The Semantic Web: A Vision or a Dream?

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1 The Semantic Web: A Vision or a Dream? Ben Weber Department of Computer Science California Polytechnic State University May 15, 2005 Abstract The Semantic Web strives to be a machine readable version of the World Wide Web in which web sites have meaningful content. The Semantic Web uses improved information retrieval, metadata, annotation, and ontologies to enhance knowledge management. ew web services will be possible, because data will be shared at a semantic level rather than a syntactical level. The Semantic Web will use XML, RDF, and ontology languages to share knowledge on the web. A formal definition for the Semantic Web has not been defined and there are different perspectives on how to build it. This paper analyzes the technologies utilized by the W3C view of the Semantic Web and discusses the implications of such a system.

2 1 Introduction The Semantic Web is an addition to the World Wide Web, allowing computers to perform much of the work currently done by humans. The Semantic Web will allow for enhanced knowledge management through improved information retrieval, metadata, annotation, and intelligent agents. The Semantic Web will use technologies such as XML, RDF, and ontologies to provide meaningful content to computers. The Semantic Web has no formal definition and there are different opinions about how it will look. The Semantic Web enables a new era of web services, because data is shared at the semantic level rather than the syntactical level. Since computers will be able to understand the content of web sties, users of the Semantic Web will be offered more web services than provided by the current World Wide Web. One of the main limitations of the current web is the retrieval of information. Most knowledge on the web is retrieved through the use of a search engine, requiring the user to parse through the results. This methods works well for many of the possible uses of the web, but there are situations when it fails. Consider a student trying to find the alias for another student named Mark, enrolled in the same operating systems class. The student could attempt to retrieve more information about the student using a search engine to search for everybody named Mark in an operating systems course. This would return mostly irrelevant results, because the computer does not realize that Mark is a student. Also, the search engine does not realize which operating systems course is being referenced. Such a query on the current web would probably fail due to the amount of unrelated information retrieved. The Semantic Web will overcome this problem by allowing users to perform searches by concepts and using technologies such as RDF to perform the search. The Semantic Web will utilize several different technologies, which can be developed in a layered approach. Each layer is dependent on the layer directly below it, and each layer only communicates with the layer above and below. One of the possible structures for the Semantic Web has been proposed by W3C. The first layer consists of uniform resource identifiers and Unicode. A uniform resource identifier (URI) is used to identify a resource on the Semantic Web, while Unicode enforces a standard character set. The next layer is extensible markup language (XML), which allows for a common syntax. Built on top of XML is resource description framework (RDF), which is used to describe resources on the Semantic Web. The next layer is the ontology layer, providing a common vocabulary for resources. On top of ontologies is the logic and proof layer, which allows computers to verify information retrieved on the Semantic Web. The top layer is trust, since computers will need to determine the truth of information. Several of these layers are already in place, but it is still too early to determine if the Semantic Web will become a reality. However, not all layers need to be in place before useful web services are available. The Semantic Web promises automatic retrieval of information and personal agents performing tasks on behalf of users, but it might not be feasible to develop such a large scale project. One problem facing the Semantic Web is the several differing views of how it should look. There are other problems preventing the development of the Semantic Web, such as limitations of RDF and dealing with the abuse of metadata. However, the current web has already overcome some of the problems faced by this new

