Bridging the gaps towards advanced data discovery over semi-structured data

Sivan Yogev, Haggai Roitman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In this work we argue that two main gaps currently hinder the development of new applications requiring sophisticated data discovery capabilities over rich (semi-structured) entity-relationship data. The first gap exists at the conceptual level, and the second at the logical level. Aiming at fulfilling the identified gaps, we propose a novel methodology for developing data discovery applications. We first describe a data discovery extension to the classic ER conceptual model termed Entity Relationship Data Discovery (ERD 2). We further present a novel logical model termed the Document Category Sets (DCS) model, used to represent entities and their relationships within an enhanced document model, and describe how data discovery requirements captured by the ERD 2 conceptual model can be translated into the DCS logical model. Finally, we propose an efficient data discovery system implementation, and share details of two different data discovery applications that were developed in IBM using the proposed methodology.

Original languageEnglish
Title of host publicationConceptual Modeling - 31st International Conference, ER 2012, Proceedings
Number of pages10
StatePublished - 8 Nov 2012
Event31st International Conference on Conceptual Modeling, ER 2012 - Florence, Italy
Duration: 15 Oct 201218 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7532 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference31st International Conference on Conceptual Modeling, ER 2012


  • Conceptual modeling
  • data discovery
  • entity relationship

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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