Semantic Markup Research Articles

Ontology-Based Annotation for Deep Web Data

A semantic annotation method for Web database query result is proposed in this paper by adopting the deep annotation procedure in semantic Web. As a global schema Web database should be followed, domain ontology is introduced to the annotation procedure for a completed and consistent annotation result. The query interface and the query result features are analyzed in detail, the strategy of query condition reconfigured is adopted, and then the semantic markups of query result are determined. By collecting Web database from different domains, the experiments indicate that the approach proposed can annotate the Web database query result properly under the support of domain ontology.

An automatic mark-up approach for structured document retrieval in engineering design

Information and knowledge retrieval has been recognized as a key issue in engineering design. A great deal of design-related information used and generated within engineering companies is formally recorded in documents. These documents become more useful if they are structured in a consistent way so that they can be retrieved and their contents accessed more effectively. Achieving useful structure in electronic documents relies on embedding some sort of mark-up or coding that is computer-understandable. Manual mark-up is time-consuming and costly. This paper proposes a knowledge engineering approach to automatic document mark-up employing XML (the eXtensible Mark-up Language) to ’tag’ explicitly the structural information. The focus here is on long and complex engineering documents. A three-level model is explored to achieve automatic semantic mark-up using a set of document decomposition schemes. The model includes a strategic level which identifies document typographical features based on such things as styles, inference or templates; a tactical level to define the rules to realize semantic mark-up according to the document features; and an operational level to perform the computational implementation of the mark-up rules. By making document structure explicit, information retrieval can be made more focused by returning not just whole documents but the document components that are most relevant or of most interest to the engineering designer, and information relevant to the designer’s need both with respect to document structure and content, not content alone. In addition, interpretation of useful structure by the human user can be hardwired into documents, which allows us to move closer to true semantic level retrieval.

The green and gold road: journal management and publishing workflow extensions for the DSpace repository platform

Articles are still the predominant format in scientific publishing, even in the web-based era. However, scientific articles often lack semantic markup. In this paper, we propose an integrated publishing and journal management workflow based on the DSpace repository software. A simple authoring and submission process, including content storage in an eXtensible Markup Language (XML)-based format and automated metadata extraction directly from the author's document, allows extending articles with structured metadata and semantic markup. Articles are no longer limited to their Portable Document Format (PDF) representation. The proposed system allows publishing content in different output formats, namely, eXtensible Hypertext Markup Language (XHTML) and PDF, with the help of eXtensible Stylesheet Language (XSL) stylesheets. This helps improve the reading experience. Furthermore, based on the articles archived in the repository, the system should make the setup and maintenance of journal issues easier. The new ...

Life Cycle for Change Management in Business Processes using Semantic Technologies

In a fast changing market environment the task of reducing the downtime for change management of business processes has high importance. Ensuring that IT reflects the updated business requirement is an important task related to change management in software development. We present a methodology and system for changing SOA-based business process implementation. We distinguish two layers: At the design layer processes are modeled in the ontology-based semantic markup language for web services OWL-S. For execution the processes are translated into BPEL. At the core of our system are a central change management component and a set of tools which perform various tasks in the overall lifecycle of change management. Finally, we demonstrate our approach with an example e-government.

Language technologies for semantic markup in mathematics

AbstractThe Web Advanced Learning Technologies project showed how, by applying state of the art language technologies to semantic markup of mathematics, it is possible to automatically produce renderings of mathematical content in a variety of languages. The intended application area of this work is that of computer assisted assessment and testing in mathematics where standardized entry examinations for perspective students could be used independently of country and language. A similar multilingual approach can be developed for any situation in which it is possible to identify a specific mathematical jargon. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

GraSSML: accessible smart schematic diagrams for all

Graphical representation is a powerful way of conveying information. Its use has made life much easier for most sighted users, but people with disabilities or users who work in environments where visual representations are inappropriate, cannot access information contained in graphics, unless alternative descriptions are included. This paper describes an approach called Graphical Structure Semantic Markup Languages (GraSSML), which aims at defining high-level diagram description languages capturing the structure and the semantics of a diagram, and enabling the generation (by transformation) of accessible and “smart” presentations in different modalities such as speech, text, graphics, etc. The structure and the semantics of a diagram are made available at the creation stage. This offers new possibilities for allowing Web Graphics to become “smart”.

Building the Mobile Web: rediscovering accessibility?

