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XXX using hyperstructure for internal data |
XXX using hyperstructure for internal data |
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XXX thus, explorability. Nelson: "Look under the world, find a turtle..." |
XXX thus, explorability. Nelson: "Look under the world, find a turtle..." |
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XXX focus+context |
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We use the term hyperstructure to **denote** a **storage model** |
We use the term hyperstructure to **denote** a **storage model** |
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that allows different data structures to overlap, but to |
that allows different data structures to overlap, but to |
290 |
components are obtained by using different predicates (as dimensions) |
components are obtained by using different predicates (as dimensions) |
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in different applitudes. XXX |
in different applitudes. XXX |
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- generally layouted as 2D graph = simulation of a drawing |
Visualizations of RDF are generally a two-dimensional |
294 |
on paper |
layout of a whole graph, as if drawn on a sheet of paper. |
295 |
- graphical editors such as IsaViz [ref] often provide tools |
Graphical editors normally let the |
296 |
for automatic graph layout, and generally allow humans |
user position the individual nodes; additionally, |
297 |
to layout graphs manually |
many editors, such as IsaViz [XXXref] offer automatic |
298 |
- no f+c |
graph-layout algorithms. |
299 |
- therefore, it's always a problem that some related items |
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300 |
are on the other end of the graph |
In this kind of visualization, when looking at a particular node, |
301 |
- we describe our visualizations of rdf below (4.2.1) |
it is often not easy to find the other nodes connected to it. |
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In particular in large graphs, the node you are looking for |
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may be in a completely different part of the image. Finding |
304 |
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anything in such a visualization representing *all* the items |
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a user stores in their computer seems bound to be a herculean task. |
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We describe our focus+context visualizations of RDF |
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in section 4.2.1 [XXXlink], below. |
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