Semantic Knowledge Management: An Ontology-Based Framework

Semantic Knowledge Management: An Ontology-Based Framework

Antonio Zilli (University of Salento, Italy), Ernesto Damiani (University of Milan, Italy), Paolo Ceravolo (University of Milan, Italy), Angelo Corallo (University of Salento, Italy) and Gianluca Elia (University of Salento, Italy)
Indexed In: SCOPUS View 1 More Indices
Release Date: August, 2008|Copyright: © 2009 |Pages: 458
DOI: 10.4018/978-1-60566-034-9
ISBN13: 9781605660349|ISBN10: 1605660345|EISBN13: 9781605660356|ISBN13 Softcover: 9781616925512
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Description & Coverage

The massive quantity of data, information, and knowledge available in digital form on the web or within the organizational knowledge base requires a more effective way to control it. The Semantic Web and its growing complexity demands a resource for the understanding of proper tools for management.

Semantic Knowledge Management: An Ontology-Based Framework addresses the Semantic Web from an operative point of view using theoretical approaches, methodologies, and software applications as innovative solutions to true knowledge management. This advanced title provides readers with critical steps and tools for developing a semantic based knowledge management system.


The many academic areas covered in this publication include, but are not limited to:

  • Activity Theory
  • Automatic multimedia representation
  • Domain knowledge
  • E-business enhancement
  • Financial news analysis
  • Interaction in virtual communities
  • KIWI
  • Knowledge management implementation
  • Knowledge-based innovations
  • Office knowledge management
  • Ontology Engineering
  • Ontology learning system
  • Ontology-based framework
  • Personalized information retrieval
  • Project memories in organizations
  • Search Engines
  • Semantic based applications
  • Semantic in organizational knowledge management
  • Semantic knowledge management
  • Semantic virtual office
  • Semantic Web approach
  • Semantic Web system supporting e-learning
  • Semantic-based learning environment
  • Semantic-based P2P reputation systems
  • Software Agents
  • Travel support system
  • Web Infrastructure
  • Workflow management system
Reviews and Testimonials

Emergent semantics provides a natural solution as its definition is based on a process of finding stable agreements; constant evolution is part of the model and stable states, provided they exist, are autonomously detected. Also, emergent semantics techniques can be applied to detect and even predict changes and evolution in the state of an organization or a community.

– Antonio Zilli, University of Lecce

This book assembles 28 chapters that detail how to develop a semantic-based knowledge management system.

– Book News Inc. (Decemeber 2008)
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Editor Biographies
Antonio Zilli graduated in physics. He is research fellow at e-business management section at the Scuola Superiore Isufi – Univeristy of Salento (Lecce, Italy). His research interests regard the technologies that enable powerful virtual collaboration in communities and organizations. He participated in research projects on semantic web studying how to represent and use ontologies and semantic descriptions, and participated at the design of technologies and tools for managing ontologies, semantic metadata and semantically annotated documents (semantic search engine). He participated in research projects on knowledge management in economic districts composed of organization and public administration. He participated on research projects on social network analysis as a strategy for monitoring and improving collaboration in wide teams and with a particular focus on the changes brought by the technological innovations. He is in the program board of the international conference on knowledge management in organization.
Ernesto Damiani is a full professor at the department of information technology of the university of Milan, Italy. He has held visiting positions at several international institutions, including George Mason University (USA), and is an adjunct professor at the University of Technology, (Australia). Prof. Damiani coordinates several research projects funded by the Italian ministry of research, the European commission and by a number of private companies including cisco, st microelectronics, siemens mobile and bt exact. His research interests include knowledge extraction and metadata design, advanced software architectures and soft computing. On these topics he has filed international patents and published more than 200 refereed papers in international journals and conferences. Ernesto Damiani is the vice-chair of the ifip wg on web semantics (wg 2.12) and the secretary of the ifip wg on open source systems (wg 2.13). He is the author, together with W. Grosky and R. Khosla, of the book “Human-Centered e-Business” (Kluwer 2003). In 2000, he was the recipient of acm sigapp outstanding service award.
Paolo Ceravolo (date of birth: October 13, 1977) holds a degree of laurea in philosophy from the philosophy department of the Catholic University of Milan (Italy) and a PhD in computer science from the department of information technologies of the University of Milan (Italy). Currently, he is an assistant professor at the same department. His research interests include ontology-based knowledge extraction and management, process measurement, semantic web technologies, emergent process applied to semantics, uncertain knowledge and soft computing. On these topics he has published several scientific papers and book chapters.