After the launch of the Mobile Web Initiative at the WorldWide Web Conference 2005, awareness is emerging that,today, mobile Web access suffers from interoperability andusability problems that make the Web difficult to use. Withthe move to small screen size, low bandwidth, and differentoperating modalities, technology is in effect simulating thesensory and cognitive impairments experienced by dis-abled users within the wider population of mobile deviceusers. The Third International Cross-Disciplinary Work-shop on Web Accessibility (W4A 2006) was targeted tobring together different communities working on similarproblems to share ideas, discuss overlaps, and make thefledging mobile Web community aware of accessibilitywork that may have been overlooked. The main questionasked was:‘‘Is engineering, designing, and building for theMobile Web just a rehash of the same old Webaccessibility problems?’’This lead to addressing issues such as:• Are the same solutions required for the Mobile Weband for accessibility and can the two communities worktogether to solve these problems?• What can the Mobile Web learn from the AccessibleWeb and what resources created to support theAccessible Web can be used by designers in theirsupport of the Mobile Web?• To cross-pollinate do we need to rethink the currentview of accessibility?Therefore, the workshop brought together a cross sectionof designers, engineers, and practitioners working on boththe Accessible and Mobile Webs; to report on develop-ments, discuss the issues, and suggest cross-pollinatedsolutions.The W4A 2006 was held on Monday the 22nd andTuesday the 23rd May 2006 as part of the FifteenthInternational World Wide Web Conference (WWW2006),running over 2 days, with 73 attendees and 20 papersaccepted for presentation. This special issue is an addi-tional outcome of the W4A 2006 Workshop, and consistsof the revised and extended version of seven papers of thepapers presented at the Workshop, selected on the basis ofthe review results. The articles presented here focus onmajor issues of the Accessible and Mobile Webs thatadvance the implementation of universal access.The first article in this special issue is entitled CapabilitySurvey of User Agents with the UAAG 1.0 Test Suite and ItsImpact on Web Accessibility by Watanabe, T. and Ume-gaki, M. This article discusses capabilities of a number ofJapanese user agents with respect to the User AgentAccessibility Guidelines (UAAG 1.0). This article high-lights that in order to promote Web accessibilityinternationally, the focus should not only be on contentaccessibility but also on user agent accessibility.It is a common belief that ‘‘A picture is worth a thou-sand words’’. That might be true for someone who issighted, but visually disabled users or users who work inenvironments where visual representations are inappropri-ate cannot access information contained in graphics, unlessalternative descriptions are included. The second article,which is entitled GraSSML: Accessible Smart SchematicDiagrams for All, by Fredj, Z.B. and Duce, D.A., investi-gates accessibility of diagrams. This article presents anapproach called Graphical Structure Semantic Markup

Building a Semantic-Rich Service-Oriented Manufacturing Environment

Service orientation has emerged as a new promising paradigm for enterprise integration in the manufacturing sector. In this article, we focus on the approach and technologies for constructing a service oriented manufacturing environment. The service orientation is achieved via virtualization in which everything, including machines, equipments, devices, various data sources, applications, and processes are virtualized as standard-based Web services. The virtualization approach is based on the emerging Web Services Resource Framework (WS-RF). A case study of virtualizing an AGV system using WS-RF is described. The use of Semantic Web Services technologies to enhance manufacturing Web services for a semantic-rich environment is discussed, focusing on OWL-S for semantic markup of manufacturing Web services and OWL for the development of ontologies in the manufacturing domain. An enterprise integration architecture enabled by Semantic Web service composition is also discussed.

AquaLog: An ontology-driven question answering system for organizational semantic intranets

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

Aqualog: An Ontology-Driven Question Answering System for Organizational Semantic Intranets

The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system whichtakes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

The reusability of induced knowledge for the automatic semantic markup of taxonomic descriptions

AbstractTo automatically convert legacy data of taxonomic descriptions into extensible markup language (XML) format, the authors designed a machine‐learning‐based approach. In this project three corpora of taxonomic descriptions were selected to prove the hypothesis that domain knowledge and conventions automatically induced from some semistructured corpora (i.e., base corpora) are useful to improve the markup performance of other less‐structured, quite different corpora (i.e., evaluation corpora). The “structuredness” of the three corpora was carefully measured. Basing on the structuredness measures, two of the corpora were used as the base corpora and one as the evaluation corpus. Three series of experiments were carried out with the MARTT (markuper of taxonomic treatments) system the authors developed to evaluate the effectiveness of different methods of using the n‐gram semantic class association rules, the element relative position probabilities, and a combination of the two types of knowledge mined from the automatically marked‐up base corpora. The experimental results showed that the induced knowledge from the base corpora was more reliable than that learned from the training examples alone, and that the n‐gram semantic class association rules were effective in improving the markup performance, especially on the elements with sparse training examples. The authors also identify a number of challenges for any automatic markup system using taxonomic descriptions.

