Volume 1, Number 25 http://isedj.org/1/25/ December 27, 2003

In this issue:

Preparing for the Semantic Web

Antonio M. Lopez, Jr Xavier University of Louisiana New Orleans, LA 70125

Abstract: As today’s undergraduates in computer information systems work towards learning those skills needed in the world of e-Commerce (e.g., HTML, Java, XML, etc.), an enhancement to the World Wide Web is being “spun.” The Semantic Web is the envisioned end-state for the movement of the World Wide Web from words, images, and audio understood only by humans to those same things “wrapped in” organizing concepts and relationships understood by both humans and software agents. Since the Semantic Web is a research effort under the auspices of the World Wide Web Consortium, how are faculty members to expose students to the emerging technology that will impact how e-Commerce will be supported in the future? This paper highlights some of the World Wide Web Consortium work done thus far in moving the current Web toward a Semantic Web. It next presents an overview of ontology development, the key enabling technology for the Semantic Web. Finally, it shows how undergraduate researchers, mentored by their faculty members, can develop ontologies that lead naturally into preparing for the Semantic Web.

Keywords: World Wide Web, e-Commerce, semantic web, ontology, undergraduate research

Recommended Citation: Lopez (2003). Preparing for the Semantic Web. Information Systems Education Journal, 1 (25). http://isedj.org/1/25/. ISSN: 1545-679X. (Also appears in The Proceedings of ISECON 2003: §2521. ISSN: 1542-7382.)

This issue is on the Internet at http://isedj.org/1/25/ ISEDJ 1 (25) Information Systems Education Journal 2

The Information Systems Education Journal (ISEDJ) is a peer-reviewed academic journal published by the Education Special Interest Group (EDSIG) of the Association of Information Technology Professionals (AITP, Chicago, Illinois). • ISSN: 1545-679X. • First issue: 2003. • Title: Information Systems Education Journal. Variant titles: IS Education Journal; IS Ed Journal; ISEDJ. • Physical format: online. • Publishing frequency: irregular; as each article is approved, it is published immediately and constitutes a complete separate issue of the current volume. • Single issue price: free. • Subscription address: [email protected]. • Subscription price: free. • Electronic access: http://isedj.org/ • Contact person: Don Colton ([email protected])

Editor Don Colton Brigham Young Univ Hawaii Laie, Hawaii

The Information Systems Education Conference (ISECON) solicits and presents each year papers on topics of interest to IS Educators. Peer-reviewed papers are submitted to this journal.

ISECON Papers Chair Associate Papers Chair Associate Papers Chair William J. Tastle Mark (Buzz) Hensel Amjad A. Abdullat Ithaca College Univ of Texas at Arlington West Texas A&M Univ Ithaca, New York Arlington, Texas Canyon, Texas

EDSIG activities include the publication of ISEDJ, the organization and execution of the annual ISECON conference held each fall, the publication of the Journal of Information Systems Education (JISE), and the designation and honoring of an IS Educator of the Year. • The Foundation for Information Technology Education has been the key sponsor of ISECON over the years. • The Association for Information Technology Professionals (AITP) provides the corporate umbrella under which EDSIG operates. AITP celebrates its 50th year as a professional society in 2003.

c Copyright 2003 EDSIG. In the spirit of academic freedom, permission is granted to make and distribute unlimited copies of this issue in its PDF or printed form, so long as the entire document is presented, and it is not modified in any substantial way.

c 2003 EDSIG http://isedj.org/1/25/ December 27, 2003 ISEDJ 1 (25) Lopez 3

Preparing for the Semantic Web

Antonio M. Lopez, Jr. Computer Sciences and Computer Engineering Department Xavier University of Louisiana New Orleans, LA 70125, USA

Abstract

As today’s undergraduates in computer information systems work towards learning those skills needed in the world of e-Commerce (e.g., HTML, Java, XML, etc.), an enhancement to the World Wide Web is being “spun.” The Semantic Web is the envisioned end-state for the movement of the World Wide Web from words, images, and audio understood only by humans to those same things “wrapped in” organizing concepts and relationships understood by both humans and software agents. Since the Semantic Web is a research effort under the auspices of the World Wide Web Consortium, how are faculty members to expose students to the emerging technology that will impact how e-Commerce will be supported in the future?