3 technology. The Semantic Web should not be viewed as a goal, it should be visualized as a direction for future functionality of the current web. 2 Overview of the Semantic Web The Semantic Web will require the union of several different themes in order to become a reality. The first technology that needs to be integrated into the Semantic Web is the retrieval of information. Currently search techniques are useful, but are usually limited to keywords. Allowing users to search by concepts and categories as well would provide more effective results. However, enabling such queries requires heavy usage of metadata. The Semantic Web will require standardizations of metadata, which can be provided by RDF and ontologies. Retrieving information on the Semantic Web will also be more efficient if knowledge is represented as a large database. Currently information on the web is distributed in heterogeneous databases, resulting in scattered data. A solution to this problem is representing databases with ontologies and using RDF to merge the ontologies. These technologies allow for the machine retrieval of information, offering new types of web services. Combining these themes enables intelligent software agents to process the information on the web. 2.1 What is the Semantic Web? There are three main perspectives of how the Semantic Web should look, two of these views are closely related to the current World Wide Web. The current web provides particular knowledge, because information is distributed across the web and there is not universal agreement. Also, most of the parsing of information retrieved from search engines is done by humans. Until search engines were able to provide retrieval of information, there were limited ways for retrieving information on the web. The current web provides web services, which are also mainly used by humans. Universal agreement and machine retrieval of information are the main differences between the current web and the Semantic Web. The first view of the Semantic Web is the universal library perspective [9]. This perspective embraces the idea that the Web should have a retrieval scheme similar to a library, in which there is a standardized metadata structure. This perspective developed as a reaction to the disorder of the Web. Searches engines such as Google and AltaVista are currently moving in this direction, as they provide retrieval methods and catalog data on the web. The universal library perspective would be equivalent to using a library catalog to search for any book anywhere in the world by any search criteria. This functionality will be feasible through the use of metadata, providing a standard format for describing knowledge. However, this perspective is no longer viewed as the current direction of the Semantic Web, since retrieved information is mainly parsed by humans. The second perspective of the Semantic Web is the knowledge navigator view. This view is similar to the universal library perspective, except that information on the web is machine retrievable [9]. The main difference between the two is that web pages will have meaningful content to computers, provided by technologies such as RDF and ontologies. This view has the most potential, since information is retrieved in a universal method and computers are able to reason on the data. However, this approach is also the most difficult to construct, because the distributed nature of the web makes universal

4 agreement challenging. The knowledge navigator perspective allows autonomous agents to reason on data and draw conclusions from the information, enabling this view to have the most functionality. The final view of the Semantic Web is the knowledge base perspective. This perspective provides machine retrieval of information by forcing agents to perform anticipated tasks [9]. This view is similar to the current web, except web services are used by agents instead of humans. Unlike the knowledge navigator approach, web sites share data syntactically rather than semantically. Therefore the information retrieved from web sites does not necessarily have meaning to an agent. However, agents can still reason on the data if components are developed with shared anticipation of knowledge. This approach allows for a large scale Semantic Web, since it does not require universal agreement between agents. This perspective appears to be the most prominent view of the Semantic Web, as current web services are becoming increasingly autonomous. 2.2 The W3C View of the Semantic Web The Semantic Web will require the merging of several technologies, one possible view is provided by the W3C. The W3C views the Semantic Web as a layered approach, in which components are only dependent on the layer directly below it. Also, layers only communicate with the layers directly below and above. This approach allows different layers to be developed with limited knowledge of the other layers. By providing a layered approach, it is possible to switch implementations of a certain layer without affecting the other layers. The lowest layer consists of Unicode and uniform resource identifiers. Unicode is used to provide a standard character set. A URI is used to identify a resource of the Semantic Web, similar to a URL on the current web. The remaining layers are built upon this framework. The extensible markup language (XML) layer is built upon Unicode and URIs, providing a common syntax for resources on the Semantic Web. XML allows for the uniform exchange of data [10], since all syntax must have a standard format. The current web uses a common syntax to describe web pages, known as HTML. Unlike HTML, XML tags do not have a fixed vocabulary. Therefore the tags in an XML document have no meaning to a computer. However, this allows a layer built on top of XML to define a vocabulary for the tags. The grammar for an XML language is defined by a schema, which is used to validate XML documents. The next layer in the W3C view is the resource description framework (RDF) layer. RDF is a standard format for describing and exchanging resources [10]. One of the uses of RDF is the description of metadata. The purpose of RDF on the Semantic Web is to allow documents to be self-describing. RDF statements are triples, consisting of a subject, predicate, and object. RDF can be used to state a specific fact, such as Mark is a student. In this case Mark is the subject, is a is the predicate, and student is the object. Any part of the triple can be described with a string literal or a URI referencing another RDF statement. One way to store RDF statements is using XML, but there is currently no standard format. RDF can be used to represent information in a relational database, but is currently much slower than traditional databases. RDF could be used for improved searching, consider the earlier example with Mark. RDF could be used to describe that Mark is a student and that Mark is in an operating systems class. This information could be used to greatly limit the search

