A Smart e-Science Cyberinfrastructure for Cross-Disciplinary Scientific Collaborations

  • Hock Beng Lim
  • Mudasser Iqbal
  • Yuxia Yao
  • Wenqiang Wang
Part of the Annals of Information Systems book series (AOIS, volume 11)


Large-scale cross-disciplinary scientific collaborations are increasingly common and require an overarching e-Science cyberinfrastructure. However, the ad hoc and incoherent integration of computational and storage resources, sensor networks, and scientific data sharing and knowledge inference models cannot effectively support cross-domain and collaborative scientific research. In this work, we design and develop a smart e-Science cyberinfrastructure which forms the key resource-sharing backbone that enables each participating scientific community to expose their sensor, computational, data, and intellectual resources in a service-oriented manner, accompanied by the domain-specific knowledge.


Sensor Network Virtual Organization Resource Discovery Grid Infrastructure Brokerage Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by Microsoft Research, Intelligent Systems Center of Nanyang Technological University, Research Support Office of Nanyang Technological University, the Singapore National Research Foundation (NRF) under grant numbers NRF-G-CRP-2007-02 and NRF2008IDM-IDM001-005, and the Singapore National Research Foundation (NRF) through the Singapore-MIT Alliance for Research and Technology (SMART) Center for Environmental Sensing and Modeling (CENSAM).