This paper highlights some of the World Wide Web Consortium work done thus far in moving the current Web toward a Semantic Web. It next presents an overview of ontology develop- ment, the key enabling technology for the Semantic Web. Finally, it shows how undergradu- ate researchers, mentored by their faculty members, can develop ontologies that lead natu- rally into preparing for the Semantic Web.

Keywords: World Wide Web, e-Commerce, semantic web, ontology, undergraduate research

1. INTRODUCTION valuable corporate asset, and this knowledge needs to be shared with global partners so The World Wide Web (WWW) is a popular that each can improve their competitive communications medium for the exchange of edge and increase their market shares. information among people – i.e., individuals Competitive businesses must find effective or people who are members of or represent ways of working together to achieve their organized groups (non-profit) or businesses goals. RosettaNet (www.rosettanet.org) is (profit). The computers that people use, an example of a non-profit consortium of whether sitting on their desks at work, in major information technology, electronic their homes, accompanying them on busi- components, and semiconductor manufac- ness trips, in cyber-cafes where they social- turing businesses working to create and im- ize, or in public libraries where they study, plement industry-wide, open business proc- are all potential points of entry into the ess standards. In B2C, today’s customers WWW network of information exchange and usually spend a significant amount of time business transactions. Unfortunately, the browsing for businesses that sell a desired success of the communications medium and product and, typically, only a few such busi- the large volume of information that it pro- nesses are browsed before customer ex- vides have actually hampered e-Commerce haustion occurs and the customer settles for growth (Davies et al. 2003), both e-Business what has been found. Competitive busi- (B2B) and Web-Commerce (B2C). In B2B nesses must find effective ways of reaching for example, today’s businesses are coming customers. Makebuzz to the realization that their knowledge is a (www.makebuzz.com) is an example of a for

c 2003 EDSIG http://isedj.org/1/25/ December 27, 2003 ISEDJ 1 (25) Lopez 4 profit company that combines a massive nology officer for software at Hewlett- bank of online marketing knowledge and Packard, is quoted as saying, “We expect the artificial intelligence (AI) strategies to in- Semantic Web to be as big a revolution as crease the chances that their client’s prod- the original Web itself.” ucts will be visible enough on a popular search engine listing so that a potential cus- Starting with the current Web, a community tomer might select them for further product of users must decide how information on a browsing. Web page can be given well-defined seman- tics, thus making this new Semantic Web While RosettaNet and Makebuzz are respec- page understandable to a software agent. tively today’s solution to the corporation’s The community of users that has accepted sharing of business knowledge problem and this challenge is the World Wide Web Con- the customer’s information overload prob- sortium (W3C). W3C (www.w3c.org) is a lem, tomorrow’s solution can be found, in very active organization having offices in part, in the use of software agents (also Valbonne, ; Cambridge, MA, USA; and called intelligent agents) that “understand” Tokyo, with a full-time staff of more Web pages. Software agents are computer than 60 and more than 500 member organi- programs that work without direct human zations (Cherry 2002). Slowly but surely, control or constant supervision to achieve W3C has been moving the Web toward the goals set forth by humans (Stojkovic and Semantic Web end-state. Two important Lupton 2000). If the WWW was under- steps were the extensible markup language standable to software agents, much more so (XML) and the resource description frame- than today’s keyword match or heuristic work (RDF). search of hyperlinks, then software agents could collect, filter, and process desired in- Presently, XML allows creators of Web pages formation found on the WWW for customers to produce and use their own markup tags or businesses. At present, both elements of (Boggs 2002). However, if other users of e-Commerce (B2B and B2C) are being held the Web know the meaning of the XML tags, back by the lack of standards for (1) repre- then they too can write scripts that make sentation of the information contained on a use of those tags. Thus, a small step has Web page, (2) translation of that information been taken to represent the information con- into other more useful forms, and (3) de- tained on a Web page and make it under- scription of content that is software agent standable to a software agent. Unfortu- understandable (Fensel 2001). If standards nately, XML does not provide standard data in these three areas are defined, then com- structures and terminologies to describe mercial software can be developed to auto- business processes and the exchange of matically encode the semantics of a Web product information (Fensel 2001). So as page as the Web page is being created. Fur- far as a software agent is concerned, the thermore, these standards will facilitate the translation issue (mentioned in the previous creation of software agents that collect Web section as needing standardization) has not content from different sources, refine the been sufficiently advanced with XML; thus content, and exchange it with other software the need for RDF. The RDF data model, agents. which is equivalent to the semantic network formalism, consists of resources, properties, 2. THE SEMANTIC WEB and statements written using XML tags (Gomez-Perez 2002). Universal Resource The Semantic Web was initially described as Identifiers (URIs) can be used in identifying “the conceptual structuring of the Web in an resources, properties, and statements. The explicit machine-readable way” (Berners-Lee RDF Schema (RDFS) provides a means of and Fischetti 1999). Later, Berners-Lee et defining relationships between resources and al. (2001) wrote, “The Semantic Web will properties. Hence, RDFS provides the basics bring structure to the meaningful content of for defining knowledge models that are simi- Web pages, creating an environment where lar to frame-based systems. software agents roaming from page to page can readily carry out sophisticated tasks for The Defense Advanced Research Projects users.” In an issue of Business Week (Port Agency (DARPA) has also supported the de- 2002), Richard Hayes-Roth, the chief tech- velopment of the Semantic Web. In an ef-

