Update (2008-11-07): Restoring the country's economy, confidence, dignity, and reputation will be tough; I expect to be disappointed along the way, but right now I am enormously pleased. Fort Collins, Larimer County, Colorado, and the United States of America expressed enough hope over fear, and rightly held the GOP accountable for getting us into this ditch.

After 7 disastrous years of mal-intent and incompetence, let's give the hopeful and serious a chance. It's time for a change.

Paul Winkler and the OpenGeo team found a problem with Shapely and Zope's web server on their 64-bit system, provided the fix, and now here's Shapely 1.0.8. An upgrade is recommended if you're using Zope or a similar framework.

I came up with an example of how Python's multiprocessing package -- standard in 2.6, and recently backported to 2.4 and 2.5 (on PyPI) -- could be used to set up a simple R-Tree index server:

from multiprocessing.managers import BaseManager

class RtreeManager(BaseManager):
    pass

RtreeManager.register('add')
RtreeManager.register('intersection')

if __name__ == '__main__':

    from rtree import Rtree

    class NoisyRtree(Rtree):
        def add(self, i, bbox):
            print "Adding: %s, %s" % (i, str(bbox))
            Rtree.add(self, i, bbox)
        def intersection(self, bbox):
            print "Searching: %s" % str(bbox)
            return Rtree.intersection(self, bbox)

    index = NoisyRtree('processing')

    RtreeManager.register('add', index.add)
    RtreeManager.register('intersection', index.intersection)

    manager = RtreeManager(address=('', 50000), authkey='')
    server = manager.get_server()
    print "Server started"
    server.serve_forever()

Run that module (man.py) as a script to start the server, and access the index from Python in a new process like this:

>>> from man import RtreeManager
>>> manager = RtreeManager(address=('', 50000), authkey='')
>>> manager.connect()
>>> print manager.intersection((-20.0, -20.0, 20.0, 20.0))
[1L, 2L, 5L]

Three items were already in my index, persisted on disk. One more can be added like this:

>>> manager.add(4, (-10.0, -10.0, -9.0, -9.0))
<AutoProxy[add] object, typeid 'add' at 0x-483da894>
>>> print manager.intersection((-20.0, -20.0, 20.0, 20.0))
[1L, 2L, 5L, 4L]

The manager synchronizes access so additions and queries from different processes don't clobber each other.

Interesting. It occurs to me that SQLite, even, is overkill for this purpose. A relational database isn't necessary and the unavoidable duplication of data is undesirable. All that is needed is an R-Tree index and, eventually, the capacity to use spatial operators and predicates in views. The Rtree package that Howard and I have been working on could serve well. It need store only the keys of CouchDB documents, so there's no duplication of spatial data. SpatiaLite (which appeals to me in many ways) uses the same geometry library as Shapely does (GEOS), so a Python query using Rtree and Shapely has essentially the same implementation as an OpenGIS SQL query of SQLite/SpatiaLite. I suggested in comments that GeoCouch might want to take advantage of the GeoJSON group's work, on geometry formatting at least.

Via Simon Willison.

The key paragraph from George Mason University's response to the Reuters lawsuit, via Dan Cohen:

The Thomson Reuters Corporation has sued the Commonwealth of Virginia over Zotero, a project based at George Mason University’s Center for History and New Media (CHNM). A free and open-source software initiative, Zotero aims to create the world’s best research tool and has already been adopted by hundreds of thousands of users at countless colleges and research universities. CHNM announces that it has re-released the full functionality of Zotero 1.5 Sync Review to its users and the open source community. As part of its formal response to this legal action, Mason will also not renew its site license for EndNote.

79 today. Geography was a key ingredient in her Earthsea novels (which I read again earlier this year, and the Other Wind for the first time). Did you know that her website has maps of Earthsea?

Is that crayon? I've been looking at a lot of crayon coloring lately, and would swear it is. Cool! Maps of Archaic Latium from her new novel, Lavinia, are also available from her site.

What Pete Johnston said:

As it happened, I was talking about ORE in a presentation last week (more on that in a follow-up post) and I expressed the opinion then that, leaving aside for a moment the core ORE model of Aggregations and Aggregated Resources, I think one of the significant contributions of ORE may turn out to be its emphasis on what I think of as a "resource-centric" approach and (at least some of) the conventions of the Semantic Web and "Linked Data" communities. In particular, I think this is a potentially important change for the "Open Archives"/"eprint repository" community, where to a large extent - not entirely, but to a large extent - repository developments on the Web have been conditioned by the more "service-oriented" framework of the OAI-PMH protocol and an emphasis on XML and XML Schema. It's also probably fair to say that I don't think the ORE project really started from this perspective, but rather things evolved and shifted - perhaps not always in a straight line! - in this direction as the work proceeded.

The discussion around ORE opened minds all around: I was clued in to Linked Data and had my interest in RDF rekindled; the ORE authors came around to embracing the practices of the Atom community.

I recognize the incongruity of my linking to A-lister Nick Carr's entry about the dwindling long tail:

Chris Anderson's "long tail" remains an elegant and instructive theory, but it already feels dated, a description of the web as we once imagined it to be rather than as it is. The long tail is still there, of course, but far from wagging the web-dog, it's taken on the look of a vestigial organ. Chop it off, and most people would hardly notice the difference. On the web as off it, things gravitate toward large objects. The center holds.

This reminds of the geospatial/geoweb community's fascination with "top 25" lists and preference for popular blogs over idiosyncratic blogs.