Yes, what you're describing is Chandler's data model which is then
enriched with a content model that understands about specific kinds
of user data and specific types of relationships between items.
The proposed topic of this thread was to explore ways of visualizing
this data/content model in a way that is easily comprehensible for
both personal use as well as collaboration.
You can import information of all sorts into the highly generic
framework of relations described as use types, linktypes, uses,
links and their attributes. Then all of them are intrinsically
interoperable. And my point is that these generic notions can
provide the conceptual backbone for the interface, a framework
that is easily understandable, which you make accessible to the
user within any interface you build.
It feels like there are a couple of threads running through your
comments below, let me see if I can address them individually (please
correct me if I misrepresent what you said):
+ I agree that our approach is to focus on end-user comprehension of
data visualizations.
+ I agree that this approach is not at odds with ideas about mind-
mapping. Instead it is intended to improve on mind-mapping UIs.
+ The generic framework you describe exists today in Chandler's data
model (see comments above). I think I was a little confused by your
comments because that wasn't the proposed topic of this thread.
+ In your last point, are you saying that mind-mapping IS easily
comprehensible without further improvements? This would be
interesting to explore further in relation to the design principles
laid down in the wiki write-ups.
I mean the way you're thinking is in terms of trying to find some
functionality that the app will provide, that will do the
simplifying for grokking that you seek. I suggest that thinking
this way foreshortens:
1) for mindmapping, seeing that it's the particular kind of
functionality it provides that makes it valuable, moreso than the
criterion of how well some functionality intended to simplify
grokking, meshes with mindmapping functionality;
2) thinking about how more genericity in conceptualizing
information, not some function, might give you a better framework
for getting to better grokkability; and
3) for mindmapping again, seeing that mindmaps are great for
grokking on the basis of seeing nodes' grouping and arranging and
interpreting that as a human, rather than the app understanding
the grouping and arrangement.
Seth
Mimi
On Jan 20, 2006, at 4:58 AM, Seth Johnson wrote:
See my comments at:
http://wiki.osafoundation.org/bin/view/Journal/
TheProblemWithHeterogeneousInformation
http://wiki.osafoundation.org/bin/view/Journal/ChunkingOverTime
Seth
Seth Johnson wrote:
It is possible to think of mindmaps as relations.
One-to-many
relations of a parent to children.
I think of relations as particular instances (a "use") of a
"use
type" (the parent or "one" side of a one-to-many relation),
combined with multiple items ("links") of a "link type"
(the
child or "many" side).
So let's say you have a mindmap of a project to organize a
conference on the "unitary executive theory."
The Use type would be "Project"
The Link type would be "Task"
The Use would be "Organize Unitary Executive Conference"
The Links would be individual tasks.
Or:
The parent or "one" entity is "Projects"
The child or "many" entity is "Tasks"
The links, the "tasks" here, need to be outlinable (unlike
the
traditional flat table relational data structure). Hence
they
would be mindmappable.
But you can speak generically about relations in terms of
use
types, uses, link types and links. I refer to a specific
use
type combined with a specific link type as a "context."
Since this is a universal data structure, you can put
everything
in it, and since you can outline, you can mindmap as well.
Of course, mindmapping doesn't presuppose that the child
nodes
are just one entity type. This is just a good generic way
of
talking about and understanding how to model things.
If in fact you want the nodes to be multi-use, you call the
link
type something that conveys that, like "Project component,"
and
the associated attributes would be used to designate what
kind of
node they are.
The main thing is that you can speak generically about all
relations with these terms, knowing that all application
data can
fit the abstractions. You just designate the context in
terms of
specific use types combined with specific link types.
Seth
Seth Johnson wrote:
Build a universal data store, and if it provides for
outlining,
you can put a mindmapping front end on it.
I would use the mindmapping interface. The key isn't so
much
what features will communicate as much as possible, as it
is the
radial arrangement of manipulable nodes around a center.
It can replace the table, so long as your architecture
provides
for outlining. In fact, I endorse the idea of distributed
data
architectures that essentially distribute metadata about
relations among "entities" while leaving attribute values
in
place at various servers.
Seth
Mimi Yin wrote:
The recent posts about mind-mapping make for a good
segue to some
research and writing I've done on the topic of how to
present gobs of
heterogeneous data in ways that let you immediately grok
it, wrap
your head around it, get the big picture, see the forest
for the
trees (pick your favorite cliche)...
Information technology has done a lot in the realm of
making it
really easy to create and disseminate lots of data.
However, we
haven't made much progress in the realm of improving the
way we
consume that data in aggregate. The problem of
organizing,
categorizing, and making information more accessible is
simply a
symptom of a larger and deeper problem:
When we look at large piles of data (without looking at
each data
point and parsing it in our heads and then flagging it,
starring it,
tagging it, filing it or categorizing it in some way) we
have no idea
what we're looking at, it's all a big mile of opaque
mush to us.
We can continue down this path of manually getting a
grip on our
data, one data point at a time. Or we can explore ways
to serve up
data in ways that are more transparent and "more
comprehensible in
aggregate".
Mind-mapping is one of them, but still in its infancy as
far as
becoming an universally useful tool (capable of
replacing the table
for example.)
Here are some essays exploring why it is that "data in
aggregate" (as
presented in lists and tables and text blobs) is so hard
to "get" and
some ideas about how to make it easier to digest.
http://wiki.osafoundation.org/bin/view/Journal/
ClassificationPaperOutline2
In particular:
http://wiki.osafoundation.org/bin/view/Journal/
TheProblemWithHeterogeneousInformation
ht
p://wiki.osafoundation.org/bin/view/Journal/PrinciplesOfGrok
http://wiki.osafoundation.org/bin/view/Journal/
WhyIsDataSoHardToGrok
http://wiki.osafoundation.org/bin/view/Journal/
LookingToThePhysicalWorld
http://wiki.osafoundation.org/bin/view/Journal/TheUseOfColor
http://wiki.osafoundation.org/bin/view/Journal/ChunkingOverTime
http://wiki.osafoundation.org/bin/view/Journal/OneUppingNature
I realize this is a lot of material, it took me a long
time even to
get to this preliminary draft, but any comments and
feedback would be
appreciated. Please ping me though if you do add
comments. Thx, Mimi
On Jan 19, 2006, at 10:02 AM, Reid Ellis wrote:
Open source, GPL'ed mindmapping tool for those who
want to explore
this:
http://freemind.sourceforge.net
Versions available for Mac, Windows, Linux (Debian,
SuSe, and other
rpm-based Linux).
Probably not as polished as the official Buzan version
(although
Buzan's http://www.mind-map.com seems to be down). But
it might
give people more ideas.
Reid
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