HVQS: The Hierarchical Visual Query System for Databases

Chen, Ping Kuen; Chen, Gwo Dong; Liu, Baw Jhiune

doi:10.1006/jvlc.1999.0140

Cited by 7 publications

(4 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, research on visual query formulation is longstanding; however, early approaches such as QBE (Query by Example) [189], QBD* (Query by Diagram) [4], Visionary [15], TableTalk [61], HVQS [41], VKQS [153], VISUAL [9], X-VIQU [43], Xing [62] and XQBE [26] employ database schemas, object-oriented models, semistructured models (e.g., XML), proprietary graph-based models, etc. Experimental research shows that approaches that rely on logical models (e.g., database schemas) are not as effective as conceptual approaches, where interaction is in terms of real world concepts [154].…”

Section: Research Landscape and Directionsmentioning

confidence: 99%

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Soylu

Giese

Jiménez-Ruiz

et al. 2016

Univ Access Inf Soc

View full text Add to dashboard Cite

Value creation in an organisation is a timesensitive and data-intensive process, yet it is often delayed and bounded by the reliance on IT experts extracting data for domain experts. Hence, there is a need for providing people who are not professional developers with the flexibility to pose relatively complex and ad hoc queries in an easy and intuitive way. In this respect, visual methods for query formulation undertake the challenge of making querying independent of users' technical skills and the knowledge of the underlying textual query language and the structure of data. An ontology is more promising than the logical schema of the underlying data for guiding users in formulating queries, since it provides a richer vocabulary closer to the users' understanding. However, on the one hand, today the most of world's enterprise data reside in relational databases rather than triple stores, and on the other, visual query formulation has become more compelling due to ever-increasing data size and complexity-known as Big Data. This article presents and argues for ontology-based visual query formulation for end users; discusses its feasibility in terms This research is funded by the Seventh Framework Program (FP7) of the European Commission under Grant Agreement 318338, "Optique".

show abstract

Section: Research Landscape and Directionsmentioning

confidence: 99%

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Soylu

Giese

Jiménez-Ruiz

et al. 2016

Univ Access Inf Soc

View full text Add to dashboard Cite

show abstract

“…However, the definition of D-VISUAL in Section 3 is not safe, i.e., may produce infinite output or may take infinite time to evaluate. For safety, in D-VISUAL, we do not allow built-in predicates of type (6) and use the following restrictions:…”

Section: Formal Properties For Nonrecursive Relational Visualmentioning

confidence: 99%

“…The logic also supports reasoning about query subsumption and applying default knowledge. In [6], the design and implementation of hierarchical visual query system (HVQS) is described where users visually formulate a query and watch the query results on a few hierarchically arranged higher layers (i.e., a hierarchical graph) of database schema.…”

Section: Recent Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A graphical query language: VISUAL and its query processing

Balkir

Özsoyoǧlu

Özsoyoğlu

2002

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

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-oriented models naturally and has formal basis. For ease of understanding and for efficiency reasons, two VISUAL semantics are introduced, namely, the interpretation and execution semantics. Translations from VISUAL to the Object Query Language (for portability considerations) and to an object algebra (for query processing purposes) are presented. Concepts of external and internal queries are developed as modularization tools.

show abstract

Iconic SQL: Practical Issues in the Querying of Databases through Structured Iconic Expressions

Narayanan

Shaman

2002

Journal of Visual Languages & Computing

View full text Add to dashboard Cite

HVQS: The Hierarchical Visual Query System for Databases

Cited by 7 publications

References 35 publications

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

Ontology-based end-user visual query formulation: Why, what, who, how, and which?

A graphical query language: VISUAL and its query processing

Iconic SQL: Practical Issues in the Querying of Databases through Structured Iconic Expressions

Contact Info

Product

Resources

About