Hybrid specification, storage, retrieval and runtime application of clinical guidelines

Clinical guidelines are a major tool in improving the quality of medical care. However, most guidelines are in free text, are not machine-comprehensible and are not easily accessible to clinicians at the point of care. We have designed and implemented a web-based, modular, distributed architecture, the Digital Electronic Guideline Library (DeGeL), which facilitates gradual conversion of clinical guidelines from text to a formal representation in the chosen target guideline ontology. The architecture supports guideline classification, semantic markup, context-sensitive search, browsing, run-time application and retrospective quality assessment. The DeGeL hybrid meta-ontology includes elements common to all guideline ontologies, such as semantic classification and domain knowledge; it also includes four content-representation formats: free text, semi-structured text, semi-formal representation and a formal representation. These formats support increasingly sophisticated computational tasks. Guidelines can thus be in a hybrid representation in which guidelines, and even parts of the same guideline, might exist at different formalisation levels. We have also developed and rigorously evaluated a methodology and an associated web-based tool, Uruz, for gradually structuring and semi-formalising free-text clinical guidelines. Finally, we have designed, implemented and evaluated a new approach, the hybrid runtime application model, for supporting runtime application of clinical guidelines that are not necessarily in a machine-comprehensible format; in particular, when the guideline is in a semi-formal representation and the patient's data are either in an electronic medical record or in a paper format. The tool implementing this new approach, the Spock module, is customised at this point to the Asbru guideline specification language and exploits the hybrid structure of guidelines in DeGeL. The Spock module also exploits our temporal-abstraction mediator to the patient record, IDAN, and our interactive intelligent-visualisation tool, KNAVE-II.

Sorting things in: Feminist knowledge representation and changing modes of scholarly production

Synopsis A feminist web-based research initiative must make electronic publication an integral part of the research design. We are at a critical juncture in the production of scholarly tools in electronic form, as we move from the production of archives that seek to reproduce existing collections of primary material towards more mediated contextual materials, such as the newly published Orlando: Writing in the British Isles from the beginnings to the present or the proposal for fusing primary and secondary materials in the projected Feminisms and Print Culture, 1830–1930 project. This discussion takes the Orlando Project as an example of what can be gained by the customized application of semantic markup language to originally digital materials in order to address some crucial issues raised by large-scale humanities computing work. Feminist scholars must participate in the highly politicized processes of knowledge organization to have a shaping impact on humanities research and dissemination, and this shift in our mode of production has major impacts on what scholarly work involves, how it is resourced, how it is conducted and by whom, and how it is credited.

Semantic Annotation for Knowledge Management: Requirements and a Survey of the State of the Art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic markup. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

A method for automatic construction of learning contents in semantic web by a text mining approach

E-learning has gradually been accepted as an alternative for traditional lecture-based learning. One key factor for the success of e-learning is the possibility of understanding the semantics of learning contents autonomously by machines. The semantic web could naturally fit in according to its ability on information interchange and sharing between machines. Such ability is made possible when the semantic web pages are properly annotated. To transform the existing semantics-lacking learning contents to semantics-enriched ones, we propose a machine learning approach to automatically generate semantic markups for traditional learning contents, which are usually presented in web pages. The proposed method applies the self-organising map algorithm to cluster training web pages and conducts a text mining process to discover the anchor texts to be tagged and their semantic descriptions. Preliminary experiments show that our method may successfully generate semantic markups for the web pages that could be used for e-learning in the semantic web environment.