He is involved in the organization of different conferences such as: innovation in knowledge-based & intelligent engineering systems (KES), IEEE/IES conference on digital ecosystems and technologies (IEEE-DEST), knowledge management in organizations (KMO). Since 2008 he is secretary of the IFIP 2.6 working group on database semantics.

Angelo Corallo is researcher at the department of innovation engineering at the University of Lecce. He graduated in physics at the University of Lecce. He has been researcher at the osservatorio astronomico di capodimonte. He teaches within the master and PhD of scuola superiore isufi (University of Lecce) and PhD program in complex industrial systems. His research interests encompass mainly the co-evolution of technological and organizational innovation, with specific focus on business ecosystem, extended enterprise and on knowledge management and collaborative working environment in project based organizations. He has been and is currently involved in many research projects related with technological and organizational issues both at Italian and European level (knowledge hub, technological system for tourism and cultural heritage, multichannel adaptive information system, digital business ecosystem). Angelo collaborates with Massachusetts Institute of Technology in projects related to enterprise process modeling enabling business to e-business transition and social network analysis in community of innovation. He collaborates with the business enterprise integration domain task force of OMG in order to define an organizational metamodel supporting the architecture of business modelling framework.
Gianluca Elia is a researcher in knowledge and learning networks at the faculty of engineering – department of innovation engineering, University of Salento (Italy) and at the e-business management section (eBMS) of the scuola superiore isufi – University of Salento (Italy). After his degree in computer science engineering, he has completed the master studies in e-business management at the e-business management section (eBMS) of the scuola superiore isufi. His research field concerns the methodological and technological aspect of knowledge management and web learning processes and platforms. Moreover, he is responsible for some research projects involving Mediterranean countries in experimenting innovative approaches of human capital creation through the usage of internet based technologies.
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In the last few years, many international organizations and enterprises have designed, developed and deployed advanced knowledge management systems that are now vital for their daily operations. Multi-faceted, complex content is increasingly important for companies and organizations’ successful operation and competitiveness.

The Semantic Web perspective has added to knowledge management systems a new capability: reasoning on ontology-based metadata. In many application fields, however, data semantics is getting more and more context- and time-dependent, and cannot be fixed once and for all at design time.

Recently, some novel knowledge generation and access paradigms such as augmented cognition, case-study-based reasoning and episodic games have shown the capability of accelerating the kinetics of ideas and competence transmission in creative communities, allowing organizations to exploit the high interactive potential of broadband and mobile network access.

In this new scenario, traditional design-time data semantics frozen in database schemata or other metadata is only a starting point. Online, emergent semantics is playing an increasingly important role. The supply of semantics is twofold: firstly, human designers are responsible for providing initial semantic mappings between information and its environment used for context-aware access. Secondly, the meaning of data is dynamically augmented and adapted taking into account organizational processes and, in general, human cognition.

The Semantic Web paradigm was proposed to tackle some of the problems related to implicit representation of data semantics affecting Web-related data items (e.g., email messages or HTML pages), providing the capability of updating and modifying ontology-based semantic annotations. Today, advanced knowledge management platforms incorporate on-demand production of Semantic-Web style metadata based on explicit, shared reference systems such as ontology vocabularies, which consist of explicit though partial definitions of the intended meaning for a domain of discourse. However, providing a consistent Semantic-Web style explicit representation of an organization’s data semantics is only a first step for leveraging organizational knowledge. It is widely recognized that business ontologies can be unstable and that managing ontology evolution and alignment is a constant challenge, as well as a heavy computational burden. Indeed, this problem cannot be tackled without realizing that integrating initial, design-time semantics with emergent, interaction-time semantics is as much an organizational, business-related process as a technology based one.

