Semantic Enhancement for Enterprise Data Management

  • Authors:
  • Li Ma;Xingzhi Sun;Feng Cao;Chen Wang;Xiaoyuan Wang;Nick Kanellos;Dan Wolfson;Yue Pan

  • Affiliations:
  • IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094;IBM China Research Laboratory, Beijing, China 100094;IBM Software Group, USA 78758-3415;IBM Software Group, USA 78758-3415;IBM China Research Laboratory, Beijing, China 100094

  • Venue:
  • ISWC '09 Proceedings of the 8th International Semantic Web Conference
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Taking customer data as an example, the paper presents an approach to enhance the management of enterprise data by using Semantic Web technologies. Customer data is the most important kind of core business entity a company uses repeatedly across many business processes and systems, and customer data management (CDM) is becoming critical for enterprises because it keeps a single, complete and accurate record of customers across the enterprise. Existing CDM systems focus on integrating customer data from all customer-facing channels and front and back office systems through multiple interfaces, as well as publishing customer data to different applications. To make the effective use of the CDM system, this paper investigates semantic query and analysis over the integrated and centralized customer data, enabling automatic classification and relationship discovery. We have implemented these features over IBM Websphere Customer Center, and shown the prototype to our clients. We believe that our study and experiences are valuable for both Semantic Web community and data management community.