The main issues of spatial databases and Geographic Information System (GIS), concern the representation, the management and the manipulation of a large and complex number of spatial objects and spatial relationships. In these systems many concepts are spatial and, therefore they are intrinsically related with a visual representation, which makes also easier to formulate queries by non-expert users. The main problems in visual query languages for spatial databases concern imprecision, spatial integrity and ambiguities in query formulation. Our concern in this chapter is with the ambiguity of visual geographical queries. In particular, a review of existing visual query languages for spatial databases and their classification on the grounds of the methodology adopted to resolve the ambiguity problem are provided.
Spatial databases and Geographic Information System (GIS) represent, manage and manipulate a large and complex number of spatial objects and spatial relationships.
Visual queries for spatial databases can be expressed using one of the following four approaches. The first approach uses predefined icons to retrieve pictorial information. Examples of languages that use this approach are: Cigales (Calcinelli and Mainguenaud, 1994), the language defined by Lee and Chin in (1995) and the card-based language proposed by Ju et al. (2003). The second approach specifies spatial relationships by freehand drawing. Sketch (Meyer, 1993) Spatial-Query-By-Sketch (Egenhofer, 1997; Blaser and Egenhofer, 2000), VISCO (Wessel and Haarslev, 1998), GeoPQL (Ferri and Rafanelli, 2005; Ferri et al., 2004) and, finally, the language proposed by Erwig and Schneider (2003), belong to this approach. The third approach uses symbolic images for representing a set of objects and a set of spatial relations among them. Languages that belong to this approach are Pictorial Query By Example (Papadias and Sellis, 1995), SVIQUEL (Kaushik and Rundensteiner, 1997), and the language proposed by Rahman et al. (2005). Finally, the fourth approach combines text and sketching in a hybrid solution, such as the language proposed by Szmurlo et al. (1998).
The main problems in visual query languages for spatial databases concern imprecision, spatial integrity (Favetta & Laurini, 2001) and ambiguities in query formulation. Some authors have proposed solutions to resolve ambiguities. For example, Favetta and Aufaures-Portier (2000) proposed a taxonomy for classifying different types of ambiguity during query formulation. They state that the best solution for ambiguities is a hybrid language (textual and visual) with a more intensive dialog between user and system.
Lbath et al. (1997) have proposed to resolve ambiguities through a standard for semantics using specific menus. They argue that it is possible to define the interpretation for the query and suggest a hybrid visual language named Aigle-Cigales, in which the system works with default semantics. Details should be explicitly mentioned through a specific contextual menu or by textual format.
Since ambiguity can represent a restriction for visual languages, it is very interesting to analyze several language proposals and classify them according to the methodology used to resolve the problem of ambiguity. A first group of languages, such as Pictorial Query By Example and SVIQUEL, faces ambiguity by allowing the use of a few operators and/or spatial relationships. A second group disambiguates language through the use of actions in query formulation by modifying the query semantics. The iconic language defined by Lee and Chin (1995) belongs to this group. A third group of languages tries to increase the user’s ability to formulate more complex queries by the use of several operators without facing the ambiguity problem. Languages that belong to this group are Cigales and LVIS. A fourth group of languages proposes approximate solutions as well as the exact answer to the query enabling the user to select what he/she requires. Sketch and Spatial Query By Sketch are part of this category. Finally, a fifth group of languages, such as GeoPQL, resolves ambiguities by introducing special new operators to manage them.
This chapter is structured as follows. Section 2 gives a brief overview of the approaches used for the definition of visual querying for spatial databases. Section 3 illustrates problems about ambiguity treatment in these kinds of visual languages. In section 4 a classification of different languages on the grounds of methodology adopting to resolve the problem of ambiguity is proposed. Section 5 presents some future perspectives on the growth of visual languages for spatial databases and conclusions.
Key Terms in this Chapter
Geographical Database: A database in which geographic information is store by x-y coordinates of single points or points which identify the boundaries of lines (or polylines, which sometimes represent the boundaries of polygons). Different attributes characterize the objects stored in these databases. In general the storing structure consists of “classes” of objects, each of them implemented by a layer. Often a geographic databases include raster, topological vector, image processing, and graphics production functionality.
Geographical Information System (GIS): A computerized database system used for the capture, conversion, storage, retrieval, analysis and display of spatial objects.
Metaphor: Figurative language that creates an analogy between two unlike things.? A metaphor does not make a comparison, but creates its analogy by representing one thing as something else.
Visual Query language: A language that allows the user to specify its goals in a two-(or more)-dimensional way with visual expressions - spatial arrangements of textual and graphical symbols.
Icon: Small pictures that represent commands, files, objects or windows.
Scalable Vector Graphics (SVG): SVG is a language for describing two-dimensional graphics and graphical applications in XML.
Extensible Markup Language (XML): is a W3C-recommended general-purpose markup language for creating special-purpose markup languages, capable of describing many different kinds of data. In other words, XML is a way of describing data.
Geography Markup language (GML): is the XML grammar defined by the Open Geospatial Consortium (OGC) to express geographic features. GML serves as a modeling language for geographic systems as well as an open interchange format for geographic transactions on the Internet.