Visual Statistics Cockpits for Information Gathering in the Policy-Making Process

Burkhardt, Dirk; Nazemi, Kawa; Stab, Christian; Steiger, Martin; Kuijper, Arjan; Kohlhammer, Jörn

doi:10.1007/978-3-642-41939-3_9

Cited by 7 publications

(3 citation statements)

References 14 publications

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“…In different projects we even extended SemaVis to support a number of different data sources, formats and data types, which enable the system to support all of the mentioned search tasks. In particular when statistical data sources such as EuroStat or statistic simulators [28], semantically enriched data sources such as DBpedia, Freebase or Eur-Lex [24], and bibliographic data sources such as EuroGraphics [29] are available for analysis purpose, it is difficult to show an initial set of visualizations that fits to all possible visualization task the user has in mind. But exactly this situation can easily be faced with our search intention analysis service that enables to predict the main intentions based on the first interaction with the system, namely querying a term or a set of terms.…”

Section: Semavis a System For Visual Information Search Exploration mentioning

confidence: 99%

Analyzing the Information Search Behavior and Intentions in Visual Information Systems

Nazemi¹,

Burkhardt²,

Kuijper³

2017

J. Computer Sci. Techno. Updates

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Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users' behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users' search intentions based on the search behavior enhanced by the application to a visual system.

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Section: Semavis a System For Visual Information Search Exploration mentioning

confidence: 99%

Analyzing the Information Search Behavior and Intentions in Visual Information Systems

Nazemi¹,

Burkhardt²,

Kuijper³

2017

J. Computer Sci. Techno. Updates

Self Cite

View full text Add to dashboard Cite

show abstract

“…This has to count for the indicator list itself and its categorical hierarchy, as well as the provision of the concrete statistical indicator data. To achieve such an interactive and explorative userinterface, we also designed a statistic cockpit approach (see therefore [16]), which allows users to orchestrate visualizations regarding the indicator hierarchy and list, as well as concrete statistical visualizations e.g. with LineCharts and ParallelCoordinates by their personal behavior and expectation.…”

Section: Statistics Visualizations Of Open Government Datamentioning

confidence: 99%

“…This allows a better considering of most of the relevant information, which are needed for an optimal decision making. For this purpose, we extend the concept of Knowledge Cockpit (for LOD [15]) and Statistic Cockpit (for OGD [16]) to a DecisionMaking Cockpit, which shows all of the previous mentioned data and visualization at the same time. This cockpit is completely dynamical and allows to compose it individually by the stakeholders.…”

Section: Multi-data and Multi-visualization Userinterfacementioning

confidence: 99%