c 2003 EDSIG http://isedj.org/1/25/ December 27, 2003 ISEDJ 1 (25) Lopez 5 fort to make Web content more accessible structuring the Web into the Semantic Web. and understandable to agents (human and Figure 1 is a semantic network with some software), DARPA has funded research in basic knowledge that someone may want to languages, tools, infrastructure, and applica- impart on a Web page (e.g., This might be tions. Based upon XML and RDF, the DARPA the beginnings of a logical theory: Men and Markup Language (DAML) was developed women are humans.). and coupled with the Ontology Inference Layer (OIL) to produce DAML + OIL, a pro- Human posed starting point for the W3C’s Semantic Web activity’s known as the Ontology Web Language (OWL) (McGuinness et al 2002). subClassOf subClassOf Web integration, frame-based systems, and description logics inspired the specification of OWL. W3C’s most recent release of DAML + OIL was March 2001, and the deadline for Man Woman the call for comment on the “last working- draft” of OWL was March 2003. Figure 1. We conclude this section with a small exam- ple that demonstrates research work in

xmlns:rdfs=”http://www.w3.org/2000/01/rdf-schema#”

xmlns:daml=”http://www.daml.org/2001/03/daml+oil#” >

World Wide Web Consortium

Human

Table 1

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Table 1 shows the markup language imple- sum, an ontology structure consists of two mentation of the semantic network adding disjoint sets, a set of concepts and a set of information about who might have published relations. An ontology structure has a con- the Web page and two new ideas. The first cept hierarchy or taxonomy expressing rela- idea is that every human is either a man or tions between concepts, for example a woman (disjointness). The second idea is “Woman subClassOf Human”, which is found that the concept of human is the same as in Figure 1 and encoded in Table 1. It also the concept of a human being (sameness). has function relations that relate concepts The encoding using XML, RDF, RDFS, and non-taxonomically (others would call these DAML is straightforward but still subject to attributes of concepts with values to be es- change as W3C continues its research work tablished with specific instances of that con- (i.e., OWL). However, the underpinning is cept). Finally, the ontology has axioms ex- without doubt the ontological structures rep- pressed in an appropriate logical language resented, in part, by semantic networks. (e.g., first order logic). In Table 1, we em- bedded the ontology axiom “Human disjoin- 3. ONTOLOGY DEVELOPMENT tUnionOf Man and Woman.” As will be seen below, for our purpose of preparing students Ontologies are a key enabling technology for for the Semantic Web, we take a more in- the Semantic Web because of what ontolo- formal, graphical approach that can be en- gies promise – a shared and common under- coded in a first order predicate calculus pro- standing of a domain that can be communi- gramming language. Our experience is that cated between people and software systems undergraduates easily understand this ap- (Davies et al. 2003). An ontology is a logical proach to ontology development. theory which gives an explicit, partial ac- count of a conceptualization; it is an inten- Ontology development can be accomplished tional semantic structure that encodes the top-down (Lenat 1995) or bottom-up (van implicit rules constraining the structure of a der Vet and Mars 1998). A top-down devel- piece of reality (Guarino and Giaretta 1995). opment of an ontology structure for a large In the early 1990s AI researchers struggled knowledge-based system can take years to with concepts such as metadata (Lopez and construct, so developers do well to import Saacks 1992), meta-knowledge (Lopez existing top-level ontologies and combine 1993), and their combined use in informa- them with knowledge from several inde- tion management systems (Saacks-Giguette pendently developed bottom-up ontologies. and Lopez 1993) to provide a vocabulary of Ontologies developed bottom-up are called terms and relations that would facilitate the domain ontologies, and they contain the