Literature DB >> 25276498

Structured Open Urban Data: Understanding the Landscape.

Luciano Barbosa1, Kien Pham2, Claudio Silva3, Marcos R Vieira1, Juliana Freire3.   

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.

Entities:  

Year:  2014        PMID: 25276498      PMCID: PMC4174913          DOI: 10.1089/big.2014.0020

Source DB:  PubMed          Journal:  Big Data        ISSN: 2167-6461            Impact factor:   2.128


  1 in total

1.  ManyEyes: a site for visualization at internet scale.

Authors:  Fernanda B Viegas; Martin Wattenberg; Frank van Ham; Jesse Kriss; Matt McKeon
Journal:  IEEE Trans Vis Comput Graph       Date:  2007 Nov-Dec       Impact factor: 4.579

  1 in total
  1 in total

1.  Data Integration for Heterogenous Datasets.

Authors:  James Hendler
Journal:  Big Data       Date:  2014-12-01       Impact factor: 2.128

  1 in total

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