The DC Municipal Regulations. This is also an experiment in open data design. See relevant post on Indexing and Searching Big Static Data
Most open data sites run as traditional websites; they have a content management function (a UI for editing content), a 'search engine', dynamic indexes, and more. They cost quite a bit of money to maintain, and often don't perform very well.
This is a different approach.
invert.js generates an inverted index
of documents so that searches can run entirely in Javascript. And since
this search index can be quite large, it allows it to be segmented.
titles.js generates a titles document, and index.html is a lightweight
index.
Future bits will generate redirects to provide alternative url schemes via generating redirect pages.
The objective is to allow a large dataset, like the DCMR (~20k documents, ~68MB of plain text), to be quickly and easily browsed on a website that's powered by a simple, cheap host like Amazon S3. A government or individual could then pre-pay for years of service.
This should also permit incredibly easy clonability; federating the data store will be as simple as downloading a copy.
mkdir docs text indexes
Install node.js module dependencies:
npm install
Scrape the datasource
node/scrape/scrape.js
Generate a json document from the titles generated in the docs directory
node titles.json
Convert the documents into plain text
Requires python plugins catdoc and sh installed which you can install via pip
python textify.py
Lastly, generate an index by running
cd generate_index
node invert.js
node trie.js