development of some domain model (The terms that are useful in a wide range of dif- previous three references are rooted in a ferent applications within a specific domain. NASA domain called the Earth Observing In a mature domain such as high school al- System). Gruber (1993) was the first to use gebra word problems there is widespread the term “ontology,” which he wrote was “a agreement on the basic terms and relation- specification of a conceptualization.” Since ships, for example objects (people, car, then, the AI community has adopted ontol- etc.), actions (walk, drive, etc.), algebraic ogy development as a pre-requisite to build- relationships, and types of problems (dis- ing knowledge-based systems because every tance-rate-time, mixture, work, etc.). How- knowledge model has an ontological com- ever in a domain such as religion, there is mitment (Noy and Hafner 1997); that is, the not as much widespread agreement. Do- ontology captures the set of concepts, main ontologies have been successfully de- terms, and relationships used to describe the veloped for military applications (Valenti et knowledge of the software system. al. 1999; Bowman et al. 2001) as well as library applications (Weinstein and Alloway Maedche (2002) gives a mathematically rig- 1997; Welty and Jenkins 1999). orous definition of an ontology structure, one that developers of the Semantic Web Although differences can exist conceptually will rely upon to organize the underlying regarding what should or should not be in an metadata and meta-knowledge of a domain ontological structure, there is some general for the purpose of comprehensive and trans- agreement on a number of basic issues. As portable software agent understanding. In Chandrasekaran et al. (1999) explained: (1)

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A domain ontology contains the names of use it. The software agent must understand objects that are found in the domain. (2) that John did not always have size 11W Relationships exist between the objects. (3) court ; he grew into them over time. Objects can have parts. (4) Objects have Perhaps, in that time period, there is a re- attributes that can take on values. (5) At- cord that John regularly purchased court tributes and relationships can change over shoes. time. (6) There are processes that occur over time in which objects participate. To To be useful, a domain ontology must be a illustrate these points of agreement consider highly internally coherent logical theory hav- the domain ontology (Figure 2). The ing specific “gates” though which interaction objects in the Shoe ontology are the nodes with other domain ontologies can occur. of the diagram (e.g., Moccasins, Boots, The question is: How does a developer test etc.). Labeled lines connecting nodes ex- the coherence of the logical theory? Fortu- press relationships between objects (e.g., nately, the DAML + OIL specification in- subClassOf, aPartOf). Attributes are rectan- cludes both a first-order logic semantics and gular tags attached to the node (e.g., size, a model-theoretic semantics. These seman- color, brand). Attributes of a node are in- tics enable the use of a first order predicate herited by the subclasses of a node, and calculus programming language such as eventually attributes take on values for very (PROgramming in LOGic) to encode specific instances of a concept (e.g., John’s the ontology and to query it, searching for Court_shoes are size: 11W, color: white, logical inconsistencies in the theory. Once a and brand: Reebok). The temporal nature domain ontology structure is developed and of the ontological structure cannot be shown validated, segments can be incorporated as in a diagram such as Figure 2; however, it is components of Web pages (as demonstrated understood and must be coded (e.g., date- in the previous section). time stamp) when the ontological structure is implemented so that a software agent can

size:

Shoe color: brand: subClassOf subClassOf Boot Moccasin

aPartOf subClassOf aPartOf Heel subClassOf

Dress_shoe Sole Sport_shoe

subClassOf subClassOf

subClassOf Jogging_shoe Court_shoe

Walking_shoe

Figure 2.

