Visual Paradigm 102 Serial Number
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The use of query builders such as that of Figure 1 is ubiquitous within the library and information science community and has served as the primary means for expressing structured searches since the development of the first online databases. However, from a UX perspective, the approach suffers from a number of fundamental shortcomings. In this paper, we examine those shortcomings, review their implications from a design perspective, and offer a new approach based on an alternative paradigm.
In Section 2, we discuss the weaknesses of the current paradigm and review their consequences for structured searching. In Section 3, we describe alternative approaches and key design insights and principles. In Section 4, we propose a new approach which builds on related work and extends it to address a number of challenges. We conclude in Section 5 with a summary and opportunities for further work.
The use of command-line query builders currently serves as the de facto paradigm for all manner of advanced search experiences. However, despite their ubiquity, the practice of using Boolean strings to express complex information needs suffers from a number of shortcomings.
The application of data visualization to search-query formulation can offer significant benefits, such as fewer zero-hit queries, improved query comprehension, and better support for exploration of an unfamiliar database (Goldberg & Gajendar, 2008). Anick et al. (1989) is an early example of such an approach. They developed a system that could parse natural language queries and represent them as movable tiles on a two-dimensional canvas. The user could rearrange the tiles to reformulate the expression and to activate or deactivate alternative elements to modify the query. In addition, the system offered support for integration with thesauri, and it displayed the number of hits in the lower left corner of each tile.
As we discussed in Section 2, crafting syntactically correct search expressions can be an error-prone and tedious process. Line numbers, parentheses, square brackets, punctuation, whitespace characters, and Boolean operators all have the potential for errors. However, a visual representation can delegate to lower-level system functions the task of generating syntactically correct expressions. Transforming logical structure into a visual layout provides a more direct mapping between the underlying semantics and physical appearance, and it provides a more intuitive experience for users wishing to experiment with different approaches.
In this paper we have reviewed conventional approaches to structured searching and identified a number of shortcomings. We have reviewed alternative paradigms and identified key design insights and principles that help mitigate these shortcomings. In 2Dsearch, we have applied and extended these insights to develop an alternative approach to traditional command-line query builders. In particular, we have developed a framework for search-strategy formulation in which users express queries by combining objects on a two-dimensional canvas. Transforming logical structure into visual layout provides a more direct mapping between the underlying semantics and physical appearance. This helps to eliminate syntax errors, makes the query semantics more transparent, and offers new ways to optimize, share, and reproduce search strategies. The platform currently provides adapters for Google, Google Scholar, Bing, PubMed, Epistemonikos, and Trip Database. In due course, we will provide other adapters, but our next objective is to engage in a formal, user-centric evaluation, particularly in comparison to traditional query builders. We are currently engaging with the library and information science community in this regard and welcome feedback. We also invite subject-matter experts to work with us in building repositories of best practice examples and templates.
We are accustomed to thinking of the task of vision as being the construction of a detailed representation of the physical world. However, a paradigm that we term animate vision argues that vision is more readily understood in the context of the tasks that the system is engaged in, and that these tasks may not require elaborate categorical representations of the 3-D world. As an example, we show how the general problem of image interpretation can be replaced in many cases by a combination of two simpler problems, identification and search. Both tasks use multidimensional color histograms to represent the model and images. Color histograms are shown to permit efficent matching and a sufficiently rich representation to distinguish among a large number of objects. 2b1af7f3a8