- Home
- HealthData.gov Challenge (2013)
- IOGDS: International Open Government Dataset Search (DEMO)
- IOGDS Analytics (V1)
- IOGDS Analytics (V2)
- Submit a Catalog to IOGDS
- Schema.org Dataset Extension (DEMO)
- Instance Hub demo (V.1)
- Instance Hub demo (V.2)
- URI Design Principles
- SW Challenge 2010
- Tutorials
- Videos
- Demos
- Datasets
- Tools & Technologies
- Community
- About Us
- Publications
- RSS Feed
User login
Navigation
Share
live demo
Information on Chilean schools
Description:
This demo mixes two different datasets: One containing information about schools (location, phone number, etc.) and other containing the SIMCE (a standardized Chilean test) scores of that school over the years.
Contributor:
Note: Some schools may not have data
Select a municipality
|
|||||||
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Thumbnail:
- Login to post comments
- 2269 reads
Comparing Chilean SIMCE test for middle school in each region
Description:
This demo shows scores in mathematics for a Chilean standardized score by region. The data is complemented by information taken from dbpedia (such as population and geographical positions).
Contributor:
Note: Region's name, latitude and population are taken from dbpedia. For some regions there is no such information so I provide only the URI of those regions.
Data table
This table show the results from the SIMCE (Quality of Education Measurement System, in spanish) together with data obtained from dbpedia. An interesting aspect is that there is information missing in dbpedia about some regions.| Region (dbpedia) | Population (dbpedia) | Latitude (dbpedia) | Avg. math score per region(simce) | Avg. language score per region (simce) |
|---|
Visualizations
The first graph shows the average of Math and Language scores in each region. It is clear that the scores are higher in the central region. A potential explanation if the correlation between population in each region and its score (as you can see in the second graph). Finally, we used dbpedia to obtain the latitude (remember that Chie is roughly speaking a vertical line, so longitudes are more or less the same for each region) and we compared that with the SIMCE results (as can be seen in the third graph). It is possible to do more analysis (in terms of density, ratio of rural/urban population and so on).Thumbnail:
- Login to post comments
- 3392 reads
Data.gov survey: dataset modification dates compared
Description:
This demonstration shows when data.gov datasets were last updated, as determined by their HTTP responses. How up-to-date are the datasets listed in data.gov? We start with a time line histogram for a moment in time.
Contributor:
Number of Datasets Modified since __
Process used
The following diagram shows the process used to obtain the last-modified dates of the data.gov datasets.
- 1 - csv2rdf4lod converted data.gov's 2010-Sep-13 version of Dataset 92 csv file using enhancement parameters and loaded the results (see sample) in LOGD SPARQL endpoint's named graph http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13.
- 2 - curl queries SPARQLProxy's named graph http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13 (which contains dataset http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13) for data.gov's dataset identifiers.
- 3 - The data.gov details page is requested and scraped to obtain references to data sources. Redirects are followed and HTTP HEADs are recorded in RDF using Turtle syntax and terminology from the Proof Markup Language ontology.
- 4,5 - The aggregated crawl is moved to within the LOGD dataset repository (here) and loaded into the LOGD SPARQL endpoint in named graph http://logd.tw.rpi.edu/source/twc-rpi-edu/dataset/data-pointer-http-headers/version/2010-Sep-21_16-30-03 (which contains dataset http://logd.tw.rpi.edu/source/twc-rpi-edu/dataset/data-pointer-http-headers/version/2010-Sep-21_16-30-03).
- 6 - This Javascript is included within THIS PAGE to query the LOGD SPARQL endpoint for dataset modification dates (using this query and these nightly-cached results). It calculates the histogram and uses Google Visualization's Annotated Timeline to render the results. A few notes are hard-coded to provide a frame of reference.
