The text of this toolkit is open for reuse under a Creative Commons Attribution licence and improvements are encouraged via Git http://github.com/maxious/govhack-tools or via email patches to govhack@lambdacomplex.org
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/
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.
The best high level reference is the 'Understanding Data' and 'Delivering Data' chapters of the Data Journalism Handbook which is available online for free at
You can learn the technical skills from scratch in Visualize This: The FlowingData Guide to Design, Visualization, and Statistics by Nathan Yau or for more advanced
Basic tutorials for a variety of languages are available for free online or you can learn interactively with websites like [Codecademy for JavaScript](http://www.codecademy.com/#!/exercises/0), [Learn Python](http://www.learnpython.org/) or [Try Ruby](http://tryruby.org/)
For web applications and visualisations, you'll need a basic understanding of JavaScript in order to configure pre made libraries like jQuery. A good source for Javascript information is the [Mozilla Development Network Javascript Page](https://developer.mozilla.org/en/JavaScript)
Following accessibility guidelines not only make a application accessible but make it a better experience for all users! Even if not making an app, good to consider these things to do and not do when designing for humans: [http://www.w3.org/TR/WCAG/](http://www.w3.org/TR/WCAG/)
Using a version control system like Git or Subversion allows you to keep many different versions of what you have been working on so you can collaborate with others or simply back up your files so you don't lose them!
Some people like sensis [http://](http://developers.sensis.com.au/)[developers.sensis.com.<wbr>au</wbr>](http://developers.sensis.com.au/)[/](http://developers.sensis.com.au/) use a provider like[http://](http://mashery.com/)[mashery.com](http://mashery.com/)[/](http://mashery.com/) or [https](https://apigee.com/)[://](https://apigee.com/)[apigee.com](https://apigee.com/) or [http://](http://apiaxle.com/)[apiaxle.com](http://apiaxle.com/)[/](http://apiaxle.com/) or [http://www.3scale.net/](http://www.3scale.net/) which handles making a good API for them.
API documentation is important too! Traditionally for SOAP APIs, you use WSDL but for REST try [Swagger](http://swagger.wordnik.com/) or [iodocs](https://github.com/mashery/iodocs)
Many web app frameworks can generate the documentation for you. For example Symfony for PHP http://symfony.com/ https://github.com/FriendsOfSymfony/FOSRestBundle http://williamdurand.fr/2012/08/02/rest-apis-with-symfony2-the-right-way/ https://github.com/nelmio/NelmioApiDocBundle https://github.com/liip/LiipHelloBundle
For example [Stripe's API](http://amberonrails.com/building-stripes-api/) or previous GovHack entrant [WeatheredOak](http://www.govhack.org/2012/06/02/weatheredoak/)
Also check out [http://thejit.org](http://thejit.org/) & [http://www.senchalabs.org/<wbr>philogl/</wbr>](http://www.senchalabs.org/philogl/) (contributed by Matt Adcock)
Some examples of data visualisation can be seen on [the Sunlight Foundation tumblr](http://sunfoundation.tumblr.com/) or at the GovHack alumn [The Open Budget](http://www/.theopenbudget.org)
Check out the visualisation tools listed in the data sections for web application tools like these [CSS Dashboard gauges](http://www.larentis.eu/donuts/)
[](img/How-to-participate-in-GovHack_html_2f0199ff1.png)Description: Planning Alerts takes data from local government development applications and sends alerts to users based on what applications are lodged in their area.
Description: Displays connections between government contracts, business details, politician responsibilities, lobbyists, clients of lobbyists, political donors and the location of these entities.
If you want to get stared quickly with mobile application development, it's worth considering cross platform frameworks like http://www.sencha.com/products/touch http://phonegap.com/ http://cordova.apache.org/
For data visualisation, there are a variety of graph widgets http://code.google.com/p/afreechart/ http://code.google.com/p/snowdon/ http://code.google.com/p/chartdroid/ http://androidplot.com/ http://code.google.com/p/achartengine/
Check out the [GeoRabble Boundary Mapper's Cookbook](http://georabble.org/2012/05/31/the-boundary-mappers-cookbook/) to see how you can tie all these things together!
