Developing and Applying a Company, Product and Business Event Ontology for Text Mining

The company, product and event (CoProE) ontology is an ontology that is being developed for use as a component of DAVID, a text mining system for business intelligence. The main design principle of the ontology, as well as the whole text miming system, is based on heavy reuse of existing freely available resources. This paper introduces the ontology and the domain knowledge component that utilizes it. In addition to describing the ontology and its design principles, we consider the ways in which the design process of the domain knowledge model and the CoProE ontology facilitated the design of our whole business intelligence text mining system.

Towards a Comprehensive Call Ontology for Research 2.0

A Call for Papers (CfP) is a small, but well-structured and information-rich message with a relatively short lifespan. CfP plays an important role in academic life, not just as an advertisement format, but also as a trigger of and advance organiser for collaborative academic writing. This paper explores the possibilities to create a comprehensive ontology for CfP so that is would be relevant and useful in Research 2.0 context for two main target groups: authors involved in collaborative writing of academic papers, and conference organisers or journal editors. Our study is conducted in three phases. First, we identify existing ontologies and other representation frameworks, which could provide concepts relevant for CfP. Next, a sample of conference CfPs is analysed and compared, to find out the common structures and peculiarities, which could be used for extending the existing ontologies. Finally, we propose Call ontology together with two usage scenarios.

OntoBox: An Abstract Interface and Its Implementation

In this paper we consider OntoBox, an implementation of a simple de-scription logic called the oo-projection, as a persistent knowledge storage. OntoBox is a mediator between the knowledge management systems and conventional information techniques (like OOP languages and data bases). The abstract interface of OntoBox and its basic implementation (OntoBox Storage) are considered. Some implementation issues are discussed, and the potential of the approach is overviewed.

Lightweight Document Semantics Processing in E-learning

There are plenty of projects aimed at incorporating semantic information into present day document processing. The main problem is their real-world usability. E-learning is one of the areas which can take advantage of the semantically described documents. In this paper we would like to introduce a framework of cooperating tools which can help extract, store, visualize semantics in this area.

Modelling and Automatic Extracting of Contextual Semantic Annotations

In order to reach the semantic Web, approaches to automatically extract semantic annotations from textual documents have been proposed. In this paper we propose an approach to automatically extract annotations by taking into account context in order to obtain a better representation of the document content. Our context is modelled by contextual relations built up from both the structure and the semantics of the text. Our approach requires text documents and a domain ontology as input. It automatically generates a set of contextual semantic annotations represented in RDF.

Visualization of Spatial Knowledge with Ontology Trees and Adaptable Search Result Grids in the Era of Web 3.0

With the emerging trend ofWeb 3.0 and the resulting huge amount of usergenerated semantically-enriched data, improved ways of knowledge visualization and human computer interaction are needed. We present several techniques of visualizing particularly spatial knowledge in largely scalable, clear structured ontology trees on the web. In addition, we describe the representation of search results with a combined approach consisting of Ajax-based grids and Google Maps.

Conceptual Foundations for a Service-Oriented Knowledge & Learning Architecture: Supporting Content, Process, and Ontology Maturing

The knowledge maturing model views learning activities as embedded into, interwoven with, and even indistinguishable from everyday work processes. Learning is understood as an inherently social and collaborative activity. The Knowledge Maturing Process Model structures this process into five phases: expressing ideas, distributing in communities, formalizing, ad-hoc learning and standardization. It is applicable not only for content but also to process knowledge and semantics. In the MATURE IP two toolsets will be develop that support the maturing process: a personal learning environment and an organisation learning environment integrating the levels of individuals, communities and organisation. The development is guided by the SER theory of seeding, evolutionary growth and reseeding and is based on generally applicable maturing services.

Business Process Knowledge Integration – A Semantic Based Approach

Knowledge necessary for the creation of business process models is distributed, consists of different types, and expresses different levels of abstraction. Its acquisition and collection into a common knowledge base, which implies integration into a single model, is the goal of the approach we are proposing. In this paper a framework for the integration of business process knowledge is proposed. It is shown how semantic technologies can contribute to the integration of different models, which represent different aspects of an organization, in order to create a more expressive model of business process knowledge.

An Ontological Approach to Semantic Video Analysis for Violence Identification

Along with the rapid increase of available multimedia data, comes the proliferation of objectionable content such as violence and pornography. We need efficient tools for automatically identifying, classifying and filtering out harmful or undesirable video content for the protection of sensitive user groups (e.g. children). In this paper we present a multimodal approach towards the identification and semantic analysis of violent content in video data. We propose a layered architecture and focus on ontological and knowledge engineering aspects of video analysis. We demonstrate the development
of two ontologies defining violent hints hierarchy that low level analysis, in visual and audio modality, respectively should identify. A violence domain ontology, as a reality representation, defines higher-level semantics. Taking under consideration extracted violent hints, spatio-temporal relations and behaviour patterns higher-level semantics automatic inference is possible.

