Multidimensional information visualization through sliding rods

Lanning, Tom; Wittenburg, Kent; Heinrichs, Michael; Fyock, Christina; Li, Glenn

doi:10.1145/345513.345306

Cited by 11 publications

(9 citation statements)

References 12 publications

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“…Query preview [16], attribute explorer [15] and other interfaces [8], and [18] provide similar ways to explore the relationships between different facets of the classification. These interfaces worked for structured information such as database.…”

Section: Related Workmentioning

confidence: 99%

Coupling browse and search in highly interactive user interfaces: a study of the relation browser++

Zhang¹,

Marchionini²

2004

Proceedings of the 4th ACM/IEEE-CS Joint Conference on Digital Libraries

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INTRODUCTIONThe size and breadth of digital libraries makes it difficult for people to quickly grasp what content is and is not available. Consequently, people usually need an overview of the digital library to help them decide if it is worthwhile to look further. As they do look further, it is helpful for their searching and browsing to get an idea of what is in the collection and how many items are available. We believe that digital library users will be well-served by highly interactive user interfaces that support alternative views of the library partitions/collections/results sets. This paper describes a user interface that aims to provide agile control over various partitions and reports results from a user study comparing this interface to a typical library search interface.A novel interface called the Relation Browser++ (RB++) for searching and browsing large information collections was designed and investigated. RB++ provides visualized category overviews of an information space and allows dynamic filtering and exploration of the result set by tightly coupling the browsing and searching functions. A user study was conducted to compare the effectiveness, efficiency and user satisfaction of completing various types of searching and browsing using the RB++ interface and a traditional form-fillin interface for a video library. An exploration set of tasks was also included to examine the effectiveness of and user satisfaction with the RB++ when applied to a large federal statistics website. The comparison study strongly supported that RB++ was more effective and efficient for completing designed tasks, especially those of data exploration, and it gained higher satisfaction from users. The exploration study showed that the interface not only facilitated users to have better understanding of the web based information collection but also was effective and efficient to find needed information from it.Faceted category structure is one way to help people understand the composition of an information collection. A Faceted approach provides different ways to slice and dice the information space, which allows the users to look at the information space from different perspectives. Allowing people to explore the relationships among different facets may further deepen their understanding and support new insights. The relational browser (RB) is an interface which provides an overview of the collection by displaying different categories and enables people to explore the relationships among these categories [10]. The different facet values also serve as selectable objects that may be employed as query widgets for a search so that the entire space can quickly be partitioned with simple mouse moves and with consequent immediate display of the resulting partition in the results panel. Figure 1 shows an application of an early version of the relational browser in the domain of the U.S. federal statistics websites. The web pages in the site were sliced into four different facets: by topic, data type, region, and date. T...

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Section: Related Workmentioning

confidence: 99%

Coupling browse and search in highly interactive user interfaces: a study of the relation browser++

Zhang¹,

Marchionini²

2004

Proceedings of the 4th ACM/IEEE-CS Joint Conference on Digital Libraries

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“…MultiNav offers another approach for browsing multidimensional data [9]. Indeed, our method of restricting data using the value-constraint buttons described in Section 2.2 was inspired by MultiNav.…”

Section: Related Workmentioning

confidence: 99%

Interactive data summarization

Lesh

Mitzenmacher

2004

Proceedings of the Working Conference on Advanced Visual Interfaces

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Summarizing large multidimensional datasets is a challenging task, often requiring extensive investigation by a user to identify overall trends and important exceptions to them. While many visualization tools help a user produce a single summary of the data at a time, they require the user to explore the dataset manually. Our idea is to have the computer perform an exhaustive search and inform the user about where further investigation is warranted. Our algorithm takes a large, multidimensional dataset as input, along with a specification of the user's goals, and produces a concise summary that can be clearly visualized in bar graphs or linegraphs. We demonstrate our techniques in a sample prototype for summarizing information stored in spreadsheet databases.

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“…The first is MultiNav [7], which is the historical precursor to EZChooser, and the second is InfoZoom [8].…”

Section: Other Bargram Systemsmentioning

confidence: 99%

“…MultiNav research prototypes are described in [7]. The most advanced MultiNav prototype used a technique we called sliding rods as the primary interaction for multidimensional navigation.…”

Section: Other Bargram Systemsmentioning

confidence: 99%

Parallel bargrams for consumer-based information exploration and choice

Wittenburg

Lanning

Heinrichs

et al. 2001

Proceedings of the 14th Annual ACM Symposium on User Interface Software and Technology

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In this paper we introduce multidimensional visualization and interaction techniques that are an extension to related work in parallel histograms and dynamic querying. Bargrams are, in effect, histograms whose bars have been tipped over and lined up end-to-end. We discuss affordances of parallel bargrams in the context of systems that support consumer-based information exploration and choice based on the attributes of the items in the choice set. Our tool called EZChooser has enabled a number of prototypes in such domains as Internet shopping, investment decisions, college choice, and so on, and a limited version has been deployed for car shopping. Evaluations of the techniques include an experiment indicating that trained users prefer EZChooser over static tables for choice tasks among sets of 50 items with 7-9 attributes.

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Multidimensional information visualization through sliding rods

Cited by 11 publications

References 12 publications

Coupling browse and search in highly interactive user interfaces: a study of the relation browser++

Coupling browse and search in highly interactive user interfaces: a study of the relation browser++

Interactive data summarization

Parallel bargrams for consumer-based information exploration and choice

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