I would say that the scenario connector uses a specific, but very composable and extensible data model, to try to be a platform for other applications. If you can imagine importing a plug-in that says “if something is tagged like this, I will interpret the structures around it in a particular way”. So, while the Compendium aims to be extensible at the level of the tool, scenario connectors serve as a platform for other applications.

Unfortunately there is no alpha build yet. I am still researching the libraries I’m going to use for the user-interface and the underlying peer-to-peer filesystem. However, the requirements document contains far more than just requirements, but instead is a largely comprehensive view of the current state of ScenConnect. If you want to know more, I recommend you check it out: (http://scen-connect.cvs.sourceforge.net/*checkout*/scen-connect/sc-documentation/sc-documentation/requirements/ScenConnectRequirements.pdf)

Also, don’t hesitiate to email me personally.

Scenario connectors are a platform that sits on top of the more technical distributed overlay file-sharing platforms, providing both an end-user interface and a scenario/scoring resource. I’d love to see scenario connectors serving a peer role with other applications, supporting connectivity to-and-from web browsers via plug-ins, to-and-from editors such as Eclipse, to-and-from computer games (providing the scoring system, and seeing what paths people choose under those conditions).

In other words, I want to keep the tool open to the opportunities that come from not being a specific methodology.

It sounds like a tremendous tool for distributed decisions and narrative building, and the future developments seem quite interesting. Is there an alpha build of the underlying software available yet?

Mark, your question is a good one. Compendium looks like a very capable tool, and it may have many of the advantages of the scenario connector technique.

I cannot claim any specific expertise in issue mapping. My background is in developing learning, planning, and visualization tools for data streams of information. However, my understanding is that the central difference between scenario connecting and other mapping techniques is the focus on using implicit connectivity by aggressively formulating the system as bundles and connection of tags. By allowing a free composition of situations, events, tags, scores, markets, and communications, we can let machine learning algorithms allow for the quick creation by remixing existing tag sets and fast comparison by evaluating the differences between nested networks of tag sets. It also can capture some of the subtle nature of scoring: If you want to say “Bob has good opinions unless you ask him about the Israel-Palestine conflict”, then this is a matter of tagging the high score you usually give Bob with a ‘Israel-Palestine’ tag and then scoring that tag lower.

As a result of this aggressive move towards tagging, scenario connector technology is directly aimed to be ready for developments in geotagging, RFID, and related ubiquitous computing technologies. By already having a network of tags accessible, this tool aims to be able to compare these tags to the surrounding environment, so that you can see how current decisions you might have to make map into the scenarios you’re interested in. While internet technologies have brought us “ambient findability”, I hope that tools like this will bring us “ambient situatedness”.

Is the method of scenario connecting very different from other kinds of mapping?