Visual Tools Decipher Historic Artefacts Documentation

Analysing and understanding the evolution of historic artefacts requires the crossexamination of indications ranging from specific pieces of data (remains of the edifice, archival materials, etc.), to generic pieces of knowledge (historical context, comparable cases, theory of architecture, etc.). This research is based on the premise that the artefact’s acts as a media allowing the integration of the above-mentioned heterogeneous indications. Consequently, they may enable information visualisation and retrieval through 2D/3D dynamic graphics. In this contribution, we discuss four SVG-based graphic tools aiming at exploiting visually the relations between an artefact and the above-mentioned indications, i.e. its documentation.

O’Cop, an Ontology Dedicated to Communities of Practice

The Palette project dedicated to lerning in Communities of Practice (CoPs) aims to offer several services for communities of practice, in particular Knowledge Management (KM) services based on an ontology dedicated to CoPs, the so-called O’CoP. Built from information sources about the Palette CoPs, O’CoP aims both at modelling the members of the CoP and at annotating the CoP’s knowledge resources. The paper describes the structure of O’CoP, its main concepts and relations, and it reports some lessons learnt from the cooperative community building of this ontology.

Information Realisation: Textual, Graphical and Audial Representations of the Semantic Web

Information Realisation is the process of presenting data as Textual, Graphical or Audial information to a human user. In this paper, we discuss the importance of this concept with respect to the accessibility of Semantic Web data to a diverse target audience. We provide an ontological point of view, defining the expressive characteristics and application domain of representation formats, thus presenting a system which produces representations customised to the user environment and the nature of the source data. Our approach considers the semantics of the data, not just the structure, and aims to present the information in the most semantically appropriate manner for the given target environment. We provide examples of a simple data set being realised as popular target representation formats: textual (XHTML, RSS); graphical (SVG, X3D); and audial (SoundML, VoiceXML).

An Ontology Based Tool for Competency Management and Learning Paths

Ontologies have already been created in different scientific areas, including knowledge and competency management, however few ontological applications are available at the moment. In this paper we present an ontology based application that we have developed for competency management and learning paths. Specifically, we provide an overview of competency management and related work in this area, a description of the competency ontology and a functional and architectural analysis. This system is being currently deployed for research purposes in a national subsidiary of Microsoft, the IT services multinational firm, with a Microsoft .NET implementation communicating with the competency ontology.

Project TEAL: Add Adaptive e-Learning to your Workflows

Workflow- or task- embedded e-learning is an actual trend in enterprise and office environments. Having been integrated into enterprise workflow or task management systems, e-learning turns into a powerful tool for enterprise knowledge management: the seamless integration into the working environment allows getting actual information about potential learning goals of the user; using up-to-date e-learning technologies enables just-in-time delivery of goal-oriented, user-tailored learning curricula, helping employees to solve problems autonomously and competently. This paper reports about the results of the project TEAL (Task-embedded adaptive e-Learning) taking place at German Research Center for Artificial Intelligence (DFKI). The aim of the project was to prove the concepts and feasibility of task-embedded e-learning by designing a reference architecture and realizing prototypical implementation based on the existing components built at DFKI: WFMS Taskman, LCMS DaMiT and ActiveMath.

Ontology-based Management of Private Multimedia Collections: Meeting the Demands of Home Users

Private users are usually overcharged with the task of managing and maintaining their personal multimedia collections. Even if the complexity of multimedia objects necessitates certain machine-assistance, it is also evident that full-automated organization would not satisfy the requirements of home users as multimedia content contains much more: individual experiences, memories and world concepts. Therefore we propose an approach based on an extensible ontology model to provide appropriate assistance for personal media management, taking advantage of as much existing information resources as possible to apply automatisms. Starting with an investigation of application context and conditions, we present our designed ontology model and the according system architecture for its employment.

A Semantic Content Representation Supporting Re-Purposing of Learning Resources

Because of the costly production of Learning Resources the Re-Use of existing Learning Resources becomes more and more important. But reusing Learning Resources in a new context makes it necessary to adapt them. We have developed a framework as base of a Re-Purposing Tool to support users to perform adaptations of Learning Resources in different dimensions which are crucial when using existing Learning Resources in a new context. The adaptation of Learning Resources is not easy to perform and comprises challenges like to deal with multiple files in multiple formats. To hide this from the user there is need for an abstraction of the underlying details. With a model which is including only the information the user needs and which is abstracting from the obstacles an adaptation of Learning Resources becomes a possible task even for novice users. This paper points out the content representation which is used in the framework to abstract from the given Learning Resources as well as the content ontology which the content representation is based on.

