Smart Data Web, a new BMWi funded project kicked-off in Berlin. Central goal of Smart Data Web is leveraging state-of-the-art data extraction and enrichment technologies as well as Linked Data to create value-added systems for German industry. Knowledge relevant to decision-making processes will be extracted from government and industry data, official web pages and social media, analyzed using NLP and integrated into knowledge graphs. These graphs will be accessible to focus industries via dashboards and APIs, as well as the public via Linked Data. Special concern will be given to legal questions, such as data licensing as well as data security and privacy.
AKSW, representing the University of Leipzig in this project, will develop the German Knowledge Graph, the central aggregation and integration interface of Smart Data Web. Unlike most current Linked Data knowledge bases, the German Knowledge Graph will focus industry-relevant data. The graph will be developed in an iterative extraction, integration and interlinking process, building on proven technologies of the Linked Data Stack. Data quality and persistence are a special priority of the German Knowledge Graph since consistency has to be guaranteed at all times. RDFUnit is our tool of choice to accomplish this task.
Smart Data Web will contribute significantly to overcome the barriers that hinder the integration of Semantic Web technologies, Web 2.0 data and data analysis for commercial application. Our partners in this project will be Beuth University of Applied Sciences, DFKI, Siemens, uberMetrics and VICO Research.
Find out more at smartdataweb.de.
Martin Brümmer on behalf of the NLP2RDF group