There are a variety of base layers like AGRI aerial imagery of Australia http://agri.openstreetmap.org/ or WMS services like http://irs.gis-lab.info/ wms or http://www.gdal.org/frmt_wms_openstreetmap_tms.xml
Google Maps APIs allow you to convert an address to map co-ordinates (geocoding) but you must display on a Google Map. The easiest way to do is with a Google Spreadsheet/Fusion Table http://williamparry.blogspot.com.au/2011/04/putting-data-into-google-fusion-tables.htm http://support.google.com/fusiontables/answer/1012281?hl=en&ref_topic=2592806
If you need geocoding for more than display (working out the distance between points etc) or you don't want to use Google Maps, Cloudmade offers free OpenStreetMap based geocoding http://developers.cloudmade.com/projects/show/geocoding-http-api
[](img/postgisexample.jpg)PostGIS is an extension for the PostgreSQL database server that allows you to store and manipulate geospatial data on a large scale. For example finding which points are in an area or what points are closest . It is also very useful for storing geospatial data because it can convert between all major formats including ESRI Shape files and Google Earth/Maps KML.
[](img/How-to-participate-in-GovHack_html_m50afbe88.jpg)QGIS is a graphical desktop application that allows viewing and editing of geospatial data. Some good base maps are available by adding the WMS layer/server [http://irs.gis-lab.info/](http://irs.gis-lab.info/)
[Layar](http://www.layar.com/) provides a platform for exploring a dataset by travelling to the actual locations of the data and looking through a smartphone. Custom markers (2D or 3D) seem to float in the air and can be clicked on for more information. You can even trigger an event like playing music when within a certain range of a location.
[](img/fusiontablesscreenshot.jpg)Input numerical values and areas to a spreadsheet and maps are produced where the areas are colored on a scale of the values
http://www.peteraldhous.com/CAR/Making_maps_with_Google_Fusion_Tables.pdf tutorial or http://support.google.com/fusiontables/topic/2592754?hl=en&ref_topic=27020 for google help files
[](img/How-to-participate-in-GovHack_html_512fcbe1.jpg)Display points and different layers. Leaflet is the easiest to use if you just want to show points with popups when clicked on.
If you need to customise the base map, try TileMill. See the [THE INSANELY ILLUSTRATED GUIDE TO YOUR FIRST DATA-DRIVEN TILEMILL MAP](http://dataforradicals.com/the-insanely-illustrated-guide-to-your-first-tile-mill-map/)
[](img/How-to-participate-in-GovHack_html_4dda24a4.jpg)Google Earth provides 3\. viewing of KML/GML files which represent points and shapes, both through a desktop application and a web plugin. These can be extended with interactive features that allow you to view by timeline or have animated tours between different points. You can also develop and customise your own viewer with the open source [NASA World Wind toolkit.](http://goworldwind.org/demos/)
Tabular data may have duplicate entries or incorrect formats (varying ways to enter dates/phonenumbers etc.). There are tools to quickly fix common problems
You can also use general purpose file manipulation tools like grep/awk/sed. These work best when you instruct them what search/change you need using Regular Expressions (RegEx) which you can learn more about at http://www.regexper.com/ and http://www.debuggex.com/?re=&str=
Great basic analysis and viewing but older versions can be limited to 6500 rows. Eg [http://www.tcij.org/training-material/car/data-mining/3474](http://www.tcij.org/training-material/car/data-mining/3474) or [http://training.sunlightfoundation.com/module/data-visualizations-google-docs/](http://training.sunlightfoundation.com/module/data-visualizations-google-docs/)
[](img/How-to-participate-in-GovHack_html_209ee972.jpg)Next step up, large datasets can be manipulated/extracted efficiently for example [http://www.postgresql.org/docs/8.4/static/tutorial-window.html](http://www.postgresql.org/docs/8.4/static/tutorial-window.html) , no built-in data visualisation though.
