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F rom the walls of caves to the pages of books, human knowledge hasfound its way onto discrete surfaces as mostly printed matter. Forthe most part, the Internet has merely extended this display, albeit

with added dimensions such as multimedia, virtual worlds, and hyper-links—a “Version 0.8 (beta)” of Vannevar Bush’s memex.1

As the network transforms our work and facilitates our interactionswith others, human knowledge is increasingly authored in the networkand augmented by it. Researchers in business-process engineering, work-flow management, and even architecture and interior design have longrealized that organizational structures significantly influence workplacedynamics. The network is now the most flexible of structures, capable ofadapting instantaneously to different projects and needs—allowinghuman knowledge to be connected and augmented in astoundingly com-plex ways.

Frank Maurerand William Regli

Weavingthe Web of Reason

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Knowledge networking has been the subject ofnumerous research programs (Grid Computing,Knowledge and Distributed Intelligence, and oth-ers). The fundamental idea behind this research isthe need for substantially new ways of thinking andworking to leverage the Internet revolution in theadvancement of human knowledge. We need newtools for capturing human knowledge as it evolvesover the network, as well as tools for indexing andretrieving it for later reuse.

WHERE IS THE REASONING? Consider the problem of capturing and reusingdesign rationale in the design of a large softwaresystem, where component development is out-sourced, system integrators create custom solutionsto enable code interoperability, and so on. Wheredoes the reasoning behind design decisions andimplementation solutions go? It exists in the etherof the interaction webs created by e-mail and col-laborative work tools, in the software code and doc-umentation, and in the minds of the developersand managers involved in the project. Our tech-nologies and tools for capturing and reusing thisknowledge are in their infancy, and draw on ideasfrom disciplines as diverse as distributed AI, com-puter-supported collaborative work (CSCW), psy-chology, and information science.

Knowledge networks are networks of peopleand computer systems that work on collaborative,knowledge-intensive tasks in a distributed—oftenvirtual—enterprise. These networks will ensurethat knowledge becomes an integral part of busi-ness practices, readily accessible for the task athand—either proactively or passively. Knowledgeneeds to be gathered, filtered, and kept up-to-date.It must also be protected from unauthorizedaccess.

From a business perspective, knowledge is pret-ty useless unless it affects action. If your decision isindependent of a piece of information, there is nopoint in collecting the information. Hence, sever-al approaches tie access to knowledge to the tasksof a business process (for example, see Maurer andHolz2 and Kühn and Abecker3). The major prob-lem here is how to make sure that these knowledge-enriched process descriptions evolve according tothe changing business environment: Maintenanceis the big issue.

SEARCHING FOR DIAMONDSKnowledge networks utilize the Web as their basicmeans of communication. Distributed or even vir-

tual enterprises can integrate their business process-es and exchange data over the Internet. The Webmakes knowledge accessible to humans. They canuse a browser to read information that is madeavailable elsewhere by a knowledge provider. As aknowledge seeker, the core problem is how to findthe few diamonds for a task in the vast rough ofinformation that is accessible on the Web. For find-ing information, we currently rely on tips, portals,and search engines:

STARS: A Socio-Technical Framework for Integrating Design Knowledge over the Internet Stephen C-Y. Lu and Jian Cai

Information technologies, including the Internet, are pro-viding an infrastructure for global information sharing, buteffective support of distributed collaborative work mayrequire mechanisms to represent the expertise, intentions,and points of view of individual team members. This pro-totype system records social and technical aspects of indi-vidual perspectives on a collaborative project, and inte-grates this knowledge into a design process by reconcilingdifferent perspectives on the design data.

The Semantic Web: The Roles of XML and RDFStefan Decker, Sergey Melnik, Frank Van Harmelen, Dieter Fensel, Michel Klein, Jeen Broekstra, Michael Erdmann, and Ian Horrocks

The next generation of the World Wide Web has beenreferred to as the "Semantic Web," where information willbe machine-processible in ways that support intelligent net-work services such as information brokers and searchagents. The Semantic Web requires interoperability stan-dards that address not only the syntactic form of documentsbut also the semantic content. Standardization efforts aim-ing at semantic interoperability include the World WideWeb Consortium’s XML/XML Schema and RDF/RDFSchema. In this article, the authors propose a generalmethod for encoding ontology representation and inferencelanguages into RDF/RDF Schema, and illustrate it throughan application to Ontology Interchange Language (OIL).

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■ The fastest way to find something on the Webis by knowing where to look. The best tips oftencome from colleagues and friends who work inthe same area, have the same interests, or oth-erwise simply understand the context of yourinvestigation. Unfortunately, the tipsters maynot be around when you need them the most.

■ Portals are the Web facade of an old idea: theydefine a context and gather information that isrelevant to it. If you are interested in a specifictopic, you go to a portal that covers it, just asyou buy a journal that addresses the topic.

■ A search engine indexes the Web and uses theindex to answer a knowledge seeker’s keywordqueries. In principle, there are two ways to cre-ate an index: automatically by using informa-tion-retrieval techniques to scan text or manu-ally by having an editor read it. Bothapproaches have their limitations. The state ofthe art in automated text understanding limitsthe accuracy of automated approaches; they alsohave problems in determining relevancy. Themanual approach, on the other hand, is costlyand difficult to pace with the evolution of theWeb. So far, no search engine is able to indexthe whole Web.

