RDFreduce: Customized aggregations with provenance for RDF data based on an industrial use case

C. Lettner, M. Pichler, W. Kirchmayr, F. Kokert, M. Habringer. RDFreduce: Customized aggregations with provenance for RDF data based on an industrial use case. pages 336-340, 12, 2013.

Autoren
  • Christian Lettner
  • Mario Pichler
  • Wilhelm Kirchmayr
  • Friedrich Kokert
  • Martin Habringer
Editoren
  • E. Weippl
  • M. Indrawan-Santiago
  • M. Steinbauer
  • G. Kotsis
  • I. Khalil I.
BuchProceedings of the 5th International Conference on Information Integration and Web-based Applications & Services - iiWAS 2013
TypIn Konferenzband
ISBN978-1-4503-2113-6
Monat12
Jahr2013
Seiten336-340
Abstract

Industrial manufacturing environments are typically supported by a backbone network of technical control- and business information systems. To carry out daily work routines like maintaining technical processes or managing business information like sales and orders, different user groups as, e.g., IT management or engineers, need different forms of integrated and aggregated views on the information stored in and flowing through these systems. In this paper, we are building on recent advances in the fields of Information Integration, Semantic Web and Linked Data and report on an approach called RDFreduce to meet aforementioned needs. RDFreduce allows for the creation of custom aggregated views on heterogeneous RDF datasets. The aggregates are equipped with provenance information, in order to be tracked back easily to the datasets they origin from. An industrial use case of RDFreduce stemming from steel production especially aiming at integrating and aggregating information flows is presented.