Supporting Domain Experts in Creating Formal Knowledge Models (Ontologies)

We explored how the intended purpose of a knowledge model can influence the modelling process and in particular, how it impacts on the choice points of the underlying modelling methodology. We introduce a classification of knowledge models according to their intended scope, expressiveness and degree of acceptance. As a result, we aim to define critical success factors of methodologies for ontologies that are built by domain experts and that can be used as a basis for knowledge enabled (software) systems

Event-based Ontology Design for Pricing Decision on Organizational Procurement Consulting

Organizational procurement is a process of information exchanges and price bargaining between buyer and seller. The process and its outcome are both influenced by the professional experience of the relevant agents, the cognition of the agents concerning market risk, the analysis of contingency in the bargaining process, etc. Decisions of an enterprise are composed by the individuals in the company. How to congregate and motivate the individuals to make good decisions for running the business in a company, are challenging issues today. A consulting model for the evolution of an organizational market is built, based on literature review of inter-organizational negotiations, and in-depth interviews with top-level executives in a few leading Taiwanese companies engaged in organizational procurement. An experimental study is conducted based on the proposed model, and the empirical data is collected to gain knowledge of organizational procurement decision making. TOVE and Protégé are applied in designing the ontology for creating valuable information for marketplace administrators building appropriate strategies for their businesses.

Performance Solution of SOA Infrastructure for Knowledge Computing

In this paper we will present a complete solution of SOA designed for knowledge computation encapsulation. SOA brings a lot of advantages to the whole ICT process when a difficult on-demand task is computed. On the other hand SOA overhead is nowadays unacceptable for this kind of computation tasks. We have used a semantic approach to describe SOA. Some contributing ideas have appeared – for example a possible approach to cache web services ontologically. This can help in knowledge computing.

Socio Economic Aspects of Consensus in Ontology Building

This paper addresses the problem of how different agents may find consensus on a particular ontology. Mainstream literature on this argument has traditionally described such problem as rooted in the realm of abstract and logical reasoning. On the other hand, a socioeconomic perspective suggests that consensus dynamics might be read as pragmatic processes driven by the interests of those who are concretely affected by the ontology and its change. Assuming a constructivist perspective, we derive from existing literature that the notion of interest might be properly defined as the retrospective need to interpret (and create) a world in which past investments can be reused. From this perspective, an ontology can be intended as a “view of the world” that legitimates the existence of a set of sunk investments made by its users. A tentative framework is proposed where these concepts are applied to describe the process of semantic consensus. The paper concludes with major implications and future work.

From Context to Knowledge: Consecutive Mapping Ontologies and Contexts

Knowledge sharing, exchange and communication are critical tasks in any knowledge management or e-commerce initiative. In order to solve these tasks ontologies can be used. But there are certain communication problems with ontologybased knowledge sharing and exchange connected with context. The paper describes these communication problems, defines two contexts types and suggests methodical basis of solution for communication problems. This methodical basis is considered and factored in the following case study using consecutive mapping between different of context types and content ontology. This case study describes Knowledge Navigator – a map that relates contents of Formalized Management methodology with the corresponding context in order to reach effective knowledge communication to end users.

Text Mining Supported Terminology Construction

In this paper we investigate the contribution of text mining techniques to a methodology of terminology construction from natural language corpora. The application area of our experiment is accidentology. In this context, the results of text mining techniques are used in order to guide the construction of a terminology of road accidents from a collection of accident reports. A model of our field, ontology of accidentology, is used that allows us to carry out the text mining process. The Terminae methodology and the tool supporting it offer the general frame for the resource construction. Further on we shall present our employed text mining techniques and the integration of the results we obtained into different phases of the construction process. Suggestions for further research to improve our techniques are also presented in this study.

Visual Browser: A Tool for Visualizing Ontologies

This paper presents an applocation called Visual Browser that is able to visualize RDF data. It explains the advantage of the RDF/RDFS as well as the way RDF triples are displayed in the visualisation process. One of the most importand features of the programm comprises a two level visualization – the data and the so-called perspective of view. The scope of this architecture is shown on examples. Two very different domains are visualized: WordNet and a Universal information Robot’s knowldege base.

