January in Seattle

The speaker's list at Bibletech 2008 is posted. I will be speaking there on - ha - guess what!

Visualizing Micro and Macro Structures in Scripture.

I will be presenting some selected diagrams of Hebrew poetry showing both internal and external structure. This presentation’s theme will not be getting things done 'faster', but the sustained learning process that a web-based software framework allows over long periods of time. The talk will also display new ways that the drawing surface expresses both aspects of structure. In doing so, I will explore visually what the ancients would have heard in an aural performance.

If you have any ideas you want to contribute to my talk, please let me know. I will certainly be crediting John Hobbins and his general rule of prosody - and my talk will explore some of the ways in which prosody confirms or is in tension with semantic structures. Right now I am thinking the following topics:

1. Coping with the volume of content -
remembering where we were, seeing where we are going.

2. focussing on detail -
examples of how to learn at the micro level
(see for instance the recent discussion of Psalm 1:1-3 here, or Psalm 2 - does concentric structure establish a frame for an uncertain term? I think you could pick almost any psalm for this process

3. Learning over time -
the tension between panic and hope - e.g. my most recent draft of psalm 37.

So two conferences coming up - SBL to meet people whose names I know and Bibletech to discover more of the potential for technology in learning and community.

I have some specific technological problems in Hebrew, some of which I hope for some light. I have experimented with root derivation, word-counting, and transcription of Hebrew. It is some help with searching but there are several limitations to my algorithms. I expect I will need to develop base forms in a dictionary as well as algorithmic helps for a fuller model. As a more traditional problem space, I would like to see some support for prosodic measurement, at least after the fact.