Semantic Technologies for Managing Complex Product Information in Enterprise Systems

Eine, Bastian; Jurisch, Matthias; Quint, Werner

doi:10.1007/978-3-319-32799-0_9

Cited by 2 publications

(1 citation statement)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Generally, these types of data are managed with the help of a number of other types of information systems, e.g., product data management systems [4], customer relationship management systems [5], and content management systems [6]. For example, product information management systems, which had been the focus of the approach that is proposed in this paper [7], provide centralized and media-neutral data storage, data management of product information in enterprises [8]. Additionally, these systems offer a number of functions, which enable companies to manage and use product data consistently in many areas inside and outside of the enterprise.…”

Section: Introductionmentioning

confidence: 99%

Ontology-Based Big Data Management

Eine

Jurisch

Quint

2017

Systems

Self Cite

View full text Add to dashboard Cite

Big data management is no longer an issue for large enterprises only; it has also become a challenge for small and middle-sized enterprises, too. Today, enterprises have to handle business data and processes of increasing complexity that are almost entirely electronic in nature, regardless of enterprises' size. Enterprises' information systems need functions based on specific technologies to be able to reduce and interpret the complexity of business data and processes. This paper pursues the question: how can state-of-the-art information systems be improved by the use of semantic technologies, and particularly ontologies? For this purpose, three use cases of information systems that could be improved are described, and approaches based on semantic technologies and ontologies are proposed. The selected use cases relate to data integration, data quality, and business process integration.

show abstract

Section: Introductionmentioning

confidence: 99%