disponibilidade e o gerenciamento sustentável de água e saneamento para todos.
Referências
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Golfarelli, M. & Rizzi, S. (2009). Data warehouse design: Modern principles and methodologies. New Delhi, India: McGraw-Hill.
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Jha, M. K., & Chowdary, V. M. (2007). Challenges of using remote sensing and GIS in developing nations. Hydrogeology Journal, 15(1), 197-200.
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Nebot,V., Berlanga, R., Pérez, J.M, Aramburu, M. J., & Pedersen, T. B. (2009). Multidimensional integrated ontologies: A framework for designing semantic data warehouses. Lecture Notes un Computer Science, 5530: Journal on Data Semantics, 13, 1-36. Berlin-Heidelberg: Springer. doi:10.1007/978-3-642-03098-7_1.
Pinilla G. & Barón, J. (2015). Inference model for dynamic classification of monographs at university level. Sistemas & Telemática, 13(35), 23-38. doi: 10.18046/syt.v13i35.2150
Prat, N., Akoka, J., & Comyn-Wattiau, I. (2012). Transforming multidimensional models into OWL-DL ontologies. In: Research Challenges in Information Science (RCIS), 2012 Sixth International Conference on. doi:10.1109/RCIS.2012.6240451. IEEE.
Spijkers, O. (2016). The Cross-fertilization between the Sustainable Development Goals and international water law. Review of European Comparative & International Environmental Law, 25(1), 39-49. doi:10.1111/reel.12152.
United Nation [UN]. (2015). Transforming our world: The 2030 Agenda of Sustainable Development [A/RES/70/1]. Retrieved from: https://sustainabledevelopment.un.org/post15/transformingourworld/publication
United Nations Environment Programme [UNEP]. (2016). Post 2015 Note #1: Integrating the three dimensions of sustainable development. Retrieved from: http://www.unep.org/unea1/docs/UNEP%20Post%202015%20Note%201%20final.pdf
United States Geologic Survey [USGS]. (2017). Maps and GIS data. Retrieved from: https://water.usgs.gov/maps.html
Wiegleb, V. (2017). Hydro-social arrangements and paradigmatic change in water governance: an analysis of the sustainable development goals (SDGs). Sustainability Science, doi:10.1007/s11625-017-0518-1.
Wiseli, D., Tanusetiawan, R., & Purnomo, F. (2017). Simulation game as a reference to smart city management. Procedia Computer Science, 116, 468-475. doi:10.1016/j.procs.2017.10.053.
Zimányi, E., & Abelló, A. (Eds.). (2016). Lecture Notes in Business Information Processing, 253: Business intelligence: 5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015. Cham, Switzerland: Springer.
Albarrak, K. M. & Sibley, E. H. (2011). A survey of methods that transform data models into Ontology models. In: IEEE International Conference on Information Reuse & Integration, Las Vegas, NV, 2011, (pp. 58-65). doi: 10.1109/IRI.2011.6009521.
Ashraf, J., Chang, E., Hussain, O.K., & Hussain, F.K. (2015). Ontology usage analysis in the ontology lifecycle: A state-of-the-art review. Knowledge-Based Systems, 80, 34-47. doi:10.1016/j.knosys.2015.02.026
Berson, A. & Smith, S. J. (1997). Data warehousing, data mining, and OLAP. New York, NY: McGraw-Hill.
Biermann, F., Kanie, N., & Kim, R.E. (2017). Global governance by goal-setting: the novel approach of the UN Sustainable Development Goals. Current Opinion in Environmental Sustainability, 26-27, 26-31. doi:10.1016/j.cosust.2017.01.010
Carpani, F. (2000). CMDM: un modelo conceptual para la especificación de bases multidimensionales [thesis]. Universidad de la República: Montevideo, Uruguay.
Cope, M. A., & Pincetl, S. (2014). Confronting standards and nomenclature in spatial data infrastructures: A case study of urban Los Angeles county geospatial water management data. IJSDIR, 9, 36-58.
Cumming, T.L, Shackleton, R., Förster, J., Dini, J., Khan, A., Gumula, M., & Kubiszewski, I. (2017). Achieving the national development agenda and the Sustainable Development Goals (SDGs) through investment in ecological infrastructure: A case study of South Africa. Ecosystem Services, 27(B), 253-260. doi:10.1016/j.ecoser.2017.05.005.
Giupponi, C. & Gain, A.K. (2017). Integrated spatial assessment of the water, energy and food dimensions of the Sustainable Development Goals. Regional Environmental Change, 17(7), 1881-1893. doi:10.1007/s10113-016-0998-z.
Golfarelli, M. & Rizzi, S. (2009). Data warehouse design: Modern principles and methodologies. New Delhi, India: McGraw-Hill.
