I'm so glad you bring up this question. Please take a look at the following links as well:
http://www.socrata.com/products/custom-web-and-mobile-apps-government-data/ (scroll down to 'Featured Apps')
A great article from telegraph about Meet the UK start-ups changing the world with open data
Also, if you check the Data gov site of UK, you will find 338 applications that use Open Data only in UK.
Actually, there are many apps out there and recently many start ups based on OD. Trying Google "Application + Open Data" will return a lot of case studies.
Here are some additional resources for application examples:
Code for America Commons: http://commons.codeforamerica.org/
Code for America Library: http://codeforamerica.org/library
Beyond Transparency: http://beyondtransparency.org/
Technical.ly Directory: http://technical.ly/directory/
Open 311 Applications: http://wiki.open311.org/GeoReport_v2/Support
If your main focus is to visualize the data and have graph metrics I would recommend this list.
If you want an off the shelf package
Gephi - Desktop application, Open Source license
Cytoscape - Desktop Application - Open Source license
Pajek - Desktop Application, Free for non Commercial use (old but still good - I've seen papers using it just few days ago)...
A popular answer comes from a 2010 question on Stackoverflow - Source Link
Northwind database - (documentation & data model)
NopCommerce sample dataset
E-commerce dataset from Amazon / Google Products / Abt Buy
Tableau Superstore (Excel file) (although I think this is aggregated)
My team builds https://vida.io a tool for creating data visualization templates. We support d3.js templates. You can see a lot of examples on our site:
For simple chart/visualization, you can use Google visualization tool:
There are a few solutions to visualize graphs : D3.js, Sigma.js, KeyLines, Gephi, Linkurious, Neoclipse, Neovigator.
Here is a table that compare some of these options : http://linkurio.us/comparative-study/
And a quick presentation about the different approaches to visualizing graphs : http://www.slideshare.net/Linkurious/graph-visualization-options-and-...
here a recent app (iOS and Android) we just released
This application was created as part of a European program, the Degust’Alp program, which combines the territory of the Alpes de Haute Provence and the Province of Cuneo in Italy.
The app allows to discover the Alpes-de-Haute-Provence South of France area.
It's a free app which ...
What are your goals? You may need to upgrade your toolset. Bash command line tools like cut, sort, uniq are very useful for this kind of thing.
If you want to analyze digit frequency, transitions between letters (n-grams), common ...
Quadrigram (www.quadrigram.com) has good graph visualizations in both 2D and 3D. They are relatively easy to set and publish.
You can also combine them with Maps and other visualizations
Checkout this example here.
For the USA, the National Highway Traffic Safety Administration (NHTSA) has general information and fact sheets about theft as well as a search tool where you can get theft rates by year, production rates by year, look by manufacturer, and more. Unfortunately, it looks like data is only up to 2011 but it does go back to 1983.
For more USA data and aggregated ...
Exponential Decay formula would work.
is the remaining amout of material of the decay cycle is complete.
If you start with 100 grams of x this is your
If your decay rate is 2% this is your r.
If you do 1 second increments that would be your t.
The remaining amount becomes your new initial amount and you
Initial Amount Time Decay ...
The Weka machine learning toolkit (in Java) introduced the text-based ARFF format (Attribute-Relation File Format) as a proposed standard format for machine learning datasets. Its website has a list of ARFF datasets. Some of them are discussed in the excellent Weka book that is now in its third edition: Witten, Frank, & Hall (2011): „Data mining. ...
There's a data catalog here: http://ogesdw.dol.gov/views/data_catalogs.php (and go to the Wage and Hour Compliance Action Data page). According to the dictionary, flsa_bw_atp_amt is the "BW Agreed to under FLSA (Fair Labor Standards Act)".
But it sounds like your question is more about how to get real qualitative information about the data fields. If that ...
Kaggle hosts many machine learning contests, and their datasets is therefore prepared for machine learning. You can even use Kaggle in Class for teaching purposes.
There is also MLcomp, whose concept of transparent comparison of ML algorithms is very attractive to me. Unfortunately the website is a bit dormant nowadays.
Note that most of the time datasets ...
microformats are the most abundant semantic technology deployed on the web today, aka they are the biggest dataset for machine learning. as long as the html document is marked up properly, they fit all of your needs and then some. you can find sites that are deploying them in the "wild" at the wiki:
and if you do a quick web search, ...
If you are using R, there is the R Datasets Package. In this way, the data is prepared and ready for analyis in R.
There are also examples of the R code, which includes how to use the library. See here for the canonical iris data set.
Other languages will also have sample datasets. In python, the scikit library is popular for machine learning and ...
Here are the slides from the vienna.rb talk (I did not attend it) about Open Football(soccer) Data and the World Cup 2014. The presentation is really interesting and it gives a lot of ideas I think.
Open Football on GitHub proposes a large collection of open football datasets.
Here is a brilliant article called "ANALYZING A NHL PLAYOFF GAME WITH TWITTER". ...
These may be the variables are looking for:
Percentage of aided students whose family income is between $0-$30,000 student share_lowincome.0_30000 float INC_PCT_LO NSLDS
Percentage first-generation students student share_firstgeneration float PAR_ED_PCT_1STGEN NSLDS
Keep in mind these are percentages of title IV aided student ...
For hospital data I found this website that lists hospital information, including location, hospital type and some quality measures. See: https://hospitalcaredata.com/directory/
I found this website with a list of urgent care facilities, but no statistical data. See: http://urgentcarelist.com/
I work at Quandl and we have a database called Organisation for Economic Co-Operation and Development.
I searched for "US hospitals" within the database and it turned results showing data for number of hospitals in the US, number of hospital beds, number of hospitals per million, number of publicly owned hospitals etc. Hope this helps.
There's various Earth imagery programs, Landsat is one of them. Some of these programs can be found here: http://earthexplorer.usgs.gov/
Select under 'data sets' either the aerial imagery or landsat, then you can select the area and download the images.
Due to the fact that a given satellite has limited resolution and takes only so many pictures per minute,...
In addition to the dataset provided by vonjd, you can look at the Online retail and Online retail II datasets on the UC irvine data repository.
They contain transaction data for an online retailer that can be used to derive the Recency, Frequency ...
If you found non-aggregate data based on latitude/longitude, then you'd still need some algorithm to map your point to the nearest measurement coordinates - which is not trivial. It's unlikely to find US-wide "incident-level" data, whereas most data will be aggregated to some geographical region and time frame.
For that reason, I think most demographic, ...
If it is a plain text file with plain text passwords, PACK is a tool to analyze text passwords. It provides several python scripts to do different level of analysis. You could run those scripts directly in the command line environment. Also, the website provides a detailed documentation that you could refer to.
Based on your requirement, I think the script ...
Without all of the original data, and its metadata, any answer here can only offer a guide as to how to start answering your questions.
Your first question is: "where is the problem?"
Your second question is: "is GSOD biased?"
Both of these must start with further statistical analysis.
And you need to analyse the metadata for the datasets you are ...