In this paper, we conceptualize visual representations (e.g., sketches, CAD drawings, and prototypes) as „artifacts of knowing‟ serving the purposes to share, transform, and symbolize organizational knowledge. First, we propose a comprehensive definition of visual representations by integrating insights from the literature domains of knowledge management and organizational culture. Building on the reviewed literature, we then develop a conceptual framework that articulates the visualization process in terms of a cyclical pathway between the formats (e.g., from sketches to prototypes) and the functions (e.g., from knowledge sharing to knowledge symbolization) of visual representations. After suggesting managerial recommendations for the use of visual representations in organizational knowledge management, we conclude our paper by pointing out the limitations of the current literature, and by suggesting directions for future research on visual knowledge management.
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.
Efficiency of semantic caching is based on reusing of already retrieved data. Reusing of already retrieved data depends on finding the containment of new queries with the older/stored queries. Advantages of semantic cache query processing (Satisfiablity and implication in database domain) have already been demonstrated in the published iterature. Description Logic (DL) has never been applied for checking relational query subsumption/containment. Sound and Complete subsumption algorithms exist for reasoning facts represented in Description Logic. DL is a formalism used to model knowledge of a domain in the form of concepts and a rich set of associations between these concepts. Reasoning on the knowledge base can be performed in order to discover implicit relations. The most important reasoning is the determination of a subsumption relation between the logical expressions. Relational queries are also a form of knowledge description. In this paper, we discuss Subsumption analysis of semantic cache query processing and its advantages in semantic cache query management by using tableau algorithms of DL. In particular, Subsumption algorithms are used to perform reasoning from the previously stored queries in the semantic cache. Query containment can be found by transforming relational queries into DL. Based upon this reasoning, a query can be divided into cache (probe) and erver (remainder) queries. This will not only contribute towards cache query processing but have a significant contribution in the cache management, too. Previously, the implication and satisfiablity techniques in database domain were handling only conjunctive queries. In our algorithms, we handle disjunctive queries, too.
This article aims at providing better understanding of the applicability of Semantic Web tools and technologies in practice. It introduces a case study of the use of semantic technologies for extraction, integration and meaningful search and retrieval of expertise data, as an example of the new approaches to data integration and information management. In particular, the paper discusses the process of building expert profiles in a form of ontology database by integrating competences from structured and unstructured sources. The results of the case study show that emerging Semantic Web technologies such as the OWL 2, SPARQL, SPIN rule language, and public vocabularies such as FOAF, DOAC, bibTeX, Dublin Core and other can be used for building individual and enterprise competence models. The proposed approach extends the functionalities of existing enterprise information systems and offers possibilities for development of future Internet services. This allows organizations to express their core competences and talents in a standardized, machine processable and understandable format, and hence facilitates their integration in the European Research Area and beyond.
An industrialisation of knowledge intensive work can be observed when analysing the transformation of the information society. This means that knowledge work reached a maturity that it can be expressed in form of processes, semantics or rules. When applying a business process oriented view – where knowledge is required to perform certain tasks – such mechanism can be used to develop a so-called knowledge conveyer belt, where knowledge is provided to the knowledge worker in a similar way like material is provided on a production belt. This paper introduces a knowledge conveyer belt as a realisation framework for process-oriented knowledge provision. This approach enables a business and knowledge alignment modelling mechanisms that keeps the “human in the loop”. Samples of projects are mentioned to show the applicability of this knowledge conveyer belt approach.
One of the principles of managing structured knowledge of an application domain is to exploit the notion of an ontology. Generalization of knowledge entities using formal semantic metadata enables classi cation and structuring of knowledge for better metadata management. Classi cation serves to form conceptual hierarchy of ontologies to reflect relationships among entities in the domain semantically while structuring helps to position vertical domain generalizations in appropriate relation-ships horizontally. We present a novel approach for conceptualization of enterprise application information in such a hierarchy to structure knowledge in abstract and domain speci c ontologies in RDFS forming reusable knowledge bases. We overcome conceptualization complexities in ligree enterprise information models by focusing on essential aspects of data types and their semantics to align relationship for business objects, enterprise data types and semantic entities with pragmatic consideration on a lightweigt semantic information model to maximize flexibility and inferential efficiency service query answering as well as reuse of structured knowledge artifacts.
This paper describes a framework for the design of performance evaluation systems in collaborative networks. This framework is composed by a performance information reference model and a multi-criteria decision support method. When used in combination by the members of a collaborative network, results in specific models that result from a collective and negotiated construction.
Based on many analyses at enterprises over the past years we see that the economy nowadays asks for efficient and sustainable solutions in knowledge management (KM). Thus, we propose to follow the principle of value orientation also in managing knowledge regarding that there are different types of business processes with different demand for KM. To confirm this fact and to deduce adequate procedures, we conducted a case study at a logistics service provider introducing the innovative method of knowledge-based value stream mapping.
