One dimensional data most often occurs in the form of sequential
lists, often text based. Typical examples include
program listings, documents with many lines,
and document search results. Users of systems that visualize such data
will sometimes wish to further search for more specific results and at
other times will want global data about the character of the list they
are viewing or how a particular element in the list compares to
others. Additionally, access to individual elements in
long lists is expected.
The common approach to these problems is to
provide methods for scrolling through long lists until the desired
element is reached. Usually this is accompanied by some sort of
ordering system to produce labels for the data, either by page or
line, which facilitate navigation. A typical world wide web search
result illustrates all these techniques. The common frustration with
such searches also illustrates the inadequacy of such answers in the
A large part of what visual approaches have to offer are more
compact presentations and more effective responses
to user choices. Rather than compiling statistics and printing them
as part of the list or as the header, visual techniques
represent relative length or importance by line length or other visual
attributes such as color. This not only allows the representation of
much more information on a single screen, but also convenience in
comparing elements. And of course, if more fits
on a screen, the user can usually access that data much faster, either
by clicking on the desired element or first filtering the view in
order to be able to see fewer elements in more detail.
Traversing long lists in changeable sort orders.
Viewing summary data about many ordered items, possibly to find
important specific elements.
Filtering out unwanted items.
Tilebars . Content of documents are viewed within in
bars. Rectangle shading can show absence or presence of topics within
Berkeley's MVD allows
for viewing layers of a document.
Chimera, R. Value bars: An information visualization and navigation tool for
multi-attribute listings, demonstration summary appears in ACM CHI `92
Conference Proc. (Monterey, CA, May 3-7, 1992) 293-294.
Lucent Technologies Visual
Insights. See this site for SeeSoft, software visualization