Component-based end-user database design for ecologists

  • Authors:

  • Judith Bayard Cushing;Nalini Nadkarni;Michael Finch;Anne Fiala;Emerson Murphy-Hill;Lois Delcambre;David Maier

  • Affiliations:

  • The Evergreen State College, Olympia, USA 98505;The Evergreen State College, Olympia, USA 98505;Department of Planetary Sciences, Lunar and Planetary Laboratory, University of Arizona, Tucson, USA 85721;The Evergreen State College, Olympia, USA 98505;Portland State University, Portland, USA 97201;Portland State University, Portland, USA 97201;Portland State University, Portland, USA 97201

  • Venue:
  • Journal of Intelligent Information Systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

To solve today's ecological problems, scientists need well documented, validated, and coherent data archives. Historically, however, ecologists have collected and stored data idiosyncratically, making data integration even among close collaborators difficult. Further, effective ecology data warehouses and subsequent data mining require that individual databases be accurately described with metadata against which the data themselves have been validated. Using database technology would make documenting data sets for archiving, integration, and data mining easier, but few ecologists have expertise to use database technology and they cannot afford to hire programmers. In this paper, we identify the benefits that would accrue from ecologists' use of modern information technology and the obstacles that prevent that use. We describe our prototype, the Canopy DataBank, through which we aim to enable individual ecologists in the forest canopy research community to be their own database programmers. The key feature that makes this possible is domain-specific database components, which we call templates. We also show how additional tools that reuse these components, such as for visualization, could provide gains in productivity and motivate the use of new technology. Finally, we suggest ways in which communities might share database components and how components might be used to foster easier data integration to solve new ecological problems.