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LOGD External Demo

These demos are not hosted in a Drupal page in http://logd.tw.rpi.edu

Clean Air Status and Trends - Ozone

Description: 
This demo shows a map of the U.S. depicting the Clean Air Status and Trends Network (CASTNET) Ozone monitoring stations and their average Ozone level. Clicking a station shows more detailed information and a link to a graphical representation of the time-series of measurements.
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About


For this demo, we used RDF data derived from ozone and visibility readings provided by the EPA's Castnet project. This RDF combines raw data on Castnet readings (ozone and visibility) with corresponding geographic information on the sites of readings, which the raw Castnet data lacks. On the provided map of the US, every yellow dot represents a single Casetnet site and dot size corresponds to an average Ozone reading for that site, where larger dots represent larger averages. When a Castnet site is clicked, a small pop-up opens, displaying more information on that site, along with a link. This link takes the user to another page that displays in a timeline all the Ozone and Visibility data available for that site. This timeline uses the Google Visualization API giving users added functionality in how they view the data in the timeline. To allow users to filter through Castnet readings, a faceted browsing interface (from the MIT Simile Exhibit API) is provided.

Interesting observations

This demo uses SPARQL to combine raw data on the Castnet Project (dataset 8) from Data.gov and geographic information on Castnet Stations (Dataset 10001) from the EPA website. This enables the demo to plot Castnet readings on a US map, allowing users to look for geographic relationships within the Castnet data. When a user clicks on a Castnet station, historical ozone values for that station can then be viewed through a timeline. Finally, the use of faceted browsing aids users in interacting with presented data, allowing for filtering based on different criteria.

Technology Highlights


  • This uses the RDF to Google visualization conversion process of using a SPARQL service and XSLT to put the data in JSON format.

    • SPARQL is used to grab data from two datasets.

  • This also uses MIT Simile Labs Exhibit to make the faceted browsing map.

    • A Web service is used to convert JSON from SPARQL into JSON that Exhibit can use.

  • The visualization used is the annotated timeline.


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Broadband Internet Use versus Total Internet Use - United States Households, 2009

Description: 
This demo shows the percentage of households in each state with broadband out of the total number of households with internet access. This is based on the division of broadband internet use in rural and urban areas as well as dial-up use in rural and urban areas.
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Lighter colored states have a lower percent of broadband internet using households, whereas states in darker blue have a higher percent of broadband using households. When you click on a state, a chart appears to the right that breaks down the individual figures showing:
  • Urban Broadband Internet Use
  • Rural Broadband Internet Use
  • Total Urban Internet Use
  • Total Rural Internet Use
The result is an interesting comparison of broadband internet adoption in states of rural and urban areas.
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Comparing US (USAID) and UK (DFID) Global Foreign Aid

Description: 
This application presents a mashup of foreign aid data (represented in US Dollars) from the United States Agency for International Development (USAID) and UK Department for International Development (DFID) for the 2007 US Fiscal Year.
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Your web browser must have JavaScript enabled
in order for this application to display correctly.
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How Americans use Electric Energy in 2005

Description: 
Bar graph of electric energy consumption by appliance, USA 2005
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This demo plots the total electronic energy consumed for different types of use from thousands of sampled families in the US. It uses Dataset 59 . It was created by Sarah Magidson and Li Ding. More details can be found at Demo Information Page. It uses the following SPARQL query.
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State Gross Income Versus Medicare Claims (2007)

Description: 
Compares the adjusted gross income (AGI) of state residents and the number of Medicare claims made within that state by residents in 2007.
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Observations

This map shows a comparison between the amount of adjusted gross income (AGI) earned by state residents and the number of Medicare claims made within that state by residents in 2007. From this visualization, we can see the following observations:
  • darker states, such as Montana, California and Florida, are the states with low average AGI per Medicare claim. California has a very huge AGI, but it also has high Medicare claims far above national average.
  • lighter states, such as Oregon, Wyoming, and Hawaii, are the states with high average AGI per Medicare claim. With fair amount of population, people in these states may be more healthy?
For further investigation, we can read some related News articles

  Technology Highlights


  Portable Interactive Google Visualization Design This demo uses Google Visualization API
 to integrate the following types of charts. This demo is also interactive such that users can see more details about a state when clicking the state on the map. We also notice that currently Google GeoMap has some limitations, e.g. it does not show Washington, D.C.
 on map.
  • GeoMap
  • Column Chart
  • Table
This demo is highly portable as also code are encoded in a HTML file and the computations are implemented using javascript.
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Comparing US-USAID and UK-DFID Global Foreign Aid

Description: 
This application presents a mashup of foreign aid data (represented in US Dollars) from the United States Agency for International Development (USAID) and UK Department for International Development (DFID) for the 2007 US Fiscal Year.
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Technical HighlightsThis application presents historical foreign aid data (ranging from 1947 to 2008) from three branches of the US Government: the United States Agency for International Development (USAID), the Department of Agriculture and the Department of State. Data may be retrieved in one of two ways:
  • 2008 Figures - Here, users may retrieve data for specific countries by clicking on a provided world map (shaded based on total foreign aid received). In turn, two kinds of information are presented:
    • Aid Figures - Here, three pie charts are presented (one for each agency), detailing specific aid categories.
    • CIA World Factbook - Information from a selected country's CIA World Factbook entry.
  • Historical Trends - Here, users may retrieve historical aid records (ranging from 1947 to 2008) for a given country. Upon selecting a country from the provided list, users may generate a timeline of aid data using a corresponding set of aid categories.
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