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A software agent can understand these OWL becomes an established means for do- segments and share that understanding with ing so. Second there is the problem of ac- the human who gave the software agent a cessibility, that is, giving the undergraduate goal to achieve. Assuming the existence of sufficient background (often not found in a several well-designed domain ontologies, required course) so that the research prob- the construction of a higher-level ontology is lem is understood and the research goal is a matter of defining the “gates” between the clear. Again, if the focus is on developing an different domain ontologies. For example, ontology then the problem of accessibility the “wears” relationship may be the gate really becomes one of what domain the stu- through which a software agent might use dent is interested in working, a possible fu- both the Human ontology and the Shoe on- ture career field. This has not proved to be tology. a real problem; students have a plethora of domains in which they are interested, and it 4. UNDERGRADUATE RESEARCH is more a problem of deciding to work on one small domain where research progress Since the tools and techniques to be used in can be demonstrated in a reasonable the Semantic Web are an emerging technol- amount of time, say, a year or two. ogy, having an undergraduate computer course focus on how to use them is not ap- Thompson (2000), an undergraduate re- propriate at this time. However, we have searcher, worked in the domain of high found it very beneficial to use ontology de- school algebra word problems. Her devel- velopment for the Semantic Web to promote oped ontology was implemented in PROLOG undergraduate research. Unlike using re- and used by CASPOR (Computer Algebra search projects in undergraduate degree Story Problem ORiginator), a PROLOG pro- programs (Hollocks 2001), such as a cap- gram that randomly generated specific types stone course or senior project, our approach of algebra word problems (e.g., mixture) for is strictly voluntary (on the part of the fac- students to solve. CASPOR used the ontol- ulty member and the undergraduate) and ogy to represent the knowledge about the does not count for any student course work. context of the word problems. For example, Nonetheless, the value to the students in- in distance-rate-time problems, a car object volved is the same as Hollock expressed: must be associated in context with an object (1) Understanding the concept of research, such as a road. This knowledge context (2) Development of problem definition and would prevent the generation of a problem goal skills, (3) Wider and more critical per- that begins, “Two cars fly to Chicago at the spectives on literature sources, (4) Devel- same time.” Instead, the ontology insures opment of reasoning and inquiry skills, (5) that the problem begins, “Two cars take the Development of presentation and writing road to Chicago at the same time.” skills, (6) Development of self-management skills, and (7) Development of an in-depth Another undergraduate researcher, Gilds understanding of a particular domain, which (2002) worked in a more difficult domain, may support career opportunities after that of world religions. The various violent graduation. acts being perpetrated globally in the name of a religion motivated the development of Getting students interested in doing our type this ontology. The student had a deep inter- of undergraduate research is not an easy est in her own religion and wanted to under- matter. First there is the need to motivate stand how other religions, that have com- the research work. Students must be given mon origins, could be in such conflict with a reason for going beyond course work, a one another. Religions are a psychosocial well-defined and structured environment, factor. Religions form a psychological con- into something new, subject to change, and text in which some people function violently, needing structure (i.e., research). Given the for example, the Kamikaze functioned in the vision of the Semantic Web and the knowl- context of Bushido, and the Hamas suicide edge that pieces of it (e.g., XML and the cur- bombers function in the context of Islam. rent Web itself) are in place and being used Bushido and Islam are not as well related as for e-Commerce, we can encourage students say Islam and Judaism (both trace historical to develop small domain ontologies that may paths from Abraham). Religions also form a be embedded into the Semantic Web after social structure within society; there are re-

c 2003 EDSIG http://isedj.org/1/25/ December 27, 2003 ISEDJ 1 (25) Lopez 9 ligious leaders (rabbi, imam, bishop, etc.), ontology has demonstrated that the ontol- buildings (temple, mosque, church, etc.), ogy needs more work before a software and other trappings. All of these concepts agent can use it. and relationships between concepts have to be incorporated into a well-structured ontol- We conclude this section with a PROLOG im- ogy to be understood by a software agent. plementation of the Shoe ontology devel- On today’s WWW there is no dearth of Web oped in the previous section. Since one of pages about religion and by various eco- the drivers for OWL is frame-based systems, nomic measures religion is big business. It we have our undergraduate researchers take is commendable that an undergraduate a frame-based knowledge representation for would even attempt to work in such a do- the ontology. Specifically, we have them main. However, after a year and a half of use the knowledge representation expressed work, the PROLOG implementation of her in Table 2.

name( Concept ). relation( Concept, Relationship, Another_Concept ). slot( Concept, Attribute ) value( Concept, Attribute, What_it_is ).

