Data Preparation and Enrichment
This activity can be carried out through three tools, namely DataGraft, ASIA, and ABSTAT.
DataGraft, and its data transformation tool Grafterizer, provide data management, data cleaning, modeling, preparation, and graph transformation functionalities using user-specified actions. In the picture below an overview of DataGraft platform is provided, which is a collection of tools for integrated management of transformations, hosting, and access to graph data. It is organized as a set of cloud services presented to the user through a Web portal. More details can be found in this seminal work.
ASIA is a tool for the semantic enrichment of data available in tabular formats, thus helping users in integrating business data with events and weather data. Semantic reconciliation algorithms are integrated into a user interface to help users map the data schema to shared vocabularies and ontologies and link data values to shared systems of identifiers. Data enrichment widgets exploit these links to shared systems of identifiers to ease the extraction of additional data from third-party sources and their fusion into the original tabular data. The figure below presents the instance-level annotation widget applied to a column including toponyms that use the GeoNames reconciliation service. More details on ASIA can be found here.
ABSTAT is a tool to profile knowledge graphs represented in RDF based on linked data summarization mechanisms. The profiles extracted by ABSTAT describe the content of the knowledge graphs using abstraction (schema-level patterns) and statistics. The profiles help users understand the content of the knowledge graphs used in the platform (e.g., linked product data), support ASIA’s semantic reconciliation algorithms, and provide data quality insights. The following figure shows the widget for the configuration of the annotation suggestion service. Further details can be found here.
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