Skip to main content
Log in

A semantic framework and software design to enable the transparent integration, reorganization and discovery of natural systems knowledge

  • Published:
Journal of Intelligent Information Systems Aims and scope Submit manuscript

Abstract

I present a conceptualization that attempts to unify diverse representations of natural knowledge while providing a workable computational framework, based on current semantic web theory, for developing, communicating, and running integrated simulation models. The approach is based on a long-standing principle of scientific investigation: the separation of the ontological character of the object of study from the semantics of the observation context, the latter including location in space and time and other observation-related aspects. I will show how current Knowledge Representation theories coupled with the object-oriented paradigm allow an efficient integration through the abstract model of a domain, which relates to the idea of aspect in software engineering. This conceptualization allows us to factor out two fundamental causes of complexity and awkwardness in the representation of knowledge about natural system: (a) the distinction between data and models, both seen here as generic knowledge sources; (b) the multiplicity of states in data sources, handled through the hierarchical composition of independently defined domain objects, each accounting for all states in one well-known observational dimension. This simplification leaves modelers free to work with the bare conceptual bones of the problem, encapsulating complexities connected to data format, and scale. I will then describe the design of a software system that implements the approach, referring to explicit ontologies to unambiguously characterize the semantics of the objects of study, and allowing the independent definition of a global observation context that can be redefined as required. I will briefly discuss applications to multi-scale, multi-paradigm modeling, intelligent database design, and web-based collaboration.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Alexandrescu, A. (2001). Modern C++ design: Generic program and design patterns applied. New York, NY: Addison-Wesley.

    Google Scholar 

  • Allen, T. F. H., & Starr, T. B. (1982). Hierarchy: Perspectives for ecological complexity. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • AMD (URL). The african mammals databank. Internet: http://gorilla.bio.uniroma1.it/amd.

  • Argonne National Laboratories (URL). Review of the Dynamic Information Architecture System (DIAS). Internet: http://www.dis.anl.gov/DEEM/DIAS.

  • Costanza, R., Duplisea, D., & Kautsky, U. (1998). Ecological modelling and economic systems with STELLA Introduction. Ecological Modelling, 110, 1–4.

    Article  Google Scholar 

  • CRAN (URL). The comprehensive R archive network. Internet: http://www.ci.tuwien.ac.at/R.

  • DMSO (URL). DoD high level architecture. Internet: http://www.dmso.mil/projects/hla.

  • Doan, A., J. Madhavan, J., Domingos, P., & Halevy, A. Y. (2002). Learning to map between ontologies on the semantic web. In Proceedings of the eleventh international conference on World Wide Web, May 07–11, Honolulu, Hawaii, USA.

  • ESD (URL). The ecosystem services database. Internet: http://esd.uvm.edu.

  • Fishwick, P. (1995). Simulation model design and execution: Building digital worlds. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Fritzson, P., & Engelson, V. (1998). Modelica—A unified object-oriented language for system modelling and simulation. In Proceedings of European Conference on Object-Oriented Programming (ECOOP98), Brussels, July 20–24, 1998. Internet: http://citeseer.nj.nec.com/fritzson98modelica.html.

  • GBIF (URL). Global biodiversity information facility. Internet: http://www.gbif.org.

  • GEON (URL). GEON Cyberinfrastructure for the geosciences. Internet: http://www.geongrid.org.

  • Grundy, J. C. (2000). Multi-perspective specification, design and implementation of software components using aspects. International Journal of Software Engineering and Knowledge Engineering, 20(6).

  • Gupta, A., Ludaescher, B., & Martone, M. E. (2000). Knowledge-based integration of neuroscience data sources. In 12th Intl. Conference on Scientific and Statistical Database Management (SSDBM), pp. 39–52. Berlin, Germany: IEEE Computer Society.

  • HPS (1995). STELLA User’s manual. High performance systems.

  • IMA (URL). Integrating modelling architecture home page. Internet: http://www.integratedmodelling.org.

  • ISO (URL). ISO/TC211 Geographic information metadata standard. Internet: http://www.isotc211.org.

  • Ives, Z. G., Halevy, A. Y., Mork, P., & Tatarinov, I. (2004.) Piazza: Mediation and integration infrastructure for Semantic Web data. Web Semantics: Science, Services and Agents on the World Wide Web, 2, 155–175.

  • Ludaescher, B., Altintas, I., & Gupta, A. (2002). Time to leave the trees: From syntactic to conceptual querying of XML. In Intl. Workshop on XML data management, in junction with Conference on Extending Database Technology (EDBT). Prague, March 2002.

