# A Graph DB-Based Solution for Semantic Technologies in the Future Internet
## 4 Connection between the LPG and SW
### SPARQL Mapping
Efficiency: The integration with labeled property graphs and the utilization of native LPG endpoints for querying, in conjunction with semantic mapping, provide the efficiency characteristic of LPG systems while retaining the inherent semantic connections in RDF data. SKATEBOARD can be seen as a linker of SPARQL endpoints, which means that it can deal with resources expressed as RDF triples using a JSON-like language. The GraphBRAIN API function that can map some SPARQL queries into Cypher ones, keeping the same semantics, allows SKATEBOARD to be connected to GraphBRAIN KGs: GraphBRAIN is seen a SPARQL endpoint server which, when queried, is updated with a new piece of information that can be accessed via a public link by SKATEBOARD. A first consequence of this approach is that we can fully exploit both graph models to query data in a much more efficient way while visualizing them. Moreover, this makes the data available on the Web as RDF triples, in this way extending the set of interconnected data. ## 6 Evaluation

The evaluation of the GraphBRAIN framework and its accompanying graph exploration interface, SKATEBOARD, encompasses three main aspects: evaluation design, results, and practical implications. This comprehensive assessment aims to provide a holistic view of the capabilities, performance, and real-world applications of these systems. ### Evaluation Design

The evaluation design was thoughtfully structured to ensure a rigorous and systematic assessment of GraphBRAIN and SKATEBOARD. It consisted of the following key components:

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* **SKATEBOARD:** The evaluation of SKATEBOARD involved a combination of quantitative and qualitative data collection methods. Quantitative data included metrics such as the query response times and system resource utilization, which were critical for assessing the performance. Qualitative data, obtained through user feedback, covered aspects such as the user satisfaction, ease of use, relevance of search results, and valuable suggestions for improvements. #### 6.1.3 Methodology

* **Analytic Hierarchy Process (AHP):** To ensure a structured and comparative evaluation, the Analytic Hierarchy Process (AHP) was employed. This systematic approach, as described by [PERSON] and [PERSON] in their 2006 work [57], allowed for a methodical assessment of GraphBRAIN and SKATEBOARD against multiple criteria. The AHP facilitated a well-organized and data-driven evaluation process. #### 6.1.4 Participants

* **GraphBRAIN:** Domain experts, researchers, and developers with expertise in knowledge graph technologies actively participated in the evaluation of GraphBRAIN. Their deep understanding of the field contributed to a comprehensive analysis. * **SKATEBOARD:** SKATEBOARD's evaluation involved a diverse group of 35 users, including researchers, students, and digital library practitioners. This user base provided valuable insights into the user experience and usability aspects of SKATEBOARD. #### 6.1.5 Metrics and Criteria

* **GraphBRAIN:** The evaluation metrics for GraphBRAIN encompassed knowledge graph statistics, domain adaptability, and ontology interconnections. These criteria enabled an assessment of the system's knowledge representation and flexibility. * **SKATEBOARD:** The quantitative metrics for SKATEBOARD included the query response times, system efficiency, and overall performance. The qualitative criteria covered user satisfaction, ease of use, relevance of the search results, and suggestions for system enhancements. ### Results

The evaluation results provide valuable insights into the performance and capabilities of GraphBRAIN and its associated graph exploration interface, SKATEBOARD. This section presents the findings of the evaluation, enriched with data and visual representations where applicable. #### 6.2.1 GraphBRAIN Evaluation Results

Knowledge Graph Statistics

The GraphBRAIN Knowledge Graph (KG) currently encompasses a wealth of entities and relationships, serving as a comprehensive repository of knowledge.