Chapter

Web-Age Information Management

Volume 6897 of the series Lecture Notes in Computer Science pp 353-365

Layered Graph Data Model for Data Management of DataSpace Support Platform

  • Dan YangAffiliated withCarnegie Mellon UniversitySchool of information Science&Engineering, Northeastern UniversitySchool of Software, University of Science and Technology
  • , Derong ShenAffiliated withCarnegie Mellon UniversitySchool of information Science&Engineering, Northeastern University
  • , Tiezheng NieAffiliated withCarnegie Mellon UniversitySchool of information Science&Engineering, Northeastern University
  • , Ge YuAffiliated withCarnegie Mellon UniversitySchool of information Science&Engineering, Northeastern University
  • , Yue KouAffiliated withCarnegie Mellon UniversitySchool of information Science&Engineering, Northeastern University

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Abstract

In order to effective management of heterogeneous data sources in dataspace and provide more high quality services, proposing a unified data model to represent all kinds of data in a simple and powerful way is the foundation of DataSpace Support Platform (DSSP). So we propose a novel layered graph Data Model (called lgDM) which includes Entity Data Graph (GD) and Entity Schema Graph (GS) to capture both associations among entities and associations among entity classes. Moreover we also propose an association mining strategy to try to incrementally find associations with less manual effort. We conduct experiments to evaluate the efficiency and effectiveness of our proposed data model.

Keywords

layered graph data model association dataspace