• DocumentCode
    249536
  • Title

    Really Opened Government Data: A Collaborative Transparency at Sight

  • Author

    Sheffer Correa, Andreiwid ; Correa, Pedro L. P. ; Silva, Daniel L. ; Soares Correa da Silva, Flavio

  • Author_Institution
    Fed. Inst. Sao Paulo, Univ. of Sao Paulo, Sao Paulo, Brazil
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    806
  • Lastpage
    807
  • Abstract
    Transparency initiatives are increasingly present at all levels of government, making volume and variety of data grow as governmental institutions wish to make their administration more open. In this context, transparency portals appear as large silos of documents with heterogeneous and often unstructured data, in which the information provided is mainly through PDF, HTML, Excel spreadsheets or other print-like format. Although they allow comfortable reading to humans, these documents fail to provide a deep, integrated and multidimensional data analysis, which would allow citizens the effective use of transparency. We hence present a work in progress to structure this information and to allocate them into repositories that comply with Open Government Data principles to provide citizens with the power of machine analysis, indiscriminate and independent technology data access. We describe a collaborative framework that engages users in capturing and transforming unstructured information into machine-readable datasets.
  • Keywords
    Big Data; data analysis; government data processing; groupware; Big Data; Excel spreadsheets; HTML; PDF; collaborative transparency; data access; data analysis; machine analysis; machine-readable datasets; print-like format; really opened government data; transparency portals; unstructured data; unstructured information; Big data; Collaboration; Educational institutions; Government; HTML; Portable document format; Portals; CKAN; Collaborative system; Open Data; Openspending; Transparency; e-Government;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data (BigData Congress), 2014 IEEE International Congress on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5056-0
  • Type

    conf

  • DOI
    10.1109/BigData.Congress.2014.131
  • Filename
    6906875