A Graphical Query Language: VISUAL and Its Query Processing

@article{Balkir2002AGQ,
  title={A Graphical Query Language: VISUAL and Its Query Processing},
  author={Nevzat Hurkan Balkir and Gultekin {\"O}zsoyoglu and Z. Meral {\"O}zsoyoglu},
  journal={IEEE Trans. Knowl. Data Eng.},
  year={2002},
  volume={14},
  pages={955-978}
}
This paper describes VISUAL, a graphical icon-based query language with a user-friendly graphical user interface for scientific databases and its query processing techniques. VISUAL is suitable for domains where visualization of the relationships is important for the domain scientist to express queries. In VISUAL, graphical objects are not tied to the underlying formalism; instead, they represent the relationships of the application domain. VISUAL supports relational, nested, and object… 
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28 Citations
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28 Citations

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This article presents and argues for ontology-based visual query formulation for end-users, and discusses its feasibility in terms of ontological-based data access, which virtualises legacy relational databases as RDF, and the dimensions of Big Data.

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This paper presents a novel query language called SVQL for video databases, which is developed based on an extension of the traditional database query language SQL, and extends the WHERE clause of SQL to introduce new conditional expressions, making SVQL with powerful expressiveness.

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It is shown in this paper that visualization led in this case to higher conceptual correctness and conceptual completeness in query formulation.

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Using graphically represented ontologies for searching content on the semantic Web

  • Leendert W. M. Wienhofen
  • Computer Science
    Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004.
  • 2004
This work describes an application design for using graphically represented ontologies for searching the (semantic) Web using RQL, OWL, XQL, and other query languages.

Orion: Enabling Suggestions in a Visual Query Builder forUltra-Heterogeneous Graphs

Orion, a visual interface for querying ultra-heterogeneous graphs that iteratively assists users in query graph construction by making suggestions via machine learning methods, is presented and compared with several methods adapting other machine learning algorithms.

Markku Rontu Visual queries for a student information system

A new diagrammatic visual query system named SEEQ (System for Enhanced Exploration and Querying) is presented as a tool for querying databases in general and student information systems in particular and is found to be strongest in visualisation because it is capable of result visualisations in addition to schema and query visualisations.

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