Abstract
In order to achieve the SDGs (Sustainable Development Goals), society must be able to consume open data to be aware of environmental situations. However, the existence of many related heterogeneous open data sets hampers citizens to use them to rise environmental awareness. In order to overcome this scenario, in this paper, we introduce a model-driven approach to automatically generate Web Augmenters that (i) homogeneously access environmental open data, and (ii) visualize this data while users are surfing the Web. In order to show the feasibility of our approach a case study is defined, based on generating a Web Augmenter that uses open data and Wikipedia related to “Mar Menor” coastal lagoon; a highly anthropized ecosystem located in South-East Spain.
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Acknowledgements
This research has been funded by project projects TED2021-130890B funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR, and Ramon y Cajal Grant RYC2018-025580-I, funded by MCIN/AEI/10.13039/501100011033, “FSE invest in your future” and “ERDF A way of making Europe”.
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González-Martínez, P., González-Mora, C., Garrigós, I., Mazón, JN., Cecilia, J.M. (2023). Towards a Model-Driven Development of Environmental-Aware Web Augmenters Based on Open Data. In: Garrigós, I., Murillo Rodríguez, J.M., Wimmer, M. (eds) Web Engineering. ICWE 2023. Lecture Notes in Computer Science, vol 13893. Springer, Cham. https://doi.org/10.1007/978-3-031-34444-2_29
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DOI: https://doi.org/10.1007/978-3-031-34444-2_29
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