Smart Data Web: Creation of an industry knowledge base for the German industry.

The Smart Data Web project has to goal to create an industry knowledge base for the German industry.


Smart Data Web is a BMWi funded project. The central goal of the Smart Data Web project is to leverage state-of-the-art data extraction and enrichment technologies as well as Linked Data to create value-added systems for the German industry. Knowledge which is relevant to decision-making processes will be extracted from government and industry data, official web pages and social media. Then the data will be analyzed using natural language processing frameworks and then it will be integrated into knowledge graphs. These knowledge graphs will be accessible via dashboards and APIs, as well as via Linked Data. Special concern will be given to legal questions, such as data licensing as well as data security and privacy.

AKSW, which is representing the University of Leipzig in this project, will develop the Knowledge Graph, which is the central aggregation and integration interface of Smart Data Web. Unlike most current Linked Data knowledge bases, the German Knowledge Graph will focus on 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 applications.


SANSA 0.2 (Semantic Analytics Stack) Released ( 2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann)

2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann

The AKSW and Smart Data Analytics groups are happy to announce SANSA 0.2 – the second release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.2 (Semantic Analytics Stack) Released"

AKSW at ESWC 2017 ( 2017-06-12T10:53:35+02:00 Christopher Schulz)

2017-06-12T10:53:35+02:00 Christopher Schulz

Hello Community! The ESWC 2017 just ended and we give a short report of the course at the conference, especially regarding the AKSW-Group. Our members Dr. Muhammad Saleem, Dr. Mohamed Ahmed Sherif, Claus Stadler, Michael Röder, Prof. Dr. Read more about "AKSW at ESWC 2017"

Four papers accepted at WI 2017 ( 2017-06-10T15:01:31+02:00 Christopher Schulz)

2017-06-10T15:01:31+02:00 Christopher Schulz

Hello Community! We proudly announce that The International Conference on Web Intelligence (WI) accepted four papers by our group. The WI takes place in Leipzig between the 23th – 26th of August. Read more about "Four papers accepted at WI 2017"

AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data. ( 2017-05-26T13:51:11+02:00 by Diego Moussallem)

2017-05-26T13:51:11+02:00 by Diego Moussallem

At the AKSW Colloquium, on Monday 29th of May 2017, 3 PM, Diego Moussallem will present two papers related to his topic. First paper titled “Using BabelNet to Improve OOV Coverage in SMT” of Du et al. Read more about "AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data."

SML-Bench 0.2 Released ( 2017-05-11T13:01:45+02:00 by Patrick Westphal)

2017-05-11T13:01:45+02:00 by Patrick Westphal

Dear all, we are happy to announce the 0.2 release of SML-Bench, our Structured Machine Learning benchmark framework. SML-Bench provides full benchmarking scenarios for inductive supervised machine learning covering different knowledge representation languages like OWL and Prolog. Read more about "SML-Bench 0.2 Released"