MnM: A Tool for Automatic Support on Semantic Markup
María Vargas-Vera, Enrico Motta, John Domingue, Mattia Lanzoni, Arthur Stutt, Fabio Ciravegna · 2004
An important precondition for realizing the goal of a semantic web is the ability to annotate web resources with semantic information. In order to carry out this task, users need appropriate representation languages, ontologies, and support tools. In this paper we present MnM, an annotation tool which provides both automated and semi-automated support for annotating web pages with semantic contents. MnM integrates a web browser with an ontology editor and provides open APIs to link to ontology servers and for integrating information extraction tools. INTRODUCTION An important pre-condition for realizing the goal of the semantic web is the ability to annotate web resources with semantic information. In order to carry out this task, users need appropriate knowledge representation languages, ontologies, and support tools. The knowledge representation language provides the semantic interlingua for expressing knowledge precisely. RDF (Hayes (2002), Lassila and Swick (1999)) and RDFS (Brickley and Guha (2000)) provide the basic framework for expressing metadata on the web, while current developments in web-based knowledge representation, such as DAML+OIL (reference description of the DAML+OIL can be found at http://www.daml.org/2001/03/reference.html) and OWL the language proposed by the WebOnt group (http://www.w3.org), are building on the RDF base framework to provide more sophisticated knowledge representation support. Ontologies (Gruber (1993)) provide the mechanism to support interoperability at a conceptual level. In a nutshell, the idea of interoperating agents able to exchange information and carrying out complex problem solving on the web is based on the assumption that these agents will share common, explicitly defined, generic conceptualizations. These are typically models of a particular area, such as product catalogues, or taxonomies of medical conditions, although ontologies can also be used to support the specification of reasoning services (McIIraith, Son and Zeng(2001), Motta (1999), Fensel and Motta (2001)), thus allowing not only ‘static’ interoperability through shared domain conceptualizations, but also ‘dynamic’ interoperability through the explicit publication of competence specifications, which can be reasoned about to determine whether a particular web service is appropriate for a particular task. Ontologies and representation languages provide the basic semantic tools to construct the semantic web. Obviously a lot more is needed; in particular, tool support is needed to facilitate the development of semantic resources, given a particular ontology and representation language. This problem is not a new one, knowledge engineers early on realized that one of the main obstacles to the development of intelligent, knowledge-based systems was the so-called knowledge acquisition bottleneck (Feigenbaum (1977)). In a nutshell, the problem is how to acquire and represent knowledge, so that this knowledge can be effectively used by a reasoning system. Although the problem is not a new one, the context provided by the semantic web introduces new aspects to the problem, with respect to the nature of the knowledge and the type of users. Nature of the knowledge. Traditional knowledge acquisition was concerned with knowledge for problem solving. Semantic markup will primarily focus on ontology population, a far easier knowledge acquisition task. Type of users. Knowledge-based systems are normally written by skilled knowledge engineers. On the web, it is likely that semantic marking up will become a common activity, carried out by content providers who are not necessarily skilled knowledge engineers. This means that more emphasis will have to be put on facilitating semantic markup by ‘ordinary’ web users (people who are neither experts in language technologies nor 'power knowledge engineers'). In particular, automated knowledge extraction technologies are likely to play an ever increasing important role, as a crucial technology to tackle the semantic web version of the knowledge acquisition bottleneck. In this paper we present MnM, an annotation tool which provides both automated and semi-automated support for marking up web pages with semantic contents. MnM integrates a web browser with an ontology editor and provides open APIs to link to ontology servers and for integrating information extraction tools. MnM can be seen as an early example of the next generation of ontology editors, being web-based, oriented to semantic markup and providing mechanisms for large-scale automatic markup of web pages. The rest of the paper is organized as follows: in the next section we will show the process model underlying the design of the tool. Section 3 will show an example of the tool in use. Section 4 will present related work. Finally sections 5 and 6 discuss evaluation and re-state the main tenets and results from our research.