Semantic Research Projects

The european project consortium develops a financial awareness platform that will be publicly available. The smart application shall improve the financial literacy of various user groups ranging from teenagers, mid-career professionals to retirees.

The agricultural industry shares huge amounts of data and embraces
Linked Data technologies to a large extend. This research project aims to improve semantic data processing in the agricultural ecosystem by aligning different data models across semantic information infrastructures.

The research consortium is tackling a central challenge at the core of data business. The digital data landscape with its various offerings for data reuse come along with a whole string of legal concerns that strongly vary depending on the licenses and geographic region. DALICC will provide a semantic application that allows users to generate license relevant information automatically and reuse it in legal document templates.

This research project aims to improve industrial resource and energy usage through semantic real-time data analytics. Linked Data technologies bear the potential to ease the process of very heterogeneous data processing. Based on use cases from leading global industry giants as Siemens and Bilfinger, a data analytics application will be provided.

Language ambiguity remains one of the hardest technical challenges when it comes to NLP tools and applications. In this research project, we make lexicographic data reusable for cognitive solutions.

Software and Data Engineering depend on each other, but are conventionally worked on separately. This generates frictions on an application level. The research project Aligned is developing methods & tools that will bring the complementary disciplines closer together.

LOD2 is by far the largest executed Linked Data research project. The W3C standards-based Linked Data technology stack was substantially expanded to meet the needs of enterprise data management. The technical enhancements were derived in cooperation with industry partners.

The research project will provide a blueprint for a Big Data enterprise architecture that is strongly shaped by a semantic layer. One of the biggest challenges in Big Data management remains the agile and dynamic usage of available resources. Making metadata management crucial to a Big Data strategy will close the gap of data availability and utilisation.

We conducted with the business and technical university of Vienna, as well as the market research institute IDC a market survey to gain insights how Linked Data technologies can address the most urgent business challenges of various industries.

This research project is dedicated to establish data standards and data quality tools to make Linked Open Data resources reusable for software vendors and application providers. The goal is to ensure that data freshness can be monitored and the data processing from third-party vendors gets increasingly automated.