• DocumentCode
    249534
  • Title

    Scientific Data Infrastructure for Sustainability Science Mobile Applications

  • Author

    Herbert, Katherine G. ; Hill, Emily ; Fails, Jerry Alan ; Ajala, Joseph O. ; Boniface, Richard T. ; Cushman, Paul W.

  • Author_Institution
    Dept. of Comput. Sci., Montclair State Univ., Montclair, NJ, USA
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    804
  • Lastpage
    805
  • Abstract
    With the recent ecological and volatile climate issues, numerous concerns have arisen which have led to the rapid growth of sustainability sciences. In sustainability studies and related areas such as crisis data management, multiple communities need to interact and contribute data, and then have this data modeled for them in an effective manner. The National Science Foundation Advisory Committee for Environment Research and Education states that, "Because of the complex relationships among people, ecosystems, and the biosphere, human health and well-being are closely linked to the integrity of local, regional and global ecosystems." In our work, we look towards developing a mobile application platform that allows data integration for multiple information sources that allows the user flexibility to learn about and actively participate in understanding and helping their environment. In this paper, we address our current work with the scientific aspects of this data.
  • Keywords
    data integration; ecology; environmental science computing; mobile computing; National Science Foundation Advisory Committee for Environment Research and Education; data integration; multiple information sources; scientific data infrastructure; sustainability science mobile applications; Communities; Data collection; Data models; Decision making; Ecosystems; Meteorology; Mobile communication; Data Integration; Scientific Big Data; Sustainability Science;
  • 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.2014.130
  • Filename
    6906874