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huviz

Image

Demonstration Sites

/cwrc/HuViz is a fork of /smurp/huviz where development occurs

Installation

What is HuViz?

HuViz is a Semantic Web graph visualization system which uses a powerful system of interactions which can be captured to produce replayable scripts. It is rather like SQL (the Structured Query Language) but applied to the task of creating graph visualizations.

Sets

The commands in HuViz can be thought of as moving nodes around among various sets, where each set behaves in a particular way on screen.

  • Activated -- the nodes which are placed into the graph and which cause other nodes connected to them to become graphed. Dragging a node into the graph Activates it.

  • Discarded -- the nodes which have been placed in the disard bin and which can't be pulled into the graph by activated nodes.

  • Graphed -- the nodes which are in the graph, either by being activated or by being pulled into the graph

  • Hidden -- the nodes which have been made invisible to reduce clutter, but which can be pulled into the graph by activated nodes

  • Labelled -- the nodes which show their labels continuously, rather than just when hovered near

  • Nameless -- the nodes which do not have pretty names

  • Pinned -- the nodes which have been pinned in particular places on the graph

  • Selected -- the nodes which have their named edges cataloged in the box labelled "Edges of the Selected Nodes" for the Draw verb to work on

  • Shelved -- the nodes which are kept, disconnected, on display on the sorted, circular "Shelf" around the central graph

Verbs

The Verbs are the operations which move nodes between the various sets, ie sets of nodes in particular states.

  • Activate / Deactivate
  • Wander
  • Walk
  • Select / Unselect
  • Draw
  • Label / Unlabel
  • Shelve
  • Hide
  • Discard / Retrieve
  • Pin / Unpin

Installation

# Install huviz from github
git clone https://github.com/smurp/huviz.git

Installation (for running the server)

# install NodeJS using NVM for most flexibility
# known to work on NodeJS >= v6.11.3
# (as of this writing, the latest Long Term Support version)

https://github.com/creationix/nvm#install-script

# Install `nvm` using the curl command in 'Install Script'.
# Then quit that Terminal window and start a new one to make sure its firing up automatically.
# There are tips at the bottom of the NVM README in case of problems.

# Then install the LTS version of `node` itself like this:
nvm install --lts

# Make sure you've got a suitable version of Node
node -v # expecting v6.11.3 or later

# Then do classic normal npm stuff
npm install # install needed modules

Running the server

npm start

Development

Running the server during development

npm run dev

Running CLI tests

npm run watchTest

# bail on first error
BAIL=1 npm run watchTest

uses https://www.npmjs.com/package/npm-watch https://www.npmjs.com/package/mocha

Developing quaff-lod

Run the auto build process while you are editing src/quaff-lod-worker.js

$ cd quaff-lod
$ npm run dev

Run the development version of huviz and tell it where to find the dev version of quaff-lod

$ cd huviz
$ QUAFF_PATH=../quaff-lod/ npm run dev

Doing releases

Per https://github.com/geddski/grunt-release

Patch Release:

Two choices:

  • npx grunt release
  • npx grunt release:patch

Minor Release

  • npx grunt release:minor

Major Release

  • npx grunt release:major

Installation (for running orlandoScrape.py)

# On OSX Mavericks install homebrew
http://crosstown.coolestguidesontheplanet.com/os-x/55


# If you want to run
# On OSX you should set up pyenv-virtualenv
https://github.com/yyuu/pyenv-virtualenv

# Make a virtualenv
pyenv virtualenv huvizenv

# use it
echo "PYENV_VERSION=huvizenv" > .python-version

# install the python requirements
pip install -r requirements.txt

Operating orlandoScrape.py

--limit 2
    limit the number of writers processed

Converting XML to Turtle (TTL)

./orlandoScrape.py --outfile data/test_20.ttl  --limit 20 -v

See data/test_20.ttl

Converting XML to NQuads

./orlandoScrape.py  --outfile data/test_1.nq   --limit 1

See data/test_q.nq

Converting XML to JSON

How to produce the full JSON output as orlando_all_entries_2013-03-04.json (the default behaviour):

./orlandoScrape.py --infile orlando_all_entries_2013-03-04.xml --outfile orlando_all_entries_2013-03-04.json  --regexes orlando2RDFregex4.txt

How to produce the poetess JSON output as orlando_poetesses_2013-02-12.json:

./orlandoScrape.py --infile orlando_poetesses_2013-02-12.xml --outfile orlando_poetesses_2013-02-12.json  --regexes orlando2RDFregex4.txt

How to produce orlando_timeline.json

egrep 'dateOf|standardName' orlando2RDFregex4.txt > orlando_timeline.regex
./orlandoScrape.py --infile orlando_all_entries_2013-03-04.xml --outfile orlando_timeline.json --regex orlando_timeline.regex -v

Running the Orlando timeline locally

git clone https://github.com/smurp/huviz
python -m SimpleHTTPServer
open http://localhost:8000/timeline.html

Generating tag_tree.json

./extractOrlandoTagInfo.py --compact --outfile orlando_tag_tree.json

Gallery

Finite state machine

Demo of finite state machine diagram

Demo of CWRC subject-centric data

Demo of moderately dense graph

3191 Nodes

Graph of 3191 nodes pulled from CWRC SPARQL

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LOD visualization tool for humanities datasets

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