Sprache: English
HINs aim to represent heterogeneous data in a information-rich, semantically correct way,
thus enabling successful analysis to obtain new information about the modeled data.
Creating an effective HIN requires close collaboration between domain experts and
computer scientists to accurately transform tabular data into a network structure. Nodes
represent combinations of feature values, with edges representing their semantic
relationships.
Standardized ontologies, along with authority files and controlled vocabularies, are
essential tools for consistent modeling of diverse datasets as HINs. Through these
standards, successful integration of datasets is ensured, leading to an enriched underlying
knowledge base
This Poster offer a new relation-based perspective on the modeled data. Analyzing them may reveal hidden insights by examining the
network’s link structure. Meta paths—sequences of relationship types—capture complex higher-order relationships between object types
in the network. Each meta path represents a specific semantic relationship and can be used for network analysis.
Research Assistant at the German Mining Museum