editz
--- a/index.md
+++ b/index.md
@@ -13,6 +13,7 @@
You should record a 3 minute speech and mix images/text to accompany.
[Screenr] (http://www.screenr.com/) , [ActivePresenter Free Edition](http://atomisystems.com/activepresenter/free-edition/) and other screencasting tools allow you to demo apps.
To mix together clips, you can use youtube video editor http://www.youtube.com/editor or local software like http://www.videolan.org/vlmc/ or http://www.lwks.com/
+You can use graphics for example [storyboards with these free icons](http://dribbble.com/shots/1083617-430-FREE-storyboard-illustrations)
You also need to submit your "source material". For an application this may be source code, for another work it might be your notes or prototypes.
The key thing here is that your source material demonstrates to the judges that some of the end result was your own work and that it is possible for another person to replicate that work.
@@ -78,6 +79,8 @@
## Virtual Servers
Many free services to try out virtual/cloud servers before scaling up: https://www.chunkhost.com/ or heroku or https://www.appfog.com/pricing/
+If your wifi starts to get congested, you can use [mosh](http://mosh.mit.edu/) to improve the performance of SSH under reduced network performance.
+
## Hosted Developer Tools
@@ -106,7 +109,6 @@
So an API isn't just an XML file!
-
A good web based data API:
* Is logically organised
@@ -240,6 +242,9 @@
## Analysis
+### R
+http://www.r-bloggers.com/starting-analysis-and-visualisation-of-spatial-data-with-r/
+http://www.r-bloggers.com/3d-mapping-in-r/
### PostGIS
@@ -330,7 +335,8 @@
### R Statistical Language
[](img/rstudio-windows.png)
-R provides a platform for advanced data analysis which can find and visualise trends even in large datasets. Some reference resources to learn the language [R basic statistics and graphs](https://people.ifm.liu.se/marjon/R_intro_solutions.pdf) [http://cran.r-project.org/doc/manuals/R-intro.html ](http://cran.r-project.org/doc/manuals/R-intro.html)There are also some addons that provide graphical interfaces that make it easier to use such as Rattle [http://rattle.togaware.com/](http://rattle.togaware.com/) , RStudio [http://rstudio.org/](http://rstudio.org/) or Deducer [http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual](http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual)
+R provides a platform for advanced data analysis which can find and visualise trends even in large datasets. Some reference resources to learn the language [R basic statistics and graphs](https://people.ifm.liu.se/marjon/R_intro_solutions.pdf) [http://cran.r-project.org/doc/manuals/R-intro.html ](http://cran.r-project.org/doc/manuals/R-intro.html) [Guerilla Guide to R](http://www.r-bloggers.com/the-guerilla-guide-to-r/)
+There are also some addons that provide graphical interfaces that make it easier to use such as Rattle [http://rattle.togaware.com/](http://rattle.togaware.com/) , RStudio [http://rstudio.org/](http://rstudio.org/) or Deducer [http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual](http://www.deducer.org/pmwiki/pmwiki.php?n=Main.DeducerManual)
R's value lies in the wide array of libraries and addons you can use. For example [BigVis](http://blog.revolutionanalytics.com/2013/04/visualize-large-data-sets-with-the-bigvis-package.html) lets you visualise 10 Million data points in 5 seconds on an ordinary computer.
