Seeing the differences among position drafts

[davidm]

Hi Michael,

On Oct 17, 2:28 pm, Michael Allan <m... at zelea.com> wrote:

> > ... It could be used for annotation of text, however I would today
> > think that the user's own comment text (I support this because...),
> > followed by an actionable statement ([[supports::Budget increase for
> > daycare services]]) might be a more practical way. Please take a
> > look athttp://www.discoursedb.org, a SMW site, for a structured
> > example.
>
> This is interesting and maybe an opportunity.  I see two approaches:
>
> (A) We follow their example, and add their structural components to
> our pollwiki.
>
> (B) We offer them our own structural components.  So they add the
> following as backbone for their discussions:
>
>    i) Voting controls (vote for an act)
>   ii) Results views (see how others are voting)
>  iii) Textual diffs of positions (the stuff to discuss and debate)
>   iv) Relations among positions (tree structures of vote flow, text flow)
>
> Do I understand correctly?  Which approach seems better, A or B?

I think adding the structure components to the poll wiki would be the
way to go. A discourseDB type approach where there are yes/no vote-
able propositions, with data for and against, contributed and refined
by individuals, with the ability to link in other pages via properties
and queries, could work best for the benefits of Votorola and SMW
without trying to do too much. A diff or visual tool to compare two
pages might be useful as an add on, but only if those pages are
carefully structured. A timeline could be constructed in SMW using
tools like http://tw.rpi.edu/proj/semhis.wiki/index.php/Main_Page

There are other opportunities, but they get complicated fast. I'd
ideally want to see more of a consensus development system, where
detailed paragraphs can be mixed and edited at a semantic level, but I
don't think that's practical. Normally a minority of users would get
into great detail and the majority would skim, from my understanding
of Votorola that could be well suited as voters can drill down and act
in networks, with the visualizations helping people craft their text.

David