Semantic annotation for knowledge management: Requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Ontology management for large-scale enterprise systems

Semantic markup languages such as RDF (Resource Description Framework) [ Resource Description Framework (RDF), http://www.w3.org/RDF/] and OWL (Web Ontology Language) [ Web Ontology Language (OWL), http://www.w3.org/2004/OWL/] are increasingly being used to externalize meta-data or ontologies about data, software and services in a declarative form. Such externalized descriptions in ontological format are used for purposes ranging from search and retrieval to information integration and to service composition [Resource Description Framework (RDF): Projects and Applications, http://w3c.org/RDF/#projects, Web Ontology Language (OWL): Tools, Projects and Applications, http://w3c.org/2004/OWL/#projects]. Ontologies could significantly reduce the costs of deploying, integrating and maintaining enterprise systems. The barrier to more wide-spread use of ontologies for such applications is the lack of support in the currently available middleware stacks used in enterprise computing. This paper presents our work on developing an enterprise-scale ontology management system that will provide APIs and query languages, and scalability and performance that enterprise applications demand. We describe the design and implementation of the management system that programmatically supports the ontology needs of enterprise applications in a similar way a database management system supports the data needs of applications. In addition, we present a novel approach to representing ontologies in relational database tables to address the scalability and performance issues. The state of the art ontology management systems are either memory-based or use ad hoc solutions for persisting data, and so provide limited scalability.

Metadata, Metaphor, and Metonymy

SUMMARY Principles drawn not just from library and information science, but also from structuralist literary theory, provide the beginnings of a flexible theoretical framework that will incorporate not just current metadata activities but those in the future that cannot yet be envisioned. A distinction common in literary studies is used here to distinguish between metadata applications for discovery and metadata applications for use. Metadata systems for resource discovery, such as the Dublin Core, are continuous with the traditions of bibliographic description, and rely on a principle of metonymy: the use of a surrogate or adjunct object to represent another. Metadata systems for resource use, such as semantic markup languages, are continuous with the traditions of database design, and rely on a principle of metaphor: the use of a paradigmatic image or design that conditions how the user will respond to and interact with the data.

Ontology Learning from Text: A Survey of Methods

After the vision of the Semantic Web was broadcasted at the turn of the millennium, ontology became a synonym for the solution to many problems concerning the fact that computers do not understand human language: if there were an ontology and every document were marked up with it and we had agents that would understand the markup, then computers would finally be able to process our queries in a really sophisticated way. Some years later, the success of Google shows us that the vision has not come true, being hampered by the incredible amount of extra work required for the intellectual encoding of semantic mark-up – as compared to simply uploading an HTML page. To alleviate this acquisition bottleneck, the field of ontology learning has since emerged as an important sub-field of ontology engineering. It is widely accepted that ontologies can facilitate text understanding and automatic processing of textual resources. Moving from words to concepts not only mitigates data sparseness issues, but also promises appealing solutions to polysemy and homonymy by finding non-ambiguous concepts that may map to various realizations in – possibly ambiguous – words. Numerous applications using lexical-semantic databases like WordNet (Miller, 1990) and its non-English counterparts, e.g. EuroWordNet (Vossen, 1997) or CoreNet (Choi and Bae, 2004) demonstrate the utility of semantic resources for natural language processing. Learning semantic resources from text instead of manually creating them might be dangerous in terms of correctness, but has undeniable advantages: Creating resources for text processing from the texts to be processed will fit the semantic component neatly and directly to them, which will never be possible with general-purpose resources. Further, the cost per entry is greatly reduced, giving rise to much larger resources than an advocate of a manual approach could ever afford. On the other hand, none of the methods used today are good enough for creating semantic resources of any kind in a completely unsupervised fashion, albeit automatic methods can facilitate manual construction to a large extent. The term ontology is understood in a variety of ways and has been used in philosophy for many centuries. In contrast, the notion of ontology in the field of computer science is younger – but almost used as inconsistently, when it comes to the details of the definition. The intention of this essay is to give an overview of different methods that learn ontologies or ontology-like structures from unstructured text. Ontology learning from other sources, issues in description languages, ontology editors, ontology merging and ontology evolving transcend the scope of this article. Surveys on ontology learning from text and other sources can be found in Ding and Foo (2002) and Gomez-Perez

ON KNOWLEDGE GRID AND GRID INTELLIGENCE: A SURVEY

The next generation Web Intelligence (WI) aims at enabling users to go beyond the existing online information search and knowledge queries functionalities and to gain, from the Web, practical wisdom for problem solving. To support such a Wisdom Web, we envision that a grid‐like computing infrastructure with intelligent service agencies is needed, where these agencies can interact, self‐organize, learn, and evolve their course of actions, identities, and interrelationships for new knowledge creation, as well as scientific and social evolution. In this paper, we first provide an overview of recent development in WI and Semantic/Knowledge Grid. Then, the fundamental capabilities of the Wisdom Web as well as the conceptual architecture of an intelligent Grid for supporting it are described. Technical challenges for realizing Grid Intelligence are highlighted and the recent advancements in related research areas are reviewed.