Research & Innovation

When linked data applications communicate, they commonly use messaging technologies in which the message exchange itself is not represented as linked data, since it takes place on a different architectural level. When a message cannot be verified and traced on the linked data level, trust in data is moved from message originators to service providers.

In recent years, named entity linking (NEL) tools were primarily developed as general approaches, whereas today numerous tools are focusing on specific domains such as e.g. the mapping of persons and organizations only, or the annotation of locations or events in microposts. However, the available benchmark datasets used for the evaluation of NEL tools do not reflect this focalizing trend.

Residential and office buildings have the largest share in energy consumption, followed by transport and industry. At the same time, many buildings do not leverage all feasible opportunities to increase their energy efficiency. Particularly, the solutions influencing the behaviour of the end-users are lacking.

In this paper we study whether state-of-the-art techniques for multidomain and multilingual entity linking can be ported to the clinical domain.

This article introduces KRLO, an ontology of knowledge representation languages (KRLs), the first to represent KRL abstract models in a uniform way and the first to represent KRL notations, i.e., concrete models. Thus, KRLO can help design tools handling many KRLs and letting their end-users design or adapt KRLs.

We present an on-going research project addressing the problem of massive amounts of unstructured data that is generated on a daily basis in most business organisations, regardless of size. Our motivation is to support in particular small and medium seized enterprises to gain a competitive advantage in the market.

Images account for an important part of Multimedia Linked Open Data, but currently most of the semantic relations between images and other entities are based on manual semantic annotation.

We developed a quiz game that uses questions automatically generated from the Czech and English DBpedia. The game uses class membership and categorization to split DBpedia resources into domains of questions, such as persons or films. Difficulty of questions is estimated by using the indegree graph metric based on links between Wikipedia pages.

Different access control models are presented in literature for semantic data, allowing the expression and enforcement of access policies that are based on roles and other attributes of the requesting user usually.

There is an emerging demand on efficiently archiving and (temporal) querying different versions of evolving semantic Web data. As novel archiving systems are starting to address this challenge, foundations/standards for benchmarking RDF archives are needed to evaluate its storage space efficiency and the performance of different retrieval operations.