Software as a Service for Supporting Biodiversity Conservation Decision Making

  • Maria Cecilia Londoño-Murcia
  • Camilo Moreno
  • Carolina Bello
  • David Méndez
  • Mario Villamizar
  • Harold Castro
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 232)


This paper presents e-clouds as a tool to support biodiversity decision making, offering a Software as a Service (SaaS) paradigm to execute computing and technic intensive applications such as species distribution models. But mere access to these tools is not enough if usability and economy are not aligned with users interests. This article presents a friendly interface hiding all the complexities of using a public cloud infrastructure, containing an application supported by expert researchers, and an architecture behind the scenes that minimizes the cost of using such a computational and technical infrastructure, what results in a very attractive option for researchers and other stakeholders to get the most out of public clouds for their tasks.


Biodiversity Conservation Spatial analysis e-clouds SaaS 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Peterson, A.T., Robins, C.R.: Using ecological-niche modeling to predict barred owl invasions with implications for spotted owl conservation. Conservation Biology 17, 1161–1165 (2003)CrossRefGoogle Scholar
  2. 2.
    Urbina-Cardona, J.N., Flores-Villela, O.: Ecological-niche modeling and prioritization of conservation-area networks for Mexican herpetofauna. Conservation Biology 24, 1031–1041 (2010)CrossRefGoogle Scholar
  3. 3.
    Ihlow, F., Dambach, J., Engler, J.O., Flecks, M., Hartmann, T., Nekum, S., Rajaei, H., Rödder, D.: On the brink of extinction? How climate change affect global chelonian species richness and distribution. Global Change Biology 18, 1520–1530 (2012)CrossRefGoogle Scholar
  4. 4.
    Jetz, W., McPherson, J.M., Guralnick, R.P.: Integrating biodiversity distribution knowledge: toward a global map of life. Trends in Ecology and Evolution 27, 151–159 (2012)CrossRefGoogle Scholar
  5. 5.
    Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A.: Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, 1965–1978 (2005)CrossRefGoogle Scholar
  6. 6.
    Phillips, S.J., Anderson, R.P., Schapire, R.E.: Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259 (2006)CrossRefGoogle Scholar
  7. 7.
    Office of Advanced Scientific Computing Research (ASCR): The Magellan Report on Cloud Computing for Science. U.S. Department of Energy (2011) Google Scholar
  8. 8.
    Krishnan, S., Clementi, L., Jingyuan, R., Papadopoulos, P., Li, W.: Design and Evaluation of Opal2: A Toolkit for Scientific Software as a Service. In: World Conference on Services, pp. 709–716 (2009)Google Scholar
  9. 9.
    Chen, W., Cao, J., Li, Z.: Customized Virtual Machines for Software Provisioning in Scientific Clouds. In: Second International Conference on Networking and Distributed Computing (ICNDC), pp. 240–243 (2011)Google Scholar
  10. 10.
    Saripalli, P., Oldenburg, C., Walters, B., Radheshyam, N.: Implementation and Usability Evaluation of a Cloud Platform for Scientific Computing as a Service (SCaaS). In: Fourth IEEE International Conference on Utility and Cloud Computing (UCC), pp. 345–354 (2011)Google Scholar
  11. 11.
    Doddavula, S.K., Rani, M., Sarkar, S., Vachhani, H.R., Jain, A., Kaushik, M., Ghosh, A.: Implementation of a Scalable Next Generation Sequencing Business Cloud Platform. In: IEEE 4th International Conference on Cloud Computing, pp. 598–605 (2011)Google Scholar
  12. 12.
    Xiaoyong, B.: High performance computing for finite element in cloud. In: International Conference on Future Computer Sciences and Application (ICFCSA), pp. 51–53 (2011)Google Scholar
  13. 13.
    Calatrava, A., Molto, G., Hernandez, V.: Combining Grid and Cloud Resources for Hybrid Scientific Computing Executions. In: Third IEEE International Conference on Coud Computing Technology and Science, pp. 494–501 (2011)Google Scholar
  14. 14.
    Fisher, S.: The Architecture of the Apex Platform,’s Platform for Building On-Demand Applications. In: 29th International Conference on Software Engineering - Companion, p. 3 (2007)Google Scholar
  15. 15.
    Zoho Corporation Pvt. Ltd. ZOHO Work Online,
  16. 16.
    SuccessFactors, Inc. SuccessFactors,
  17. 17.
    Silicon Graphics International. Cyclone,
  18. 18.,

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Maria Cecilia Londoño-Murcia
    • 1
  • Camilo Moreno
    • 1
  • Carolina Bello
    • 1
  • David Méndez
    • 2
  • Mario Villamizar
    • 2
  • Harold Castro
    • 2
  1. 1.Instituto de Investigación de Recursos Biológicos Alexander von HumboldtBogotáColombia
  2. 2.Grupo COMIT, Departamento de Ingeniería de Sistemas y ComputaciónUniversidad de los AndesBogotáColombia

Personalised recommendations