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 [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'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)
ggplot2 is the typical graphical output of R and is very powerful. See these tutorials for instructions: http://chartsnthings.tumblr.com/post/36978271916/r-tutorial-simple-charts http://flowingdata.com/2012/12/17/getting-started-with-charts-in-r/
You can do some very creative plotting for example [putting pictures of Pokemon where their power level is on an X/Y axis](http://www.r-bloggers.com/to-plot-them-is-my-real-test/)
To share your analysis with the world you can use [KnittR](http://yihui.name/knitr/) which to make reports. These can include google widgets/charts/maps with the [googlevis](http://www.r-bloggers.com/googlevis-0-3-2-is-released-better-integration-with-knitr/) package.
Create visualisations from various data formats by dragging and dropping. Free trial available on website. [](img/Tableau-Screenshot.jpg)
[](img/How-to-participate-in-GovHack_html_m11006fce.jpg)Javascript based charts for webpages.
[](img/How-to-participate-in-GovHack_html_m90d8020.jpg)Javascript visualisations that are more interactive or intricate than charts. Can be hard to learn but there are examples and easier to use premade visualisations such as [word clouds](http://www.jasondavies.com/wordcloud/), [realtime filtering of barcharts](http://square.github.com/crossfilter/), or [bubble trees for comparing amount sizes](https://github.com/okfn/bubbletree).
Most of the world's data isn't structured because it is contained in documents (webpages, tweets etc.). Sometimes it is possible to structure it, sometimes there are tools that are better suited it unstructured data.
PDFs - http://source.mozillaopennews.org/en-US/articles/introducing-tabula/ for text PDFs or http://www.reporterslab.org/dochive/ for images (common in scanned document PDFs)
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.
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.
For light weight analysis, try R or Ruby: http://www.r-bloggers.com/simple-text-mining-with-r/ http://blog.josephwilk.net/ruby/latent-semantic-analysis-in-ruby.html
"Overview automatically sorts thousands of documents into topics and sub-topics, by reading the full text of each one." Simply make a CSV file with two columns, id and text. 10,000 documents is a good limit for the current state of the system. https://www.overviewproject.org/
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.
[](img/webadmin-data.png)Help understand relationships - how is X connected to Y and via what other entities they both are connected to.
Imports and exports can be done by [writing a java program](http://www.slideshare.net/maxdemarzi/etl-into-neo4j) or [spreadsheet](http://blog.neo4j.org/2013/03/importing-data-into-neo4j-spreadsheet.html)
Major graph databases like these can be accessed using a common syntax called Gremlin or by writing a simple Java/Python/Ruby application. Queries can be tested in the built in data browser.
NetworkX is a social network analysis library for python. Many advanced analyses built in like finding communities within a graph. Also good for converting data into graphs.
Proper visualisation of networks can be hard as described in this presentation [Visualising Networks: Beyond the Hairball](http://www.slideshare.net/OReillyStrata/visualizing-networks-beyond-the-hairball)
You can run [TreeViz](http://www.randelshofer.ch/treeviz/) locally or use [d3 on a website](http://bl.ocks.org/mbostock/4063550), [step by step instructions for creating tree data for d3](http://blog.pixelingene.com/2011/07/building-a-tree-diagram-in-d3-js/)
[](img/How-to-participate-in-GovHack_html_7579906d.png)Classic directed graph visualisation tool, can even [generate images online without installing](http://ashitani.jp/gv/) or use in webpages with [javascript port of software](http://code.google.com/p/canviz/). File format ["dot" very easy to learn](http://en.wikipedia.org/wiki/DOT_language)
[](img/How-to-participate-in-GovHack_html_74d01d05.jpg)Desktop graph editor and renderer. Many good automatic layout algorithms even for very large graphs.
[](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.