5 results, but is still problematic if there are two students named Mark in the same class. The flexibility of RDF makes it suitable as a base for ontologies, which are described using RDF schema. The Semantic Web will allow for machine retrieval of information by acting as one large database [10], this functionality is provided by the ontology layer. An ontology is used to define a vocabulary, which might be used to give meaning to XML tags. The Semantic Web will use ontologies to manage databases with different structures. Since ontologies are based on RDF, it is possible to merge several ontologies into one. Merging ontologies will allow the Semantic Web to view several heterogeneous databases as one large, uniform database. Further functionality is added through the use of web ontology language (OWL), which allows constraints and rules to be applied to certain parts of an ontology. The next layer in the Semantic Web is the proof and logic layer. Agents that automatically retrieve information must determine the validity of knowledge [6]. This layer is essential, since information retrieved from distributed sources may be incomplete or inconsistent. Agents will require verification methods, such as checking if a document is internally inconsistent. Currently there are no standards for the logic and proof layer. This layer may also consider the trustworthiness of a certain source, which is defined by the trust layer. The top layer of the W3C view of the Semantic Web is the trust layer. Software agents must determine who to trust and how much to trust a given source. The amount to trust a source can partially be determined by the logic and proof layer, but the Semantic Web will require a higher level of granularity. One approach to determine trust is using a web of trust [8], but this method also lacks the necessary granularity. Assigning trust on the Semantic Web is a complex task, because verifying the identity of an agent is difficult. When transactions take place between humans, photo identification can be used to assure identity. This process requires an authority to issue the identification, similar authorities will be necessary for the Semantic Web. A mechanism analogous to photo identification should be used to verify identity on the Semantic Web. 3 Is the Semantic Web Possible? The Semantic Web will integrate several themes to turn the World Wide Web into a machine readable web allowing intelligent software agents to autonomously perform tasks, but such a vision may be unattainable. 3.1 Semantic Web Challenges The Semantic Web must overcome several challenges to become a reality. However, many of these same problems have already been faced by the current web. Like the current web, the Semantic Web will need to be scalable [8]. Google currently indexes billions of web sites and the Semantic Web may be of similar size. Much of the success of the current web is due to its simple protocol [10]. Current knowledge management tools have been geared towards small intranets and do not scale to such a large network. Autonomous agents might not be able to retrieve accurate information, because there is so much information distributed across the web. In order to make the Semantic Web feasible, improved indexing and searching methods must be developed.