Distributed Knowledge Management in the Absence of Shared Vocabularies

Distributed Knowledge Management Systems (DKMS) are often faced to heterogeneous environments associated with the absence of shared vocabularies. DKMSs realise Knowledge Flows between autonomous Knowledge Nodes as parts of social networks. Schwotzer models the KNs’ individual policies for input relevance and output strategy as Knowledge Ports. Topic Map Technologies are well suited for the semantic integration of distributed, heterogeneous knowledge. But current implementations base on pure naming approaches to Subject Identity in connection with the use of shared vocabularies. Maicher’s SIM Approach helps to use Topic Map Technologies for the semantic integration of distributed, heterogeneous knowledge in the absence of shared vocabularies. To detect Subject similarity it exploits the Topics’ usage in the current context. Our contribution is the liaison of the Knowledge Port Approach and the SIM Approach. This leads to DKMSs which significantly better deal with the absence of shared vocabularies.

An Ontology-Based Framework for Representing Organizational Knowledge

This paper describes an ontology-based organizational knowledge representation framework focused on the specification of a two kinds of ontologies: the top level ontology containing concepts characterizing the typical organizational background and COKE ontologies representing so called core organizational knowledge entities. The framework constitutes an abstract representation of organizational knowledge providing a semantic support for designing knowledge management infrastructure able to interoperate with systems already existing in an organization. Moreover, the annotation of COKE w.r.t. the top level ontology allowed by the framework facilitates their semi-automatic handling, retrieval and evolution monitoring.

A Methodological Approach for Constructing Ontology-Based Reference Models in Digital Production Engineering

In the digital planning process of a manufacturing plant, several partners like OEM, prime contractor and its subcontractors are involved. Since the partners have partially overlapping views (electricity, mechanical structure, plant controlling) on the plant to be designed, they have to exchange data during their collaboration. Due to syntactical, structural and semantical differences, data integration is necessary but also complicated. Our method of resolution comprises an ontology-based reference model, which all partners map to as well as an underlying technical infrastructure. This paper focuses on the methodology for constructing an ontology-based reference model in digital production engineering.

Pre-Built Information Space: Some Observations on the Challenges of Process-oriented Knowledge Management

PreBIS is a research-project1 that develops five core functions of context-aware collaborative information provision, based on user requirements in weakly structured and information intensive business processes. An innovative software architecture will be proposed, that adapts and combines processes, ontologies and document chunks. PreBIS realises four forms of “pre-building” an information space: at the document or information level, in systems integration, at the process level, and in learning routines. The discussions in the project allow some suggestions on how to characterise and handle the challenges in knowledge process modelling, as they were addressed by the aims of the conference.

Topic Identification: Framework and Application

This paper is on topic identification, i. e., the construction of useful labels for sets of documents. Topic identification is essential in connection within categorizing search applications, where several sets of documents are delivered and an expressive description for each category must be constructed on the fly. The contributions of this paper are threefold. (1) It presents a framework to formally specify the topic identification problem along with its desired properties, (2) it introduces a classification scheme for topic identification algorithms and outlines the respective algorithm of the AIsearch meta search engine, (3) it proposes a hybrid approach to topic identification, which relies on classification knowledge of existing ontologies.

Improving Knowledge Sharing through Knowledge Objects Representation

People need information to create new knowledge. For each piece of information obtained, a range of previous knowledge, competences, beliefs and own concept definitions significantly influence personal perception and one’s knowledge creation. This in turn, affects the ability to remember, reason, solve problems and interpret information. These issues have to be considered when planning knowledge management systems, in which information retrieval and handling, reuse, people interaction, knowledge interchange and dissemination comprise its characteristics. This paper is based on the Knowledge Object definition from Merrill and proposes an approach which more precisely enables Knowledge Object representation, taking into account the domain in which a KO is used, a range of previous knowledge, competences, beliefs, concept definitions, user profile and recommendation from community users.

A Comprehensive Guideline for Building a Domain Ontology from Scratch

Conceptual analysis and knowledge representation often require to develop an ontological support. The activity of developing a domain ontology is therefore one of the fundamental steps to be carried out when developing a shared model of the knowledge possessed by an organization, and consequently, one of the pilasters of knowledge management.

It is clear, however, that this activity, as well as all other engineering activities, is constrained to be methodologically coherent in its phases, because the control over correctness of the development method is the only possible way to keep events of such an activity on its own track. Though it would seem attractive to deploy software applications which provide automation to the development of such models, the results of automatic ontology tools in the real practice of knowledge management are definitely disappointing.

