Doctoral Consortium – Paper 4
Scientific data is being acquired in high volumes in support of studies in many knowledge areas. Regular data analytics processes make use of datasets that often lack enough knowledge to facilitate the data user work. By relying on knowledge graphs (KGs), those difficulties can be mitigated. This research focuses on enabling data analytics over scientific data in light of knowledge available in KGs with the intent of facilitating data discovery, supporting contextual analysis, inferring semantic differences between data points and leveraging automatic data visualization.