Knowledge communication is an essential mechanism to facilitate intra- and inter-organizationalnowledge transfer. In order to improve the efficiency of knowledge communi-cation, organizations need to pay particular attention to the clarity of conveyed knowledge in order not to create confusion, misunderstandings, or misapplication of knowledge. In this con-tribution, we show where and how the concept of clarity matters for knowledge management in general, and for knowledge communication in particular. We review and operationalize the clarity concept so that it can become the object of a systematic management effort. Further-more, we show ways of how clarity can be pro-actively and systematically managed. We have tested our conception of clarity in a survey on clarity in knowledge-focused presentations, and we present the results in this paper. An outlook on future research on clarity in knowledge management concludes the article.
This paper looks at the convergence of knowledge management and Enterprise 2.0 and describes the possibilities for an overarching exchange and transfer of knowledge in Enterprise 2.0. This will be underlined by the presentation of the concrete example of T-Systems Multimedia Solutions GmbH (MMS), which describes the establishment of a new portfolio element using a community approach “IG eHealth”. This is typified by the decentralised development of common ideas, collaboration and the assistance available to performing responsibilities as provided by Enterprise 2.0 tools. Regarding the collaboration of knowledge workers as the basis, a regulatory framework will be developed for knowledge management to serve as a template for the systemisation and definition of specific Enterprise 2.0 activities. The paper will conclude by stating enabling factors and supporting Enterprise 2.0 activities, which will facilitate the establishment of a expert knowledge management system for the optimisation of knowledge transfer.
Knowledge-intensive organizations that carry out many Knowledge-Intensive Business Processes (KIBP), seek to improve and enhance their KIBP for gaining competitive advantages. These organizations need to develop their Knowledge Management (KM) infrastructure of KIBP, starting from knowledge audit that is a necessary first step in any KM initiative. As KM infrastructure integrates social and technological disciplines, we developed a combined Socio-Engineering Knowledge Audit Methodology (SEKAM) for a systematic audit of the KM infrastructure in the context of KIBP. In this paper we present and discuss the conceptual framework of SEKAM and its instruments developed in this research.
30.000 advisory calls per year! How to analyze, rate and improve them interactively? For getting these goals a novel technique is introduced, which is based on a structure similar to a music score. Via a “duet”, guided by the advisor called, the main contents of the dialogue are extracted and stored automatically. At this, trained speech recognition is applied for the (known) advisor’s part for monitoring and controlling the call’s course, and keyword spotting is used for the (unknown) “customer” to pick out instances from sets of expected values. The results thereof fill an abstract score annotated to the call conducted. Then, because of the strong structure of such scores, the archive of all these dialogues is an ideal base for retrieval, exploration, comparison and clustering of calls, using e.g. graphical tools like knowCube®.
Although receiving significant attention in management research, the organizational competence concept still remains difficult to apply, due to the vagueness of the theoretical construct, and due to the lack of pragmatic procedures to make it actionable. According to recent research, knowledge visualization may mitigate the elusiveness of the competence concept by assisting the identification, management, and communication of competences. In this paper, we thus review the academic literature in search for conceptual representations designed to support organizational competence mapping at the intra-, and inter-organizational level. By taking a synoptic overview of the collected representations, we single out the building blocks of competence visualization, and develop a corresponding classification. Drawing on this classification, we position twelve existing competence representation methods in an integrative framework to assist practitioners in selecting the right representation method and to inform scholars about future research and development needs.
Classifying phenomena is a key step to building new knowledge, especially in the early stages of a research process. It can bring about multiple advantages and insights, such as overview and comparison. Yet it also poses several risks and constraints. Thankfully, challenges can be over-come by re-classifying items in a domain with alternative classification principles, which lead to new insights or perspectives, as well as highlight previously neglected considerations. This process can be supported by graphic representations. Visualizing the drawn (and redrawn) distinctions can make a classification accessible and versatile, which makes it easier to compare with other classifications. Visualizing classifications can augment the entire research process, including hypothesis formation, testing, interpretation and result reporting. There is no systematic overview of methods to represent (especially qualitative) classifications graphically. This paper fills that gap in the literature. We distinguish between four types of visual classifications, based on their differing ability to emphasize hierarchies or group relations. We label these four types as compilations, configurations, layers, and trees. We analyze their benefits for the research process and point out potential risks to consider when using visualization for classifications purposes in social science research.
According to recent neurobiological and psychological research by A. Damasio respectively G. Gigerenzer it is the aim of this paper to point out the limits of plainly cognitive approaches to decision-making and problem-solving (in economy) and – by showing the significance of emotions and (gut) feelings in decision respectively problem-solving processes to contribute to an essential improvement of Knowledge Management leading to a decisive competitive advantage of enterprises.
