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The Web Within: Leveraging Web Standards and Graph Analysis to Enable Application-Level Integration of Institutional Data

  • Luiz GomesJr.
  • André Santanchè
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8990)

Abstract

The expansion of the Web and of our capacity of producing and storing information have had a profound impact on the way we organize, manipulate and share data. We have seen an increased specialization of database back-ends and data models to respond to modern application needs: text indexing engines organize unstructured data, standards and models were created to support the Semantic Web, Big Data requirements stimulated an explosion of data representation and manipulation models. This complex and heterogeneous environment demands unified strategies that enable data integration and, especially, cross-application, expressive querying.

Here we present a new approach for the integration of structured and unstructured data within organizations. Our solution is based on the Complex Data Management System (CDMS), a system being developed to handle data typical of complex networks. The CDMS enables a relationship-centric interaction with data that brings many advantages to the institutional data integration scenario, allowing applications to rely on common models for data querying and manipulation.

In our framework, diverse data models are integrated in a unifying RDF graph. A novel query model allows the combination of concepts from information retrieval, databases, and complex networks into a declarative query language that extends SPARQL. This query language enables flexible correlation queries over the unified data, enabling support for a wide range of applications such as CMSs, recommendation systems, social networks, etc. We also introduce Mappers, a data management mechanism that simplifies the integration of heterogeneous data and that is integrated in the query language for further flexibility. Experimental results from real data demonstrate the viability of our approach.

Keywords

Query model integration Data integration DB/IR Integration Graph data models Graph query languages Complex data 

Notes

Acknowledgments

The authors would like to thank Prof. Frank Wm. Tompa for feedback and encouragement in earlier stages of this work. This work was partially financed by the Microsoft Research FAPESP Virtual Institute (NavScales project), CNPq (MuZOO Project and PRONEX-FAPESP), INCT in Web Science (CNPq 557.128/2009-9) and CAPES, with individual grants from CAPES and FAPESP (process 2012/15988-9).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Institute of ComputingUniversity of Campinas (UNICAMP)CampinasBrazil

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