This paper focuses on the concept of data spaces, which can serve as a basis for the future
data economy. In data spaces, applicable to various business domains, stakeholders will be …

In recent years, the efforts of both governmental and commercial institutions to exchange
and publish data have significantly increased. Data published by these institutions is usually …

Schema matching is a process that serves in integrating structured and semi-structured data.
Being a handy tool in multiple contemporary business and commerce applications, it has …

A semantic model of a data source is a representation of the concepts and relationships
contained in the data. Building semantic models is a prerequisite to automatically publishing …

In recent years, the impact and usability of semantic data management has increased
continuously. Still, one limiting factor is the need to create a semantic map** in the form of …

Analyzing and modeling the implicit semantic relationships in data sources is the key to
achieving integration and sharing of heterogeneous data information. However, manual …

The schema matching problem is at the basis of integrating structured and semi-structured
data. Being investigated in the fields of databases, AI, semantic Web and data mining for …

Oceanographic research is a multidisciplinary endeavor that involves the acquisition of an
increasing amount of in-situ and remotely sensed data. A large and growing number of …

In recent years, geometric deep learning methods have been proposed, which are called
Graph Convolutional Neural Networks (GCNNs). GCNNs not only can extract effective …

Ontology-based data management and knowledge graphs have emerged in recent years as
efficient approaches for managing and utilizing diverse and large data sets. In this regard …