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Structured Open Urban Data: Understanding the Landscape

Overview of attention for article published in Big Data, September 2014
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#13 of 296)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
twitter
49 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
50 Dimensions

Readers on

mendeley
101 Mendeley
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Title
Structured Open Urban Data: Understanding the Landscape
Published in
Big Data, September 2014
DOI 10.1089/big.2014.0020
Pubmed ID
Authors

Luciano Barbosa, Kien Pham, Claudio Silva, Marcos R. Vieira, Juliana Freire

Abstract

A growing number of cities are now making urban data freely available to the public. Besides promoting transparency, these data can have a transformative effect in social science research as well as in how citizens participate in governance. These initiatives, however, are fairly recent and the landscape of open urban data is not well known. In this study, we try to shed some light on this through a detailed study of over 9,000 open data sets from 20 cities in North America. We start by presenting general statistics about the content, size, nature, and popularity of the different data sets, and then examine in more detail structured data sets that contain tabular data. Since a key benefit of having a large number of data sets available is the ability to fuse information, we investigate opportunities for data integration. We also study data quality issues and time-related aspects, namely, recency and change frequency. Our findings are encouraging in that most of the data are structured and published in standard formats that are easy to parse; there is ample opportunity to integrate different data sets; and the volume of data is increasing steadily. But they also uncovered a number of challenges that need to be addressed to enable these data to be fully leveraged. We discuss both our findings and issues involved in using open urban data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 49 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 7%
France 1 <1%
Ireland 1 <1%
Australia 1 <1%
Austria 1 <1%
India 1 <1%
Brazil 1 <1%
Unknown 88 87%

Demographic breakdown

Readers by professional status Count As %
Student > Master 28 28%
Student > Ph. D. Student 24 24%
Other 10 10%
Researcher 8 8%
Student > Postgraduate 6 6%
Other 12 12%
Unknown 13 13%
Readers by discipline Count As %
Computer Science 37 37%
Engineering 10 10%
Social Sciences 9 9%
Agricultural and Biological Sciences 5 5%
Earth and Planetary Sciences 4 4%
Other 19 19%
Unknown 17 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 85. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2016.
All research outputs
#537,918
of 26,558,784 outputs
Outputs from Big Data
#13
of 296 outputs
Outputs of similar age
#4,788
of 249,304 outputs
Outputs of similar age from Big Data
#1
of 8 outputs
Altmetric has tracked 26,558,784 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 296 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 249,304 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them