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Journal on Data Semantics OnlineFirst articles

11.06.2018 | Original Article

Topic Summary Views for Exploration of Large Scholarly Datasets

In this article, we present the E-sch approach for exploration of large scholarly datasets based on topic summary views. The goal of E-sch is to semantically summarize the dataset related to a potentially very large number of scholar publications …

22.05.2018 | Original Article

SPARQL Query Containment Under Schema

Query containment is defined as the problem of determining if the result of a query is included in the result of another query for any dataset. It has major applications in query optimization and knowledge base verification. To date, testing query …

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With the Web serving as a huge worldwide data repository, issues related to data semantics (familiar to database modelers since the 1970s) have again become of paramount importance. As Web data comes from heterogeneous, possibly unknown and mostly uncontrolled sources, it is anything but obvious how the information beyond the most basic factual data can be correctly understood. The same concern applies to data that is exchanged between systems that need to agree on its meaning in order to avoid dangerous misunderstandings. Semantic elicitation and the availability of appropriate semantic metadata are the key to the meaningful use of information in modern distributed environments.

The Journal on Data Semantics (JoDS) provides an international high-quality publication venue for researchers whose themes cover issues related to information semantics. Its target domain ranges from theories supporting the formal definition of semantic content to innovative domain-specific applications of semantic knowledge, thus covering work done on conceptual modeling, databases, Semantic Web, information systems, workflow and process modeling, ontologies, business intelligence, interoperability, mobile information services, data warehousing, knowledge representation and reasoning, and artificial intelligence.

Topics of relevance to this journal include (but are not limited to):

  • Conceptualization, knowledge representation and reasoning
  • Conceptual data, process, workflow, and event modeling
  • Provenance, evolution and change management
  • Context and context-dependent representations and processing
  • Multi-model and multi-paradigm approaches
  • Mappings, transformations, reverse engineering and semantic elicitation
  • Semantic interoperability, semantic mediators and metadata management
  • Ontology models and languages, ontology-driven applications
  • Ontology, schema, data and process integration, reconciliation and alignment
  • Web semantics and semi-structured data
  • Integrity description and handling
  • Semantics in data mining and knowledge extraction
  • Semantics in business intelligence, analytics and data visualization
  • Spatial, temporal, multimedia and multimodal semantics
  • Semantic mobility data and services for mobile users
  • Supporting tools and applications of semantic-driven approaches

Submissions may qualify as research papers, survey articles, industry papers, position papers, or short communications, and should contain original material that has not been submitted or published elsewhere.

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Product Lifecycle Management im Konzernumfeld – Herausforderungen, Lösungsansätze und Handlungsempfehlungen

Für produzierende Unternehmen hat sich Product Lifecycle Management in den letzten Jahrzehnten in wachsendem Maße zu einem strategisch wichtigen Ansatz entwickelt. Forciert durch steigende Effektivitäts- und Effizienzanforderungen stellen viele Unternehmen ihre Product Lifecycle Management-Prozesse und -Informationssysteme auf den Prüfstand. Der vorliegende Beitrag beschreibt entlang eines etablierten Analyseframeworks Herausforderungen und Lösungsansätze im Product Lifecycle Management im Konzernumfeld.
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