  • Ludaescher, B., Gupta, A., & Martone, M. E. (2001). Model-based mediation with domain maps. Proceedings 17th Intl. Conference on Data Engineering (ICDE), Heidelberg, Germany.

  • Madhavan, J., Bernstein, P. A., Domingos, P., & Halevy, A. Y. (2002). Representing and reasoning about mappings between domain models. Proceedings of the Eighteenth National Conference on Artificial Intelligence (pp. 80–86). Edmonton, Alberta, Canada.

  • Michener, W. K., Beach, J. H., Jones, M. B., Ludaescher, B., Pennington, D. D., et al. (2004). A knowledge environment for the biodiversity and ecological sciences. Journal of Intelligent Information Systems, in this issue.

  • Minar, N., Burkhart, R., Langton, C., & Askenazi, M. (1996). The swarm simulation system: A toolkit for building multi-agent simulations. Santa Fe Institute Working Paper 96-06-042.

  • Mosterman, P., & Vangheluwe, H. L. (2000). Computer automated multi paradigm modeling in control system design. In A. Varga (Ed.), IEEE International Symposium on Computer-Aided Control System Design, 65–70. Anchorage, Alaska; IEEE Computer Society Press.

  • OWL (URL). OWL Web Ontology Language Guide W3C Recommendation 10 February 2004. Internet: http://www.w3.org/TR/owl-guide.

  • PBI: Partnership for Biological Informatics (URL). Ecological metadata language (EML). Internet: http://www.ecoinformatics.org/software/eml.

  • PostgreSQL (URL). PostgreSQL home page. Internet: http://www.postgresql.org.

  • Ptolemy (URL). The Ptolemy project. Internet: http://ptolemy.eecs.berkeley.edu.

  • RDF (URL). Resource Description Framework (RDF). Internet: http://www.w3.org/RDF.

  • RDQL (URL). RDQL—A Query Language for RDF W3C Member Submission 9 January 2004. Internet: http://www.w3.org/Submission/RDQL/.

  • SciDI: SEMANTIC MEDIATION IDENTIFIED AS APPROACH TO SCI DATA INTEGRATION (2002). Scientific Data Integration Panel, Intl. Conf. On Extending Database Technology (EDBT), Prague, March 2002.

  • SEEK (URL). Science Environment for Ecological Knowledge (SEEK). Internet: http://seek.ecoinformatics.org.

  • SIMILE (URL). Simulistics home page. Internet: http://www.simulistics.com.

  • Simulink (URL). Mathworks home page. Internet: http://www.mathworks.com.

  • Stevenson, R. D., Haber, W. A., & Morris, R. A. (2003). Electronic field guides and user communities in the eco-informatics revolution. Conservation Ecology, 7(1), 3. Internet: http://www.consecol.org/vol7/iss1/art3.

  • Stockinger, H., Rana, O., Moore, R., & Merzky, A. (2001). Data management for grid. Environments, High Performance Computing and Networking (HPCN 2001), Amsterdam, NL, June 2001.

  • TDWG (URL). International working group on taxonomic databases. Internet: http://www.tdwg.org.

  • Vangheluwe, H. L., Kerckhoffs, E. J. H., & Vansteenkiste, G. C. (2001). Computer automated modelling of complex systems. In E. J. H. Kerckhoffs, & M. Snorek (Eds.), 15th European Simulation Multi-conference (ESM), 7–18. Prague, Czech Republic; Society for Computer Simulation International (SCS).

  • Villa, F. (1992). New computer architectures as tools for ecological thought. Trends in Ecology and Evolution, 7, 179–183.

    Article  Google Scholar 

  • Villa, F. (2001). Integrating modelling architecture: A declarative framework for multi-scale, multi-paradigm ecological modelling. Ecological Modelling, 137, 23–42.

    Article  Google Scholar 

  • Villa, F., & Costanza, R. (2000). Design of multi-paradigm integrating modelling tools for ecological research. Environmental Modelling and Software, 15, 169–177.

    Article  Google Scholar 

  • Villa, F., Wilson, M. A., DeGroot, R., Farber, S., Costanza, R., & Boumans, R. M. J. (2002). Design of an integrated knowledge base to support ecosystem services valuation. Ecological Economics, 41, 445–456.

    Article  Google Scholar 

  • XQUERY (URL). XQuery 1.0: An XML query language. W3C Working Draft 12 November 2003. http://www.w3.org/TR/xquery.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ferdinando Villa.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Villa, F. A semantic framework and software design to enable the transparent integration, reorganization and discovery of natural systems knowledge. J Intell Inf Syst 29, 79–96 (2007). https://doi.org/10.1007/s10844-006-0032-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10844-006-0032-x

Keywords

Navigation