# Smart Environmental Data Infrastructures: Bridging the Gap between Earth Sciences and Citizens
## 6 Wrap-up Discussion on New Research Challenges  
This section describes a framework that defines dimensions to evaluate the progress on the achievement of the proposed nine challenges. Besides, it discusses an initial evaluation of currently available semantic approaches according to the proposed framework, and it summarizes the related geospatial technologies which might be related to future solutions for each challenge. The evaluation of the currently available semantic technologies has been synthesized in Table 1. Further details are given below for each challenge. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Semantic Approach** & \multicolumn{6}{c}{**Evaluation Dimensions**} \\ \hline
**1. Geospatial RDF Representation** & **Vector** & & & **Raster** & & **Integrated** \\ RDF & N & & N & & N & \\ GeoSPARQL & Y & & & N & & N & \\ RDF Cube & N & & & N & & N & \\ SciSPARQL & & N & & Y & & N & \\ \hline
**2. Efficient Integrated** & **Efficient** & **Efficient** & **Text** & **Text** & **Efficient** & **Efficient** & **Efficient** \\
**Semantic** & **Vector** & **Raster** & **Vector** & **Raster** & **Vector** & **Raster** & **Vector-Raster** \\
**Vector-Raster Storage** & **Encoding** & **Encoding** & **Encoding** & **Encoding** & **Access** & **Access** & **Join** \\ RDF Text Encodings & N & N & N & N & N & N & N \\ GeoSPARQL & Y & N & Y & N & Y & N & N \\ Implementations & & & & & & & \\ SciSPARQL & N & Y & N & Y & N & Y & N \\ \hline
**3. Environmental** & & & & & & & \\
**Observation and** & **Level** & **Observation** & **Modelling** & **Application** & **Sampling** & **Coverage** & **Data Quality** \\
**Modeling Ontology** & & & & & & & \\ ISO 19115 & Y & N & N & N & N & N & Y \\ GeoDCAT-AP & Y & N & N & N & N & N & N \\ Observation Models & & & & & & & \\ (O&M, ODM, etc.) & & & & & & \\ SSN & & & & & & & \\ \hline
**4. Geospatial to RDF** & & & & & & & \\
**Mappings** & & & & & & & \\ Relational to RDF & & & & & & & \\ Mappings & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Evaluation of current semantic technologies in the context of each research challenge. A geospatial RDF representation should support both vector features and raster coverages. Besides, those types of geospatial data should be supported in an integrated manner, i.e., avoiding the need for two separate model components or data structures. Notice that having separate representations for vector and raster data disables for example: (i) the representation of a raster cell (i.e., a spatial point with a specific spatial resolution) as the value of an attribute of a vector feature and (ii) the use of geometric types as data types for coverage attributes. Separate data models have been defined for vector features [8; 9; 26] and raster coverages [10] by the OGC, and such an approach is followed in general by the currently available geospatial data management technologies. In [54], an integrated data model was proposed, but a relevant implementation is not available. Regarding current semantic technologies, RDF [36] and RDF Cube [55] support semantic conventional and general