In this paper, we present the Ontology Matching EvaLuation Toolkit (MELT), a software toolkit to facilitate ontology matcher development, configuration, evaluation, and packaging. Compared to existing tools in the ontology matching domain, our framework offers detailed evaluation capabilities on the correspondence level of alignments as well as extensive group evaluation possibilities. A particular focus is put on a streamlined development and evaluation process along with ease of use for matcher developers and evaluators. Our contributions are twofold: We present an open source matching toolkit that integrates well into existing platforms, as well as an exemplary analysis of two OAEI 2018 tracks demonstrating advantages and analytical capabilities of MELT.

Knowledge Graph Embeddings, i.e., projections of entities and relations to lower dimensional spaces, have been proposed for two purposes: (1) providing an encoding for data mining tasks, and (2) predicting links in a knowledge graph. Both lines of research have been pursued rather in isolation from each other so far, each with their own benchmarks and evaluation methodologies. In this paper, we argue that both tasks are actually related, and we show that the first family of approaches can also be used for the second task and vice versa. In two series of experiments, we provide a comparison of both families of approaches on both tasks, which, to the best of our knowledge, has not been done so far. Furthermore, we discuss the differences in the similarity functions evoked by the different embedding approaches.

In this demo, we introduce MELT Dashboard, an interactive Web user interface for ontology alignment evaluation which is created with the existing Matching EvaLuation Toolkit (MELT). Compared to existing, static evaluation interfaces in the ontology matching domain, our dashboard allows for interactive self-service analyses such as a drill down into the matcher performance for data type properties or into the performance of matchers within a certain confidence threshold. In addition, the dashboard offers detailed group evaluation capabilities that allow for the application in broad evaluation campaigns such as the Ontology Alignment Evaluation Initiative (OAEI).