Table 2

name(shoe). name(moccasin). name(dress_shoe). name(sport_shoe). name(boot). name(jogging_shoe). name(walking_shoe). name(court_shoe). name(heel). name(sole). relation(moccasin, subClassOf, shoe). relation(dress_shoe, subClassOf, shoe). relation(sport_shoe, subClassOf, shoe).

relation(boot, subClassOf, shoe). relation(jogging_shoe, subClassOf, sport_shoe). relation(walking_shoe, subClassOf, sport_shoe). relation(court_shoe, subClassOf, sport_shoe). relation(heel, aPartOf, shoe). relation(sole, aPartOf, shoe). slot(shoe, size). slot(shoe, color). slot(shoe, brand). What are the parts of a shoe?

?- relation(What, aPartOf, Shoe). What = heel; What = sole; no more solutions What are the attributes of a court shoe?

?- has_slot(court_shoe, What). NOTE: These attributes are inherited What = size; from the attributes of a shoe. What = color; What = brand; no more solutions

Table 3

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The PROLOG implementation of the Shoe ontology axiom that is used to implement ontology is given in Table 3. Having a com- inheritance. The students consider such a puter executable ontology allows under- PROLOG rule part of the ontology “engine” graduate researchers to verify and validate since it can be used with any ontology hav- their logical theory using simple queries. ing the knowledge representation structure Examples of such queries and the program’s given in Table 2. For completeness, the response appear at the bottom of Table 3. PROLOG implementation for the inheritance The last query in Table 3 is generated by an axiom is presented in Table 4.

has_slot( Concept, Attribute ) :- slot( Concept, Attribute ), !. has_slot( Concept, Attribute ) :- relation( Concept, subClassOf, SuperConcept), has_slot( SuperConcept, Attribute ).

Table 4

There is little doubt that undergraduates can into a Semantic Web page. The paper tran- do the work described in this section. The sitioned to a focus on the logical theory that most challenging part of the student’s re- would give an explicit, partial account of a search is getting the in-depth understanding conceptualization (i.e., an ontology). An of the domain and, with that understanding, example was presented showing how an on- a more critical perspective on the informa- tology might be developed in a specific do- tion sources used in the domain. Developing main. The paper suggested a type of under- the ontology and implementing it in a de- graduate research as a vehicle for develop- scriptive first order logic programming lan- ing domain ontologies, implementing each in guage is not difficult. Querying the ontology a first order descriptive programming lan- looking for inconsistencies can be difficult guage, and validating them via queries. and can show that the proposed ontology is Published examples of such undergraduate not ready to have a software agent use it. research were cited, and an implementation However, all of this work, whether com- of the previous example ontology given. pletely successful or not, is preparing, quite The thesis of the paper is that undergradu- naturally, for the Semantic Web. ate research in ontology development is a natural way to prepare students for working 5. CONCLUSION on the future Semantic Web.

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Antonio M. Lopez, Jr. holds the Conrad N. Hilton Endowed Chair in Computer Science at Xavier University of Louisiana. During the 2000-2001 academic year, he also held the Chair in Artificial Intelligence at the Center for Strategic Leadership of the Army War College, Carlisle, PA. He was recognized for his work there with the Department of the Army Superior Civilian Service Award, and he continued in dual status as Visiting Professor in Artificial Intelligence until July 2003. Lopez received his Ph.D. in Mathematical Sciences from Clemson University in 1976. His current research areas are: intelligent agents, knowledge-based systems, ontology development, and knowledge management. Email: [email protected] WebPages: www.xula.edu/~tlopez

c 2003 EDSIG http://isedj.org/1/25/ December 27, 2003