Hoekstra, A.J, Chapagain, A.K., & van Oel, P.R. (2017). Advancing water footprint assessment research: Challenges in monitoring progress towards Sustainable Development Goal 6. Water, 9(4), 438. doi:10.3390/w9060438.
Inmon, W.H. (2005). Building the data warehouse. Indianapolis, IN: John Wiley & Sons.
Jensen,M. (2016). Sustainable Development Goals Interface Ontology: Semantics for sustainability [ppt]. Retrieved from: http://ncgia.buffalo.edu/OntologyConference/PPT/Jensen.pdf
Jha, M. K., & Chowdary, V. M. (2007). Challenges of using remote sensing and GIS in developing nations. Hydrogeology Journal, 15(1), 197-200.
Khan, S. M., Bain, R. S., Lunze, K., Unalan, T., Beshanski-Pedersen, B., Slaymaker, T., & ... Hancioglu, A. (2017). Optimizing household survey methods to monitor the Sustainable Development Goals targets 6.1 and 6.2 on drinking water, sanitation and hygiene: A mixed-methods field-test in Belize. Plos One, 12(12), 1-18. doi:10.1371/journal.pone.0189089.
Kimball, R. & Ross, M. (2002). The data warehouse toolkit: The complete guide to dimensional modelling. New York, NY: Wiley.
Kurze, C., Gluchowski, P., & Bohringer, M. (2010). Towards an ontology of multidimensional data structures for analytical purposes. In: 43rd Hawaii International Conference on System Sciences, Honolulu, HI, (pp. 1-10). doi: 10.1109/HICSS.2010.485.
Malinowski, E. & Zimnyi, E. (2008). Advanced data warehouse design: From conventional to spatial and temporal applications (data-centric systems and applications). Berlin-Heidelberg: Springer.
Moreira, J., Cordeiro, K., Campos, M. L., & Borges, M. (2014). Ontowarehousing - Multidimensional design supported by a foundational ontology: A temporal perspective, data warehousing and knowledge discovery. In:
Lecture Notes in Computer Science, 8646: Proceedings of the 16th International Conference, DaWaK 2014, (pp. 35-44). Berlin-Heidelberg: Springer.
Mugagga, F. & Nabaasa, B.B. (2016). The centrality of water resources to the realization of Sustainable Development Goals (SDG): A review of potentials and constraints on the African continent, International Soil and Water Conservation Research, 4(3), pp. 215-223. doi:10.1016/j.iswcr.2016.05.004.
Nebot,V., Berlanga, R., Pérez, J.M, Aramburu, M. J., & Pedersen, T. B. (2009). Multidimensional integrated ontologies: A framework for designing semantic data warehouses. Lecture Notes un Computer Science, 5530: Journal on Data Semantics, 13, 1-36. Berlin-Heidelberg: Springer. doi:10.1007/978-3-642-03098-7_1.
Pinilla G. & Barón, J. (2015). Inference model for dynamic classification of monographs at university level. Sistemas & Telemática, 13(35), 23-38. doi: 10.18046/syt.v13i35.2150
Prat, N., Akoka, J., & Comyn-Wattiau, I. (2012). Transforming multidimensional models into OWL-DL ontologies. In: Research Challenges in Information Science (RCIS), 2012 Sixth International Conference on. doi:10.1109/RCIS.2012.6240451. IEEE.
Spijkers, O. (2016). The Cross-fertilization between the Sustainable Development Goals and international water law. Review of European Comparative & International Environmental Law, 25(1), 39-49. doi:10.1111/reel.12152.
United Nation [UN]. (2015). Transforming our world: The 2030 Agenda of Sustainable Development [A/RES/70/1]. Retrieved from: https://sustainabledevelopment.un.org/post15/transformingourworld/publication
United Nations Environment Programme [UNEP]. (2016). Post 2015 Note #1: Integrating the three dimensions of sustainable development. Retrieved from: http://www.unep.org/unea1/docs/UNEP%20Post%202015%20Note%201%20final.pdf
United States Geologic Survey [USGS]. (2017). Maps and GIS data. Retrieved from: https://water.usgs.gov/maps.html
Wiegleb, V. (2017). Hydro-social arrangements and paradigmatic change in water governance: an analysis of the sustainable development goals (SDGs). Sustainability Science, doi:10.1007/s11625-017-0518-1.
Wiseli, D., Tanusetiawan, R., & Purnomo, F. (2017). Simulation game as a reference to smart city management. Procedia Computer Science, 116, 468-475. doi:10.1016/j.procs.2017.10.053.
Zimányi, E., & Abelló, A. (Eds.). (2016). Lecture Notes in Business Information Processing, 253: Business intelligence: 5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015. Cham, Switzerland: Springer.
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2018-02-23
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Esta publicação está licenciada sob os termos da licença CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.pt_BR).