The KIWI Vision

The KIWI (Knowledge-based Innovation for the Web Infrastructure) vision was born out of an interdisciplinary research project involving a computer science research group, SESAR lab (, and eBMS, an advanced business school working in the e-business management area ( The project was funded by the Italian Ministry of Research - Basic Research Fund (FIRB).

KIWI envisioned a distributed community composed of information agents sharing content, e.g. in advanced knowledge management platforms, corporate universities or peer-to-peer multimedia content sharing systems. In this community, agents and human actors are able to cooperate in building new semantics based on their interaction and adding it to content, irrespective of the source (and vocabulary) of the initial semantics of the information.

The KIWI vision considers emergent semantics constructed incrementally in this way as a powerful tool for increasing content validity and impact.

The observation that emergent semantics results from a self-organizing process has also some interesting consequences on the stability of the content from the business management and social sciences point of view. Also, this perspective promises to address some of the inherently hard problems of classical ways of building semantics in information systems. Emergent semantics provides a natural solution as its definition is based on a process of finding stable agreements; constant evolution is part of the model and stable states, provided they exist, are autonomously detected. Also, emergent semantics techniques can be applied to detect and even predict changes and evolution in the state of an organization or a community.

This Book’s Structure

This book contains a number of contributions from well-recognized international researchers who, although working independently, share at least some of the aims and the interdisciplinary approach of the original KIWI project.

The contents are structured in three sections, the first one is completely related to the KIWI project, the activities, the theoretical results and the prototypes developed are presented and discussed. The work was developed in a methodological framework that represents the phases and the tools for an effective introduction of a semantic-based knowledge management platform in a community. The second one presents other theoretical works related to the introduction of the semantic description of knowledge resource in organization or in technological environment. The third section instead is devoted to the description of technological systems and applications that are planned and developed for improving with the semantic aspect the management of knowledge resources.

More in particular, Chapter 1, “KIWI: A Framework For Enabling Semantic Knowledge Management”, by Paolo Ceravolo, Angelo Corallo, Ernesto Damiani, Gianluca Elia, and Antonio Zilli, provides a general overview of the KIWI vision and approach, while Chapter 2: “Introduction To Ontology Engineering”, written by Paolo Ceravolo and Ernesto Damiani, provides a no-prerequisites introduction to Semantic-Web style explicit representation of data semantics. Thanks to these introductory chapters the reader will be able to understand the basic techniques of data annotation by means of ontology-based vocabularies. Semantic-Web style annotations give an explicit representation of the data semantics as perceived at design-time by the data owners and creators. However, in many cases semantic annotations are not created manually, but extracted from existing data.

Chapter 3, “OntoExtractor: A Tool For Semi-Automatic Generation And Maintenance Of Taxonomies From Semi-Structured Documents”, by Marcello Leida, and Chapter 4: “Search Engine: Approaches And Performance” written by Eliana Campi and Gianluca Lorenzo, respectively discuss semi-automatic techniques and tools for generating semantic annotations, and the performance of classic (as opposed to semantics-aware) access and search techniques. These chapters identify many potential advantages and pitfalls of a “straightforward” application of Semantic Web techniques to add semantics-aware annotations to business data.

Then, the scope of the book broadens, taking into account later additions to annotations expressing data semantics due to interactions. Chapter 5 “Toward Semantic-based P2P Reputation Systems”, by Ernesto Damiani and Marco Viviani, shows how peer-to-peer interaction at different levels of anonymity can be used to superimpose new annotations to existing metadata, assessing their reliability and trustworthiness. An important field for exploiting online, emergent semantics based on interactions is Web-based e-Learning, where the learner patterns of behavior when interacting with content can be captured and transformed into additional annotations to the content itself or to its original metadata.

Chapter 6, “SWELS: A Semantic Web System Supporting e-Learning”, by Gianluca Elia, Giustina Secundo and Cesare Taurino, explores this semantics-aware perspective on e-Learning, while Chapter 7, “Approaches To Semantics In Knowledge Management”, by Cristiano Fugazza, Stefano David, Anna Montesanto and Cesare Rocchi, discusses some fundamental problems raised by the adoption of explicit semantics representation techniques as the basis of knowledge management systems.

