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Figure: Example Databox View with some 1500 items (including wiki pages, emails, publications, and deliverables on a timeline).

Databox View

Databox View is a common-purpose visualisation view application that can interactively represent large volumes of pre-processed tabular data, conceptualised as items on a two-dimensional canvas.

In a Databox View application, each item is represented with a small rectangular icon and title, and associated with additional properties (suitable for e.g. filtering). Item data can be further decorated using simple vector graphics.

Databox View enables an efficient creation of visualisation applications. A typical application consists of two components: 1) A data processing pipeline yielding a simple item table file (in a process called itemisation) and an associated graphics file; and 2) a Databox View project file. Opening the project file launches a a Databox View application that allows visually browsing the data.

Note that the item and the graphics data typically depend on a particular data processing pipeline. Thus, the data content and the visual appearance of Databox View may change upon applications.


Requires a Java VM version 1.5 or later. Full set of features requires Java VM 1.6 or later.

Brief User Guide

The following guide explains the basic functionality of the Databox View Client, from end user point of view.

1. Navigation

Basic navigation takes place via panning (left-click + drag) and zooming (scroll wheel). Items' properties can be examined by right-clicking item icons (or Ctrl + left-click). The view may be automatically fitted using the menu "View/Fit". A quick find panel can be opened to the bottom of the view, for searching item titles via Java-like regular expressions (menu View/Find). More complex views can be set using filters.

2. Basic information

Each item is associated with property information, depending on the application. Right-clicking (or Shift/Ctrl-clicking) an item and selecting menu "Show Information..." from the item menu presents all data about a particular item in a simple dialogue. Additional menu items may also be available, depending on the application. General item information about the current Databox is available via the menu "View/Statistics...". More complex analysis can be performed in other applications; since the databox source format is a simple html table, data can be easily loaded into e.g. Web browsers and desktop spreadsheet editors.

3. Filtering

The menu "View/Filters..." opens a dialogue for filtering and highlighting view data. Filters can be used to filter out or highlight interesting general properties of the data (e.g. visualising trends), and pointing out particular values (e.g. searching or spotting outliers). Filtering is based on the idea of facet groups. Each facet group is associated with an operation (Nothing/Hide/Show/Highlight/Dim) over items, and related properties (such as informative group title, highlight color, and highlight shape). Each facet group includes facets that select items by matching item properties according to available types (Nothing|RegExp|Number). When enabled, the facet group operation takes place for items that match all of the related facets. New facet groups and facets can be created using the related menu items. Additional controls exist for moving facet groups and removing facet groups and facets. (Note that filters are currently session-based and are not saved with projects.)

For instance, view filters may be used to highlight items that include the string "Data" or "data" in their title property. This can be achieved by first adding a facet group and selecting "Highlight" for the facet group operation. To constrain the facet group to match only the intended items, the (now sole) facet of the group should be set as follows: Select "title" (or similar) as the item property being evaluated, "RegExp" as the facet type (Java regular expression syntax), and "[Da]ata" (without the parenthesis) as the facet value (setting "Data|data" etc. would also do). The Databox view is updated accordingly. Note that spotting the highlighted items might become easier by setting another highlight colour, and/or first dimming all items by adding a facet group associated with the operation "Dim". (Add new facet group, set it to "Dim", and move up in the list.)

4. Projects

Information about a particular view is managed in terms of Databox view project files (see menu "Project"). Novice end-users do not have to explicitly define projects etc. New projects are essentially defined using the "Project/Project Settings..." menu. This allows also controlling e.g. item icon and font sizes, and the visibility of decorative shapes. Errors (e.g. trying a load a project with corrupted data) are reported using the Error Console (see "View/Error Console...").

5. Data Formats and Performance

Databox view is based on two source files, typically outputted by a data processing pipeline: an item table in simplified html and decorative shapes in simplified svg. The following examples illustrate these document types (assuming correct text encodings):


Figure: Example view based on the sample sources (please note that the image is missing due a missing logo file).

Sample data.html:

x y color title type link
0 100 blue Finland Country
100 0 rgb(200,200,255) Tampere City
100 200 rgb(200,200,255) Helsinki City

Sample shapes.svg:

<svg xmlns:xlink="">
  <rect x="0" y="0" width="30" height="30" stroke="blue" fill="rgb(240,240,240)" />
  <rect x="0" y="0" width="30" height="10" stroke="blue" fill="none" />
  <image x="0" y="0" width="10" height="10" xlink:href="logo.jpg" />
  <ellipse cx="0" cy="0" rx="30" ry="10" stroke="blue" fill="rgb(230,230,240)" />
  <line x1="0" y1="100" x2="100" y2="0" stroke="blue" />
  <line x1="0" y1="100" x2="100" y2="200" stroke="blue" />
  <line x1="0" y1="100" x2="0" y2="0" stroke="blue" />
  <text x="0" y="20" fill="blue">Simple Example</text>

Databox View is capable of interactively presenting a fair amount of data. When in motion, the view is drawn adaptively, according to the CPU power available. Actual speed of the application mainly depends on the size of source data. In brief, processing is smooth when the source data fits into the main memory of the computing device and paging (etc.) is not needed. As a rule of thumb, if size of the associated properties is small, Databox view application can smoothly work with tenths of thousands of items on a workstation with a 2GB of main memory.
Topic attachments
I Attachment Action Size Date Who Comment
databox-2010-04-08.jarjar databox-2010-04-08.jar manage 110.4 K 08 Apr 2010 - 14:44 OssiNykanen  
databox-2010-04-21.jarjar databox-2010-04-21.jar manage 122.4 K 21 Apr 2010 - 15:34 OssiNykanen Quick find function added.
databox-2010-04-27.jarjar databox-2010-04-27.jar manage 125.5 K 27 Apr 2010 - 09:14 OssiNykanen New highlight shapes, logo fix
format-example.jpgjpg format-example.jpg manage 8.6 K 27 Apr 2010 - 10:01 OssiNykanen View of the format example
oks-databox-small.jpgjpg oks-databox-small.jpg manage 54.5 K 08 Apr 2010 - 14:30 OssiNykanen Databox OPAALS D6.11 example
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Topic revision: r23 - 24 Feb 2011 - 12:38:05 - OssiNykanen


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