Be sure to checkout the list of ["10 R packages I wish I knew about earlier"](http://blog.yhathq.com/puosts/10-R-packages-I-wish-I-knew-about-earlier.html)
@@ -348,11 +354,14 @@
## Visualisation
-### [Tableau Desktop](http://www.tableausoftware.com/)
-
+### WYSIWYG visualisation tools
+
+[Tableau Desktop](http://www.tableausoftware.com/)
Create visualisations from various data formats by dragging and dropping. Free trial available on website. [](img/Tableau-Screenshot.jpg)
See this [Tableau Desktop Tutorial](http://schoolofdata.org/2013/04/27/ddjschool-tutorial-analysing-datasets-with-tableau-public/)
+
+There are also web based tools like [plot.ly](http://plot.ly) and [infogr.am](http://infogr.am)
### Web page (Javascript) graphs
[Flotr2](http://www.humblesoftware.com/flotr2/)/[Google Chart Tools](https://developers.google.com/chart/)
@@ -377,7 +386,8 @@
## Analysing
Natural Language Processing libraries like OpenNLP for Java or NLTK / [Pattern](https://github.com/clips/pattern) for Python allow you to extract information from text. For example, [finding the important keywords in a sentence automatically](http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/)
-One of the most useful techniques found in these libraries is Named entity recognition which extracts the subjects named in a piece of text. [TextRazor](http://www.textrazor.com/) lets you analyse up to 500 documents a day online.
+
+One of the most useful techniques found in these libraries is Named entity recognition which extracts the subjects named in a piece of text. You can find online services that will interpret text for you without having to install any libraries or write any code such as [Yahoo Content Analysis](http://developer.yahoo.com/contentanalysis/) or [TextRazor](http://www.textrazor.com/).
A search engine just for your dataset can also help. Tools like Apache Lucene/Solr or ElasticSearch can help you index and search large datasets in new ways.
@@ -396,13 +406,12 @@
# Graph (relationships and networks) Data Tools
Graph data can be very valuable for finding communities, hubs and connections between entities (the 6 degrees of separation). This is through the techniques of Social Network Analysis.
-You can also find "linked data", [tools for use are listed here](http://logd.tw.rpi.edu/tools_technologies) as well as [sgvizler](http://code.google.com/p/sgvizler/) for sparql graphing and [Flint SPARQL editor](http://openuplabs.tso.co.uk/demos/sparqleditor). For more linked data tools, see the [govcamp useful tools wiki](http://govcampau.wikispaces.com/useful+tools)
+You can also find "linked data", [tools for use are listed here](http://logd.tw.rpi.edu/tools_technologies) as well as [sgvizler](http://code.google.com/p/sgvizler/) for sparql graphing, [RelFinder for RDF exploration](http://www.visualdataweb.org/relfinder.php) and [Flint SPARQL editor](http://openuplabs.tso.co.uk/demos/sparqleditor). For more linked data tools, see the [govcamp useful tools wiki](http://govcampau.wikispaces.com/useful+tools)
## Analysis
### R
-http://www.slideshare.net/ianmcook/social-network-analysis-in-r
-- http://is-r.tumblr.com/post/38240018815/making-prettier-network-graphs-with-sna-and-igraph
+R statistical language can be used for social network analysis too http://www.slideshare.net/ianmcook/social-network-analysis-in-r http://is-r.tumblr.com/post/38240018815/making-prettier-network-graphs-with-sna-and-igraph
### Graph Databases
@@ -452,8 +461,13 @@
Many tools can produce input files for Gephi including Graph Databases and [a Excel Spreadsheet to map twitter social networks](http://dfreelon.org/2013/04/26/spreadsheet-converts-tweets-for-social-network-analysis-in-gephi/)
+If you need to distribute or customise Gephi-like functionality [Cytoscape](http://www.cytoscape.org/) provides a framework (looks much like Gephi user interface) to develop advanced interactive network visualisations in Java, including filtering and clustering.
+
### [sigma.js](http://sigmajs.org/)
[](img/How-to-participate-in-GovHack_html_m6006eaf3.jpg)Javascript graph viewer for displaying graphs on webpages without any other plugins/applications required. It can use GEXF files exported from tools like neo4j, gephi or NetworkX.
It's also possible to [filter/search the displayed network in sigma.js](https://github.com/jacomyal/osdc2012-sigmajs-demo)
+[Cytoscape.js](https://github.com/cytoscape/cytoscape.js) can also be used for interactive web-based network visualisation.
+
+