How can we improve the precision (all informationfound for a query is useful) and recall (all usefulinformation is found) of knowledge on the Web?One way is to use a knowledge representation lan-guage to annotate the information available and usean inference engine to overcome the limitations ofkeyword annotations. This would allow searchengines to formally reason about the meaning of aspecific page (that is, determine its semantics).

The article by Decker et al. (pp. 63-74) in thisissue describes one possible approach toward asemantic Web. They use RDF to represent onto-logical knowledge. (For other approaches that arebased, for example, on XML representations, seethe special issue of IEEE Intelligent Systems onKnowledge Management and the Internet.4)

KNOWLEDGE AS A SERVICEUsing declarative AI-like representations and gen-eral-purpose reasoning engines will not answer allthe questions regarding support for knowledgenetworks.

First, there is the question of effort. Who anno-tates all the Web pages with formal knowledge rep-resentations, who maintains it, and who makes surethat all the knowledge represented stays compati-ble so that you can post a query to a “semantic”search engine and actually get back results from sev-eral different Web sites?

Second, will these representations really improveprecision and recall on an Internet scale? So far,there is no empirical data to answer this question.

Third, is the future of knowledge networks toprovide services instead of information? Objectsmay exist on the Web and offer their standardizedservices to interested parties. Instead of definingsemantics declaratively, a service defines semanticsoperationally. There are several trends in this direc-tion, such as application servers based on compo-nent models like Enterprise JavaBeans andMicrosoft COM, or the CORBA approach.

The article by Lu and Cai (pp. 54-62) showswhat can be built on top of a service model. Itexamines knowledge networking in the context ofdistributed engineering design and manufacturing.Traditional design environments have focused ontools, integrating data so different tools can worktogether. Cai and Lu propose creating tools thataddress how people work together to resolve con-flicts and move toward a final product. They callthis a socio-technical framework for design andintroduce us to some ideas that cross engineering,computing, and social science.

The theme articles in this issue of IEEE InternetComputing touch on some recent work in knowl-edge networking. We hope readers find them usefulin understanding some of the fundamental researchissues and enabling technologies by which we canall extend our own personal and professionalknowledge networks. ■

REFERENCES1. V. Bush, “As We May Think,” Atlantic Monthly, July 1945;

available online at http://www.isg.sfu.ca/~duchier/misc/

vbush/vbush-all.shtml.

2. F. Maurer and H. Holz, “Process-Oriented Knowledge

Management for Learning Software Organizations,” Proc.

12th Workshop on Knowledge Acquisition, Modeling, and

Management (KAW-99), 1999; available online at http://

sern.ucalgary.ca/KSI/KAW/KAW99/papers.html.

Instead of defining semanticsdeclaratively, Web services define

them operationally.

3. O. Kühn and A. Abecker, “Corporate Memories for

Knowledge Management in Industrial Practice: Prospects

and Challenges,” J. Universal Computer Science (Special

Issue on Information Technology for Knowledge Manage-

ment), vol. 3, no. 8, 1997; available online at http://www.

iicm.edu/jucs_3_8/corporate_memories_for_knowledge.

4. R. Dieng, “Knowledge Management and the Internet,”

IEEE Intelligent Systems, vol. 15, no. 3, May/June 2000, pp.

14-17.

Frank Maurer is an associate professor at the University of Cal-

gary, Canada, and co-director of the Alberta Software Engi-

neering Research Consortium (ASERC). His research inter-

ests are in e-business engineering, experience management,

and software process support. Maurer received a PhD from

the University of Kaiserslautern, Germany. He is a mem-

ber of the IEEE, the ACM, and the editorial board of IEEE

Internet Computing. More information on his work is avail-

able online at http://sern.ucalgary.ca/~maurer/.

William Regli is an assistant professor of computer science at

Drexel University, Philadelphia, and director of Drexel’s Geo-

metric and Intelligent Computing Laboratory. His research

interests are in artificial intelligence and engineering design.

Regli received a PhD from the University of Maryland at Col-

lege Park. He is the recipient of a 1998 NSF Career Award

and a member of the editorial board of IEEE Internet Com-

puting. More information on his work is available online at

http://www.mcs.drexel.edu/~regli.

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Knowledge networks are discussed in the area of knowledge man-agement. These workshops and conferences for further informa-tion include

Knowledge Management and Knowledge Distribution throughthe Internet, held at the Workshops on Knowledge Acquisition,Modeling, and Management, Banff, Canada, in 1998 and 1999 • http://sern.ucalgary.ca/KSI/KAW/KAW99/papers.html http://ksi.cpsc.ucalgary.ca/KAW/KAW98/KAW98Proc.html

International Joint Workshop on Artificial Intelligence, Workshopon Knowledge Management and Organizational Memories •http://www.dsv.su.se/ijcai-99/

Third International Conference on Practical Aspects of Knowl-edge Management, Basel, Switzerland • http://research.swisslife.ch/pakm2000/

ECAI 2000 Workshop on Knowledge Management and Organi-zational Memories •http://www-sop.inria.fr/acacia/WORKSHOPS/ECAI2000-OM/call.html

Conference on Information and Knowledge Management (CIKM) •http://www.cs.umbc.edu/cikm/

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