6 Another challenge facing the Semantic Web is the dynamic nature of the web, as web sites are constantly changing. News web sites such as Slashdot change every day and other sites such as EBay may change every minute. The dynamic nature of web sites causes the extrapolation of data from the Semantic Web to be more difficult, since information may be constantly changing. Intelligent software agents using the Semantic Web must be able to deal with these changes, but it is difficult to detect changes on such a large scale. In addition to web sites changing, it is possible that certain web sites might not exist. Like the World Wide Web, the Semantic Web will allow broken links [8]. Agents will need to deal with changing information and nonexistent links. Due to the distributed nature of the Semantic Web, agents will need to integrate multiple knowledge sources. However, information from different sources may be inconsistent or contradictory. Agents will be faced with different vocabularies and conceptualizations of the same domain [8]. One possible approach to this problem is the use of ontologies to merge vocabularies, but problems arise from different views of the same domain. One current effort to build a common ontology is WordNet, which is a lexical database for the English language. Information from different web sites may contain varying quality of knowledge and agents will need to distinguish the quality of web sites. Currently there are a limited number of techniques for dealing with varying qualities of knowledge, such as local containment of inconsistencies. Since many of the above challenges result in untrustworthy knowledge, agents will be limited to incomplete reasoning. Therefore, agents using the Semantic Web must realize that not all retrieved information is valid. 3.2 Required Technologies The Semantic Web will require the use of metadata to describe resources, but much of the metadata for the World Wide Web is ignored. The main reason that metadata is discarded is due to the abuse of keywords, such as adding keywords in an attempt to increase the chances of being retrieved by a search engine. There are other reasons not to trust metadata, since people are fallible [3]. If metadata fields are left blank or are inaccurate, a search will retrieve invalid results. Another problem on the World Wide Web is the lack of standardization of metadata. A possible method to define the structure of metadata is through an ontology. One effort to standardize metadata is Dublin Core. Searches on the Semantic Web will rely on more advanced searches, as well as valid metadata. Currently search engines use keywords to retrieve information. However, this approach requires users to select the correct keywords for valid results. Many problems arise through the use of keywords, since the context of the words is lost. Words can have multiple meanings and searches have no way of knowing which meaning the user intended. Vivisimo attempts to group results into concepts, but the context of the words is still lost. Semantic Web searches should go beyond keywords, allowing users to search by concepts and categories. One of the promises of the Semantic Web is the annotation of web sites. The Semantic Web will allow web pages to be annotated much like the margins of a book [10]. A user viewing a web site may wish to add a link to relevant information or may wish to express a counter argument. Certain web sites such as Amazon allow for user feedback, but the Semantic Web will allow for a more general approach to annotation.

7 However, annotation quickly runs into many of the same problems faced by metadata, mainly abuse and standardizations. The large number of document formats on the World Wide Web makes it difficult to define a standard format for annotation. Also, annotation allows users to abuse web sites. Two browsers that attempt to solve these problems are Multivalent and Annotea. A current roadblock to the development of the Semantic Web is the limitations of RDF. The purpose of RDF on the Semantic Web is to allow documents to be selfdescribing, but it doesn t necessary have more implicit meaning that XML. The semantic distinctions possible with RDF can be made using XML [3]. Another shortfall of RDF is the lack of schema checking, similar to the verification offered by XML schema. RDF can not be validated in the same way as XML, since a schema tool would need to analyze statements at the semantic level rather than the syntactical level. RDF can also lead to reference chains, since RDF statements can point to other statements. It may be necessary to retrieve several RDF statements in order to analyze a single statement. RDF can be used to represent a database, but currently tools are too slow to use for the scale of the Semantic Web. 4 Analysis Currently the most tangible version of the Semantic Web is the knowledge base perspective, which allows computers to perform much of the work done by humans. Due to the distributed nature of the web, the universal library view seems unpractical. It is impossible to have the perfect metadata necessary for this perspective. Even if a metadata standard is agreed upon, such as Dublin Core, it is still possible for people to make mistakes or abuse the system. Forcing too many standards prevents the Semantic Web from evolving, because components would become tightly coupled. The knowledge navigator perspective is also unlikely since it is built upon the universal library. Also, it may not be possible for machines to discover meaning from documents on the web. The knowledge base view seems most likely, since it is a gradual change from the current web. Unlike the other perspectives, the knowledge navigator approach requires an agent to have anticipated knowledge [9]. This limits the ability of agents, but this view is partially attainable with current technology. 4.1 Limitations of RDF The goal of the Semantic Web is to give meaning to documents. One approach to allow for semantic understanding of knowledge is by describing documents with RDF. However, a machine can infer nothing from an RDF statement. RDF statements are used to reference concepts, but the machine has no notion of these concepts. It is possible for a concept to be described by another RDF statement, but this adds more facts rather than actually define the concept. Computers can infer information from these facts, but these conclusions may have little semantic truth. RDF is only binary data to a computer, because a computer has no notion of the world. However, the discussion of whether a computer can ever understand a concept is not the domain of knowledge management, it is the domain of philosophy. Agents may never actually understand the meaning of data, but the Semantic Web is still a possibility.

