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- API opendata.ramseycounty.us | Last Updated 2017-08-03T17:47:36.000Z
Dataset showing commute to work by transportation type.
- API data.edmonton.ca | Last Updated 2019-07-17T16:59:17.000Z
This was one single topic among many, from the February 2018 Mixed Topic survey. To view the survey questions, click on the following link: https://www.edmontoninsightcommunity.ca/c/a/5tKHEJ44EOxCU3WV2dl88H?t=1 Open from February 13 - 20, 2018. At the time the survey was launched survey invitations were sent to 7,131 Insight Community Members. 2,024 members completed the survey which represents a completion rate of 28%. A total of 2,071 respondents completed the survey: 2,024 Insight Community Members and 7 from the call to action button on our webpage and 40 using the anonymous link(s) on edmonton.ca/surveys which will have no demographic information. Column definitions can be found as an attachment to this dataset (under the About option, in the Attachment section).
- API finances.worldbank.org | Last Updated 2016-09-08T22:55:07.000Z
This dataset contains documents related to this project funded by the Afghanistan Reconstruction Trust Fund (ARTF). For questions, go to www.artf.af or contact: email@example.com.
- API data.edmonton.ca | Last Updated 2019-07-17T16:57:02.000Z
This was one single topic among many as part of the September 2015 Mixed Topic survey. Test link to view these questions: https://www.edmontoninsightcommunity.ca/R.aspx?a=526&as=7YW63mx6N7&t=1. Open from September 08 - 16, 2015. At the time the survey was launched survey invitations were sent to 3516 Insight Community Members. 1477 members completed the survey which represents a completion rate of 42%. A total of 1637 respondents completed the survey: 1477 Insight Community Members and 160 using the anonymous link which will have no demographic info.
- API opendata.maryland.gov | Last Updated 2019-01-31T19:53:09.000Z
*** DISCLAIMER - This web page is a public resource of general information. The Maryland Mass Transit Administration (MTA) makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the spatial data or database information provided herein. MTA and partner state, local, and other agencies shall assume no liability for errors, omissions, or inaccuracies in the information provided regardless of how caused; or any decision made or action taken or not taken by any person relying on any information or data furnished within. *** This dataset assesses rail station potential for different forms of transit oriented development (TOD). A key driver of increased transit ridership in Maryland, TOD capitalizes on existing rapid transit infrastructure. The online tool focuses on the MTA’s existing MARC Commuter Rail, Metro Subway, and Central Light Rail lines and includes information specific to each station. The goal of this dataset is to give MTA planning staff, developers, local governments, and transit riders a picture of how each MTA rail station could attract TOD investment. In order to make this assessment, MTA staff gathered data on characteristics that are likely to influence TOD potential. The station-specific data is organized into 6 different categories referring to transit activity; station facilities; parking provision and utilization; bicycle and pedestrian access; and local zoning and land availability around each station. As a publicly shared resource, this dataset can be used by local communities to identify and prioritize area improvements in coordination with the MTA that can help attract investment around rail stations. You can view an interactive version of this dataset at geodata.md.gov/tod. ** Ridership is calculated the following ways: Metro Rail ridership is based on Metro gate exit counts. Light Rail ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. MARC ridership is calculated using two (2) independent methods: Monthly Line level ridership is estimated using a statistical sampling process in line with FTA established guidelines, and approved by the FTA. This method of ridership calculation is used by the MTA for official reporting purposes to State level and Federal level reporting. Station level ridership is estimated by using person counts completed by the third party vendor. This method of calculation has not been verified by the FTA for statistical reporting and is used for scheduling purposes only. However, because of the granularity of detail, this information is useful for TOD applications. *Please note that the monthly level ridership and the station level ridership are calculated using two (2) independent methods that are not interchangeable and should not be compared for analysis purposes.
- API www.data.act.gov.au | Last Updated 2018-09-10T07:33:27.000Z
This data set provides a count and percentage of trips categorised by the purpose of the trip. This data is from individuals sampled in obtaining data for the ACT Household Travel Survey. A trip is defined as the travel between two main activities, where a stop may constitute a change in transport mode. As an example: driving from home to a park and ride facility, then catching a bus to an interchange, then walking to a shop to purchase an item and finally walking to work is comprised of 4 ‘stops’ and two ‘trips’. Note: This data represents travel and activity on an average weekday.
- API data.kcmo.org | Last Updated 2014-02-06T18:17:19.000Z
Taxicab Rate Information Card, along with information on the Taxicab Hotline, managed by the Regulated Industries Division of the Neighborhoods and Housing Services Department of the City of Kansas City, Mo.
- API opendata.lasvegasnevada.gov | Last Updated 2019-02-11T23:39:04.000Z
See "About" for field info. This dataset shows cases filed and disposed in the Las Vegas Municipal Court.
- API data.ct.gov | Last Updated 2019-06-05T21:40:30.000Z
Lists the results of all active Department of Transportation performance measures to feed a performance dashboard.
- API data.ct.gov | Last Updated 2018-04-09T15:36:58.000Z
Payroll Data, including Calendar Year 2015 through the most recent pay period. Data used in the Open Payroll application