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# provides secondary references that independently document some of the NetWeaver applications developed since the late 1980s (see the [[#References]] section in this article, as well as applications documented for the [[Ecosystem Management Decision Support|EMDS]] system).

First, though, a word about knowledgebases. While there are various ways of describing a [[knowledgebase]], perhaps one of the more central concepts is that a knowledgebase provides a formal specification for interpreting information.<ref>Walters, J.R., and N.R. Nielsen. 1988. Crafting Knowledge-based Systems. New York: John Wiley and Sons. 342 p.</ref> Formal in this context means that the specification is [[Ontology (information science)|ontologically committed]] <ref>Gruber, T.R. 1995. Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies 43:907-928.</ref> to the semantics and syntax prescribed by a knowledgebase processor (aka, an engine).

== A brief history ==

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First, the knowledge of individual subject-matter experts engaged in [[knowledge

engineering]] often is not fully integrated when dealing with complex problems, at least initially. Rather, this knowledge may exist in a somewhat more loosely organized state, a sort of knowledge soup with chunks of knowledge floating about in it. A common observation of knowledge engineers experienced in graphically designing [[knowledgebase]]s is that the process of constructing a graphic representation of problem-solving knowledge in a formal logical framework seems to be synergistic, with new insights into the expert’sexpert's knowledge emerging as the process unfolds. (At the moment, this assertion is largely anecdotal. Contributors to this article need to find a suitable way to document this point, because it is actually a rather important finding not simply limited to NetWeaver, but knowledge engineering more broadly).

Second, synergies similar to those observed in organizing the reasoning of individual subject-matter experts also can occur in [[knowledge engineering]] projects that require the interaction of multiple disciplines. For example, many different kinds of specialists may be involved in evaluating the overall health of a watershed. Use of a formal logic system, with well defined syntax and semantics, allows specialists’ representation of their problem solving approach to be expressed in a common language, which in turn facilitates understanding of how all the various perspectives of the different specialists fit together.

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== References ==

Barr, N.B., R.S. Copeland, M. De Meyer, D. Masiga, H.G. Kibogo, M.K. Billah, E. Osir, R.A. Wharton, and B.A. McPheron. 2006. Molecular diagnostics of economically important Ceratitis fruit fly species (Diptera: Tephritidae) in Africa using PCR and RFLP analyses. Bulletin of Entomological Research, 96: 505-521505–521. [http://journals.cambridge.org/action/displayAbstract?aid=936280 online]

Dai, J.J., S. Lorenzato and D. M. Rocke. 2004. A knowledge-based model of watershed assessment for sediment. Environmental Modelling & Software Volume 19: 423-433423–433. [https://dx.doi.org/10.1016/S1364-8152(03)00158-0 online]

Galbraith, John M., Ray B. Bryant, Robert J. Ahrens. 1998. An Expert System for Soil Taxonomy. Soil Science Volume 163: 748-758748–758. [http://journals.lww.com/soilsci/pages/articleviewer.aspx?year=1998&issue=09000&article=00008&type=abstract online]

Heaton, Jill S., Kenneth E. Nussear, Todd C. Esque, Richard D. Inman, Frank M. Davenport, Thomas E. Leuteritz, Philip A. Medica, Nathan W. Strout, Paul A. Burgess, and Lisa Benvenuti. 2008. Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises. Biodiversity and Conservation 17:575–590. [https://dx.doi.org/10.1007/s10531-007-9282-3 online]

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Hu, Z.B., X.Y. He, Y.H. Li, J.J. Zhu, Y. Mu, and Z.X. Guan. 2007. Ying yong sheng tai xue bao (The journal of applied ecology) 18:2841-5. [https://www.ncbi.nlm.nih.gov/sites/entrez online]

Janssen, R., H. Goosen, M.L. Verhoeven, J.T.A. Verhoeven, A.Q.A. Omtzigt, and E. Maltby. 2005. Decision support for integrated wetland management, Environmental Modelling & Software Volume 20: 215-229215–229. [https://dx.doi.org/10.1016/j.envsoft.2003.12.020 online]

Mendoza, G.A., and Ravi Prabhu. 2004. Fuzzy methods for assessing criteria and indicators of sustainable forest management. Ecological Indicators 3: 227-236227–236.

[https://dx.doi.org/10.1016/j.ecolind.2003.08.001 online]

Paterson, Barbara, Greg Stuart-Hill, Les G. Underhill, Tim T. Dunne, Britta Schinzel, Chris Brown, Ben Beytell, Fanuel Demas, Pauline Lindeque, Jo Tagg, and Chris Weaver. 2008. A fuzzy decision support tool for wildlife translocations into communal conservancies in Namibia, Environmental Modelling & Software Volume 23: 521-534521–534. [https://dx.doi.org/10.1016/j.envsoft.2007.07.005 online]

Porter, Andrea, Adel Sadek, and Nancy Hayden. 2006. Fuzzy Geographic Information Systems for Phytoremediation Plant Selection. J. Envir. Engrg. 132: 120. [https://dx.doi.org/10.1061/(ASCE)0733-9372(2006)132:1(120) online]

Saunders, M.C., T.J. Sullivan, B.L. Nash, K.A. Tonnessen, B.J. Miller. 2005. A knowledge-based approach for classifying lake water chemistry. Knowledge-Based Systems Volume 18: 47-5447–54. [https://dx.doi.org/10.1016/j.knosys.2004.04.006 online]

== External links ==

* [http://wwwemds.institutemountain-viewgroup.redlands.edu/emdscom/ Ecosystem Management Decision Support (EMDS) System]

* [http://rules-of-thumb.com/ Rules of Thumb, Inc.]