8 Much of the functionality of the Semantic Web is provided through RDF, but RDF may not be expressive enough. RDF is based on triples, which allow specific things to be said about a specific object. However, RDF lacks the ability to negate statements. This is a small problem, but entire ontologies are built on top of this foundation. This problem can be overcome by using languages such as OWL, which have the ability to apply rules and constraints to an ontology. This approach does not necessarily limit the expressiveness of RDF, but it does have implications on speed. The W3C view of the Semantic Web allows for layers to be replaced by alternatives, one such technology is Notation Improving Information Retrieval The feasibility of the Semantic Web depends on the revival of metadata. Currently search engines such as Google ignore metadata in web pages, due to abuse. Search engines try to extract metadata from the document itself. Still much of the content of a document is lost using this approach, since it is reduced to keywords. A user may search for parts of the document that are not described by the selected keywords, therefore a relevant result might not be retrieved. This problem can be solved by agreeing on a metadata standard and using metadata for the retrieval of information. However, this leads back to the problem with abuse of metadata. The Semantic Web should work towards reducing abuse problems rather than trying to generate metadata. A human with domain expertise is more likely to produce relevant metadata for a document than a set of domain independent rules. The Semantic Web relies on the ability of computers to retrieve information. It is difficult for an agent to extract useful information from the current web, because web sites are formatted for humans rather than computers. This problem can be solved by using RDF to describe web sites, since RDF statements can be parsed by a computer. However, an agent must determine which web site to view. Different sources on the web may have contradictory information, therefore an agent must determine which web site has the highest quality of knowledge. Agents require the ability to validate knowledge, otherwise they may come to erroneous conclusions. It may be necessary to limit the usage of agents on the Semantic Web to a particular domain. 4.3 Will Semantic Web technologies be adopted? To extend the functionality of the current web, the Semantic Web will require addition access to information. For example, an agent that handles scheduling will need access to a user s personal schedule. Other web services will require additional shared personal information. This raises several security concerns, as agents will have access to sensitive personal information. The Semantic Web might lead to a new age of hackers, which trick personal agents into sharing private information. Most security issues will be addressed in the trust layer, but distributed trust on the Semantic Web might not be possible. Agents interact in a digital environment, which makes it extremely difficult to verify identity. The Semantic Web might be too big of a security risk to become a reality. Even if the technology to support the Semantic Web is tangible, it is possible that people will not accept it. The Semantic Web gives personal agents more control,

9 abstracting users from the computer. Machines may be able to perform tasks faster and with more accuracy, but computers can still make mistakes. For example, pilots still fly airplanes even though autopilot technology exists. The Semantic Web requires people to share sensitive information and people might not trust personal agents. Also, the Semantic Web would require businesses to share more information. However, information is valuable and companies are often unwilling to distribute it freely. Therefore, business might not embrace the idea of the Semantic Web. The technology provided by the Semantic Web might go too far. For example, consider the Context Free automatic paper generator. Agents might replace too much of the work currently done by humans. Such advances may lead to a lack of original thought, since machines can automatically generate results. The Semantic Web might lead to a loss of research principles, because agents would be performing information retrieval rather than humans. Also, the power of the Semantic Web could destroy the need for libraries, since all knowledge would be available on the web. The Semantic Web should be used to enhance knowledge management, not replace it. 5 Conclusion The Semantic Web will allow computers to perform much of the work currently done by humans on the World Wide Web. The Semantic Web enables agents to perform useful tasks autonomously on the web, because web sites will have meaningful content to computers. The Semantic Web will use XML, RDF, and ontologies to provide web services. However, the Semantic Web is still far from reality, as there are many problems with the distributed nature of the web. Major changes from the current web include more advanced and accurate retrieval of information, the use of metadata, annotation, and intelligent software agents. The Semantic Web has no formal definition and there are different opinions about how it will look. It can be thought of as an evolving version of the current web, in which machines and humans interact with web services. The vision of the Semantic Web may not be attainable, but the current web will continue to progress in the direction of such a technology.

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