Use of provenance
The following diagram illustrates how the Proof Markup Language was used to record the HTTP headers obtained from the government agency servers. A portion of this data graph is selected by the SPARQL query listed above (the headers are excluded). The red links show the HTTP redirects and HTML anchor hrefs from the data.gov details page to the actual dataset URL on the hosting agency's domain. The green boxes represent URIs for the information obtained (HTTP headers), while the purple boxes associate the information received with its source and when it was received. For more discussion on how provenance is used in LOGD and csv2rdf4lod, see
A look at how csv2rdf4lod incorporates provenance into its tabular conversions.
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Endpoint:
Thumbnail:
- 3 comments
- 2993 reads
White House Visitor Search
Description:
This demo lets users search visitors and visitees of the White House. The top 100 frequent visited people in the White House are listed.
Contributor:
Contributor:
White House Visitor Search |
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Query:
Uses SPARQL Query:
Uses SPARQL Endpoint:
Uses SPARQL Endpoint:
Thumbnail:
- Login to post comments
- 5359 reads
Tobacco Policy Adoption by US States (1990-2009)
Description:
A PopSciGrid demo presenting a chart that shows the changes of the number of states part of which has adopted tobacco policies that ban smoking in some bars, workplaces, or restaurants.
This demo is part of the Population Sciences Grid Project. For more information, please contact Professor Deborah McGuinness.
Please note: The National Cancer Institute’s (NCI) PopSciGrid Community Health Data Portal enables users to explore the relationship between cancer risk factors, health outcomes, and factors in the social and political environment. The maps, graphs, and tables on this website are not intended to convey information about causal relationships, and the NCI does not endorse any conclusions or inferences that individual users may draw from the maps, tables, or graphs produced by this website. Learn more about cancer.
Browser considerations: Firefox and IE 8 on Windows XP have difficulties displaying the following demonstrations. IE 7 on Windows Vista also has difficulties. Demonstrations can be successfully viewed using IE 8 on Windows 7, and Firefox and Safari on Mac. Flash is required for all browsers.
Using the demo: This demo shows a chart of the number of states with policies regulating use of tobacco in bars, restaurants, and workplaces from 1990 to 2007.
Data series used in this demo:
* NCI internal dataset
Contributors
National Cancer Institute
|
Rensselaer Polytechnic Institute
Northwestern University
|
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Query:
Uses SPARQL Endpoint:
Thumbnail:
- Login to post comments
- 3855 reads
Data.gov survey: Raw dataset modification dates
Description:
This demonstration shows when the data.gov datasets were last updated, as determined by their HTTP header responses. How up-to-date are the datasets listed in data.gov? We start with a time line histogram for a moment in time.
Contributor:
Process used
The following diagram shows the process used to obtain the last-modified dates of the data.gov datasets.
- 1 - csv2rdf4lod converted data.gov's 2010-Sep-13 version of Dataset 92 csv file using enhancement parameters and loaded the results (see sample) in LOGD SPARQL endpoint's named graph http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13.
- 2 - curl queries SPARQLProxy's named graph http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13 (which contains dataset http://logd.tw.rpi.edu/source/data-gov/dataset/92/version/2010-Sep-13) for data.gov's dataset identifiers.
- 3 - The data.gov details page is requested and scraped to obtain references to data sources. Redirects are followed and HTTP HEADs are recorded in RDF using Turtle syntax and terminology from the Proof Markup Language ontology.
- 4,5 - The aggregated crawl is moved to within the LOGD dataset repository (here) and loaded into the LOGD SPARQL endpoint in named graph http://logd.tw.rpi.edu/source/twc-rpi-edu/dataset/data-pointer-http-headers/version/2010-Sep-21_16-30-03 (which contains dataset http://logd.tw.rpi.edu/source/twc-rpi-edu/dataset/data-pointer-http-headers/version/2010-Sep-21_16-30-03).
- 6 - This Javascript is included within THIS PAGE to query the LOGD SPARQL endpoint for dataset modification dates (using this query and these nightly-cached results). It calculates the histogram and uses Google Visualization's Annotated Timeline to render the results. A few notes are hard-coded to provide a frame of reference.