The next two chapters deal with the relation between design-time and emergent data semantics on one side and the definition of the business processes where data are used on the other side. Namely, Chapter 8 “A Workflow Management System For Ontology Engineering”, by Alessandra Carcagnì, Angelo Corallo, Antonio Zilli, Nunzio Ingraffia and Silvio Sorace, describes a methodology and its implementation in a workflow management system for producing ontology-based representations. Chapter 9, “Activity Theory For Knowledge Management In Organizations”, by Lorna Uden, proposes a theoretical foundation to workflows for generating knowledge.

The following chapters discuss in detail the application of the KIWI vision to specific business-related scenarios. Namely, Chapter 10, “Knowledge Management and Interaction in Virtual Communities”, by Maria Chiara Caschera, Arianna D’Ulizia, Fernando Ferri and Patrizia Grifoni, is about the practical integration of design-time and emergent semantics in the context of the highly dynamic virtual communities of Web 2.0. Chapter 11: “An Ontological Approach To Manage Project Memories In Organizations”, by Davy Monticalo, Vincent Hilaire, Samuel Gomes and Abderrafiaa Koukam, goes back to organizational knowledge management, elaborating on the specific problems posed by managing semantically rich content such as project memories. Chapter 12 “K-link+: A P2P Semantic Virtual Office for Organizational Knowledge Management”, by Carlo Mastroianni, Giuseppe Pirrò and Domenico Talia describes a practical solution relying on peer-to-peer technology and protocols supporting different levels of anonymity.

The book’s concluding chapters contain highly interesting and practical case-studies. Namely, Chapter 13 “Formalizing And Leveraging Domain Knowledge In The K4CARE Home Care Platform”, by Ákos Hajnal, Antonio Moreno, Gianfranco Pedone and David Riaño, deals with the increasingly important scenario of knowledge management supporting healthcare and assisted living environments. Chapter 14, “Knowledge Management Implementation In A Consultancy Firm”, by Kuan Yew Wong and Wai Peng Wong, presents a case study related to managing the information produced in a consultancy activity, which present interesting problems related to intellectual rights management. Chapter 15, “Financial News Analysis Using A Semantic Web Approach”, by Alex Micu, Laurens Mast, Viorel Milea, Flavius Frasincar and Uzay Kaymak, discusses the user centered extraction of semantics from financial newsfeeds.

In Chapter 16, “Enhancing E-Business on the Semantic Web through Automatic Multimedia Representation”, by Manjeet Rege and Ming Dong and Farshad Fotouhi, a Semantic Web automatic data description process is applied to multimedia content, the system is aimed at improving electronic collaboration between firms and customers.

Chapter 17, “Utilizing Semantic Web and Software Agents in a Travel Support System”, by Maria Ganzha, Maciej Gawinecki, Marcin Paprzycki, Rafal Gasiorowski, Szymon Pisarek, Wawrzyniec Hyska, presents an ontology based e-business application: ontologies are used to make functioning an agent-based travel support system, the ontology , used to demarcate data, enable to manage user profiles. In the end, Chapter 18, “Personalized Information Retrieval in a Semantic-based Learning Environment”, by Antonella Carbonaro and Rodolfo Ferrini, discusses a learning system able to arrange course using an ontological description of contents and users.


With the rapid emergence of social applications on the Web, self-organization effects have once again proven their interest as a way to add semantics to existing business knowledge.

This book discusses how identifying emerging relationships among previously unrelated content items (e.g., based on user and community interaction) may dramatically increase the content’s business value. ES (Emergent Semantics) techniques enrich content via a self-organizing process performed by distributed agents adaptively developing the proper interpretation via multi-party cooperation and conflict resolution. Emergent content semantics is dynamically dependent on the collective behavior of communities of agents, which may have different and even conflicting interests and agendas.

According to the KIWI overall vision, a new generation of content will self-organize around end-users semantic input, increasing its business value and timeliness. The KIWI approach envisions a more decentralized, user-driven “imperfect”, time-variant Web of semantics that self-organizes dynamically, tolerating conflicts.