  1. 1.
    Joseph, J., Fellenstein, C.: Grid Computing. IBM Press, USA (2004)Google Scholar
  2. 2.
    Sotomayor, B., Childers, L.: Globus Toolkit 4 Programming Java Services. Morgam Kaufmann, San Francisco (2006)Google Scholar
  3. 3.
    Leymann, F., Güntzel, K.: The business grid: Providing transactional business processes via grid services. In: Proceedings of the International Conference on Service Oriented Computing (ICSOC), Trento, Italy (2003)Google Scholar
  4. 4.
    McKee, P.: Grid – the ‘white knight’ for business? BT Technology Journal 23(3) (July 2005) 45–51Google Scholar
  5. 5.
    Zhang, L., Li, H., Lam, H.: Toward a business process grid for utility computing. In: IT Professional, IEEE Computer Society, 6(5), (September/October 2004) 62–64Google Scholar
  6. 6.
    Korpela, E., Werthimer, D., Anderson, D., Cobb, J., Lebofsky, M.: SETI@home – Massively distributed computing for SETI. Computing in Science & Engineering 3(January) (2001) 78–83Google Scholar
  7. 7.
    Alonso, G., Casati, F., Kuno, H., Machiraju, V.: Web Services: Concepts, Architectures and Applications. Springer, Berlin (2003)Google Scholar
  8. 8.
    Singh, M.P., Huhns, M.N.: Service-Oriented Computing Semantics, Processes, Agents. Wiley, New York (2005)Google Scholar
  9. 9.
    Stuckenschmidt, H.: van Harmelen, F.: Information sharing on the semantic web. Advanced Information and Knowledge Processing. Springer, Heidelberg (2005)Google Scholar
  10. 10.
    Uschold, M., Gruninger, M.: Ontologies: Principles, methods and applications. Knowledge Engineering Review 11(2) (1996) 93–115CrossRefGoogle Scholar
  11. 11.
    Guarino, N., Carrara, M., Giaretta, P.: An ontology of meta-level categories. Proceedings of the 4th International Conference on Knowledge Representation and Reasoning (KR94), Morgan Kaufmann, San Mateo, CA (1994)Google Scholar
  12. 12.
    TeraGrid, http://www.teragrid.org/. Accessed 18 Jul 2010
  13. 13.
    Yamamoto, N., Nakamura, R., Yamamoto, H., Tsuchida, S., Kojima, I., Tanaka, Y., Sekiguchi, S.: GEO grid: Grid infrastructure for integration of huge satellite imagery and geosciences. In: Proceedings of the 6th IEEE/ACM International Conference on Computer and Information Technology (CIT), Seoul, Korea, (2006) 75Google Scholar
  14. 14.
    The London e-Science Center, http://www.lesc.ic.ac.uk. Accessed 18 Jul 2010
  15. 15.
    The Cambridge e-Science Center, http://www.escience.cam.ac.uk. Accessed 18 Jul 2010
  16. 16.
    Alper, P., Corcho, O., Kotsiopoulos, I., Missier, P., Bechhofer, S., Kuo, D., Goble, C.: S-OGSA as a reference architecture for OntoGrid and for the semantic grid. In: Proceedings of the 16th Global Grid Forum (GGF16) Semantic Grid Workshop, Athens, Greece, February (2006)Google Scholar
  17. 17.
    MyGrid: http://www.mygrid.org.uk/. Accessed 18 Jul 2010
  18. 18.
    Hull, D., Wolstencroft, K., Stevens, R., Goble, C., Pocock, M., Li, P., Oinn, T.: Taverna: A tool for building and running workflows of services. Nucleic Acids Research 34 (2006) 729–732CrossRefGoogle Scholar
  19. 19.
    Cyberinfrastructure for the Centre for Environmental Sensing and Modeling, http://censam.mit.edu/research/res5/index.html#sec4. Accessed 18 Jul 2010
  20. 20.
    The National Weather Study Project, http://nwsp.ntu.edu.sg. Accessed 18 Jul 2010
  21. 21.
    Sensor Grid for GPS Data Processing Project, http://sensorgrid.ntu.edu.sg/gps. Accessed 18 Jul 2010
  22. 22.
    The LiveE! Project, http://www.live-e.org/en/index.html. Accessed 18 Jul 2010
  23. 23.
    e-Science Ontology, http://sensorgrid.ntu.edu.sg/SmarteScience.html. Accessed 18 Jul 2010
  24. 24.
    The Open Geospatial Consortium, http://www.opengeospatial.org. Accessed 18 Jul 2010
  25. 25.
    Semantic Web for Earth and Environmental Terminology (SWEET), http://sweet.jpl.nasa.gov/ontology. Accessed 18 Jul 2010
  26. 26.
    Geography Markup Language, http://www.opengeospatial.org/standards/gml. Accessed 18 Jul 2010
  27. 27.
    Sensor Web Enablement Working Group, http://www.opengeospatial.org/projects/groups/sensorweb. Accessed 18 Jul 2010
  28. 28.
    Sensor ML, http://www.opengeospatial.org/standards/sensorml. Accessed 18 Jul 2010
  29. 29.
    Pease, A., Niles, I., Li, J.: The suggested upper merged ontology: A large ontology for the semantic web and its applications. In: Working Notes of the AAAI-2002 Workshop on Ontologies and the Semantic Web, Edmonton, Canada, July (2002)Google Scholar
  30. 30.
    Russomanno, D.J., Goodwin, J.C.: OntoSensor: An Ontology for Sensor Network Application Development, Deployment, and Management, Handbook of Wireless Mesh and Sensor Networking. McGraw Hill, New York (2008)Google Scholar
  31. 31.
    OWL Web Ontology Language Reference, Mike Dean and Guus Schreiber, Editors, W3C Recommendation, 10 February 2004, http://www.w3.org/TR/2004/REC-owl-ref-20040210/ Latest version available at http://www.w3.org/TR/owl-ref/. Accessed 18 Jul 2010
  32. 32.
    Liu, J., Zhao, F.: Towards semantic services for sensor-rich information systems. In: Proceedings of the 2nd IEEE/CreateNet International Workshop on Broadband Advanced Sensor Networks, Boston, MA, October (2005)Google Scholar
  33. 33.
    OWL-S. http://www.daml.org/services/owl-s. Accessed 18 Jul 2010
  34. 34.
    Lim, H.B., Iqbal, M., Wang, W., Yao, Y.: The national weather sensor grid: A large-scale cyber-sensor infrastructure for environmental monitoring. International Journal of Sensor Networks (IJSNet), Inderscience 7(1/2) (2010) 19–36CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Hock Beng Lim
    • 1
  • Mudasser Iqbal
    • 1
  • Yuxia Yao
    • 1
  • Wenqiang Wang
    • 1
  1. 1.Intelligent Systems CenterNanyang Technological UniversitySingaporeSingapore

Personalised recommendations