Use of provenance
The following diagram illustrates how the Proof Markup Language was used to record the HTTP headers obtained from the government agency servers. A portion of this data graph is selected by the SPARQL query listed above (the headers are excluded). The red links show the HTTP redirects and HTML anchor hrefs from the data.gov details page to the actual dataset URL on the hosting agency's domain. The green boxes represent URIs for the information obtained (HTTP headers), while the purple boxes associate the information received with its source and when it was received. For more discussion on how provenance is used in LOGD and csv2rdf4lod, see
A look at how csv2rdf4lod incorporates provenance into its tabular conversions.
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Query:
Uses SPARQL Endpoint:
Thumbnail:
- Login to post comments
- 5914 reads
Trends in Smoking Prevalence, Tobacco Policy Coverage and Tobacco Prices (1991-2007)
Description:
A PopSciGrid demo that illustrates how tobacco policy coverage rate, cigarette price/tax, and smoking rate have changed over time.
This demo is part of the Population Sciences Grid Project. For more information, please contact Professor Deborah McGuinness.
Please note: The National Cancer Institute’s (NCI) PopSciGrid Community Health Data Portal enables users to explore the relationship between cancer risk factors, health outcomes, and factors in the social and political environment. The maps, graphs, and tables on this website are not intended to convey information about causal relationships, and the NCI does not endorse any conclusions or inferences that individual users may draw from the maps, tables, or graphs produced by this website. Learn more about cancer.
Browser considerations: Firefox and IE 8 on Windows XP have difficulties displaying the following demonstrations. IE 7 on Windows Vista also has difficulties. Demonstrations can be successfully viewed using IE 8 on Windows 7, and Firefox and Safari on Mac. Flash is required for all browsers.
Using the demo: Select a year and a data series to show a heatmap that compares data for different states on a US map (the map may be blank in some combination because impacteen datasets (other than the policy data) only cover data between 1991 and 2007). Select a state to show the evolution of data series from 1991 to 2007.
PopSciGrid Project Contributors
National Cancer Institute
|
Rensselaer Polytechnic Institute
Northwestern University
|
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Endpoint:
Thumbnail:
- Login to post comments
- 24835 reads
Interative US Tobacco Policy Coverage Map (1990-2009)
Description:
This demo illustrates how tobacco policy coverage has changed over time.
Contributor:
Uses Dataset:
Uses Technology:
Uses Technology:
Uses Technology:
Uses Technology:
Uses SPARQL Query:
Uses SPARQL Endpoint:
Thumbnail:
- 1 comment
- 1964 reads
To the extent possible under law,
Tetherless World Constellation
has waived all copyright and related or neighboring rights to
TWC LOGD. TWC LOGD is an educational project on open government data using Semantic Web technologies.
Datasets hosted on this site are converted from a number of data sources such as data.gov. All data created by us are open for reuse, and usage of data created and managed by other sources should follow their own licenses.
The data contained on this site is automatically repopulated from US government or other open data sites, and any personal data in our linked-data versions is coming from those sources. If your information is removed from the government sources, it will be automatically removed from ours on the next update.
Warning: Table './drupal/watchdog' is marked as crashed and last (automatic?) repair failed query: INSERT INTO watchdog (uid, type, message, variables, severity, link, location, referer, hostname, timestamp) VALUES (0, 'php', '%message in %file on line %line.', 'a:4:{s:6:\"%error\";s:12:\"user warning\";s:8:\"%message\";s:337:\"Table './drupal/accesslog' is marked as crashed and last (automatic?) repair failed\nquery: INSERT INTO accesslog (title, path, url, hostname, uid, sid, timer, timestamp) values('live demo', 'taxonomy/term/19', '', '10.0.1.254', 0, 'qgl5hjoanvf30ihb21staieri5', 215, 1601310425)\";s:5:\"%file\";s:58:\"/data/www/html/drupal/modules/statistics/statistics.module\";s:5:\"%line\";i:63;}', 3, '', 'https://logd.tw.rpi.edu/category/keywords/live_demo', ' in /data/www/html/drupal/includes/database.mysqli.inc on line 134