We thus would prefer to look at formalized methodologies, and in particular, we are interested in methodologies which work from scratch, namely which aim at providing the ontological structure without any general and supposedly shared reference model in front. That choice is not the ideal one, since in general, scalability is a very desirable property, but since the two problems of developing from scratch and integrating existing parts are deeply different we have to commit to one focus.

After having reviewed the existing methodologies, we understood that these methods, which are depicted at different levels of depth in the current literature, are indeed covering in a reasonable way the several aspects of the development of a domain ontology from scratch, but each has both advantages and drawbacks. We thus carried out an analysis, which is the focus of this paper, about the conditions which make the knowledge engineer commit to one single methodology, defining a set of choosing criteria.

We define a meta-methodology which is based upon the analysis of the choosing conditions in several steps, and model this in the specific case of knowledge management activities.

The paper is organized as follows: Sections 2 and 1 are devoted to describe the framework we refer the ontologies to belong, and Section 3 reviews existing methodologies which have been documented in the recent literature. In Section 4 we provide a description of the meta-methodology we have developed. Section 5 takes some conclusions and sketches further work.

Towards the Semantic Grid: Putting Knowledge to Work in Design Optimization

Modern computational Problem Solving Environments (PSEs) become more and more complex and knowledge intensive in terms of their integrated toolsets, in particular for engineering design search and optimization. Whether these toolsets can be assembled effectively to produce satisfactory results depends heavily on using the best domain practice and following decisions made by skilled engineers in practical situations. In this paper, a knowledge based approach is used to acquire this knowledge from existing sources and model it in a maintainable fashion. Ontologies are used to develop the conceptualization of a knowledge base. In order to reuse this knowledge to provide guidance at knowledge intensive points, we propose a knowledge based advisor, which can give a context-aware critique to guide users through effective operations of building domain workflows. The concept of a state panel is proposed to collect system state information, which is then reasoned about together with various task models in the JESS (Java Expert System Shell) environment. Two reasoning strategies are designed for different advising styles. A multilayer and client-server style architecture is proposed to illustrate how this advisor can be deployed to make available its knowledge advising service to a real workflow construction PSE in a maintainable fashion. Throughout we use the example of these knowledge services in the context of design optimization in engineering.

Managing Operation Knowledge for the Metal Industry

The development of a knowledge management system (KMS) is becoming increasingly important for the metal industry in Taiwan. The ontology design and knowledge search are two major activities of knowledge management. In this paper, we introduce a threestage life cycle for the ontology design and propose a Java/XML-based scheme for automatically generating knowledge search components to reduce the overhead in developing a KMS. The resulting ontology is classified as information ontology and domain ontology so that the objective of semantic match for knowledge search can be realized. The system is built on the top of the component-based KAON development suite which makes it more flexible and robust. We conduct a case study by applying the system to Metal Industries Research & Development Centre (MIRDC), Taiwan to confirm its effectiveness and efficiency in dealing with KM activities. In addition, the proposed reusable scheme endorses the encouraging feasibility of wide applications to different domains.

Managing User Focused Access to Distributed Knowledge

Community web sites exhibit the property that multiple content providers exist. Of course, any portal is only as useful as the quality and amount of its content. Developing original content is time consuming and expensive. To offset the cost, we present a novel framework, viz. SEAL (SEmantic portAL), that builds on Semantic Web standards. We illustrate our approach with examples from the OntoWeb community portal. Community web sites exhibit two dominating properties: They often need to integrate many different information sources and they require an adequate web site management system. SEAL exploits ontologies for fulfilling the requirements set forth by these two properties. Ontologies provide a high level of sophistication for web information integration as well as for web site management.

SEAL-II — The Soft Spot between Richly Structured and Unstructured Knowledge

Recently, the idea of semantic portals on the Web or on the intranet has gained popularity. Their key concern is to allow a community of users to present and share knowledge in a particular (set of) domain(s) via semantic methods. Thus, semantic portals aim at creating highquality access — in contrast to methods like information retrieval or document clustering that do not exploit any semantic background knowledge at all. However, by way of this construction semantic portals may easily suffer from a typical knowledge management problem. Their initial value is low, because only little richly structured knowledge is available. Hence the motivation of its potential users to extend the knowledge pool is small, too.

We here present SEAL-II, a methodology for semantic portals that extends its previous version, by providing a range of ontology-based means for hitting the soft spot between unstructured knowledge, which virtually comes for free, but which is of little use, and richly structured knowledge, which is expensive to gain, but of tremendous possible value. Thus, we give the portal builder tools and techniques in an overall framework to start the knowledge process at a semantic portal. SEAL-II takes advantage of the ontology in order to initiate the portal with knowledge, which is more usable than unstructured knowledge, but cheaper than richly structured knowledge.