Model-Driven Development of Web Augmenters for Facilitating Environmental Open Data Consumption

Citizens must consume open data published by public institutions to be aware of environmental issues of SDGs (Sustainable Development Goals). However, the existence of many related heterogeneous open data sets hampers citizens to access and consume them to raise environmental awareness. To overcome this scenario, in this paper, we introduce a model-driven development approach to automatically generate maps as web augmenters to allow citizens to surf the Web while they 1) homogeneously access environmental open data, and 2) easily visualize this data on the map. To show the feasibility of our approach, we focus on a case study of biodiversity maps, which are related to SDG 14 (life below water), and 15 (life on land). Through this case study, a web augmenter applied to Wikipedia is automatically generated from environmental open data related to “Mar Menor” coastal lagoon; a highly anthropized ecosystem located in Southeast Spain. A focus group is conducted to validate that our generated web augmenter is easy to use and useful for environmental open data consumption.