Extreme Programming focuses on spreading knowledge through many collaborative practices like pair programming, planning game, and retrospectives. The basic idea behind these practices is to share the work specific knowledge across the development teams as well as the management quarters. This knowledge sharing is said to have an accelerated effect when it is combined with the retrospectives analysis of the knowledge gained and the process performed. This inherent property of Knowledge Management (KM) facilitated by retrospective analysis is being used to teach Extreme Programming (XP) methodology as a graduate level Software Engineering (SE) course and is showing a notable effect on the learning process. The paper describes the KM issues in XP practices and how these issues are being managed for the students to present them with a profound learning experience.
This paper proposes an approach for automatically extracting symptoms associated to a given disease from semantic-based descriptions of health records of patients affected by an investigated pathology. The proposal implements non-standard reasoning services developed in Description Logics for the individuation of informative commonalities in concept collections and can make significantly easier the diagnosis process of rare and unknown diseases.
In this paper we present a novel, semantic-based approach for supporting the software development process in a distributed environment. The approach is based on collecting and preserving knowledge used in the software development process in order to support its usage in similar cases later on. One of the main advantages of this approach is possibility to collect required knowledge automatically by observing the behaviour of a software engineer. The approach has been implemented in the TEAM software system and evaluated in three real-world use cases.
In resource based learning settings learners have to cope with a multitude of resources. One big challenge for learners is managing the knowledge contained in these resources appropriately. We discuss some existing knowledge modeling methods and related tools with regard to learning scenarios. This paper focuses on presenting a knowledge modeling approach based on personal knowledge networks. Aggregation and mapping of these personal networks can form a community network supporting exchange of knowledge. Furthermore a proof-of-concept is described.
Based on an analysis of existing tools and approaches and literature from the areas of design and cognitive science, we identify a set of functional requirements to be met by diagrammatic knowledge mapping techniques and tools in order to be cognitively adequate for extensive personal knowledge management. This collection of requirements can be used to evaluate existing tools or as a guideline for the design of novel knowledge mapping approaches and tools.
Unforeseen Experiences from a Balanced Scorecard Project in the Healthcare Sector
In the context of the Balanced Scorecard development in the Upper Austrian Gesundheits- und Spitals AG (gespag) the methodology of strategy maps was applied in order to build a base for the definition of relevant areas of strategic measures. When applying the methodology it turned out that it is very supportive also from the knowledge management perspective (especially 2nd Generation KM), e.g. for the explication of knowledge, cognitive mapping, the creation of a common-mindset (organisational learning), the storage of information and individual learning about strategy and systemic thinking. Furthermore, it allows organisational knowledge integration meaning that people can integrate both the explicated knowledge in their system or their work, and the appropriate “sense” of the further information provided. The intention of the article is to show that methods of strategic management, and possibly from many other fields, can also be very beneficial in a knowledge management context.
Determining fields of excellence in the know-how of knowledge intensive companies is often a crucial decisional process, aimed e.g., at identifying the competence to be strengthened or to invest on in a long term strategy. In this paper we propose a semantic-based approach for automatic extraction of such a specializing knowledge, usually called Core Competence in knowledge management literature. The proposed approach exploits Description Logics as formalism for the representation of knowledge sources and implements novel reasoning services, in particular informative common subsumers specifically devised for Core Competence evaluation.
Several data quality management (DQM) tasks like duplicate detection or consistency checking depend on domain specific knowledge. Many DQM approaches have potential for bringing together domain knowledge and DQM metadata. We provide an approach which uses this knowledge modeled in ontologies instead of aquiring that knowledge by cost-intensive interviews with domain-experts. These ontologies can directly be annotated with DQM specific metadata. With our approach a synergy effect can be achieved when modeling a domain ontology, e.g. for defining a shared vocabulary for improved interoperability, and performing DQM. We present three DQM applications which directly use knowledge provided by domain ontologies. These applications use the ontology structure itself to provide correction suggestions for invalid data, identify duplicates, and to store data quality annotations at schema and instance level.
This paper introduces the LIR-Schema, a framework to model knowledge flows within a company based on model-theory. Competence management is integrated in this framework as a tool for modelling the contexts of sender and receiver of expertise. The main target of this framework is to reduce the knowledge gap between experts and laymen within the company.
In the paper the new possibilities of eLearning 2.0 management systems for knowledge production, experience sharing and communication are presented. The Web 2.0 effects and mechanisms for knowledge capturing and construction are discussed. Reviews of seven new generation learning systems are done with aim one of them to be selected for knowledge building and competence development during the university education as well as after degree receiving. The analysis of eLearning 2.0 management systems is performed in context of the IEEE LTSA (Learning Technology Systems Architecture) component architecture.
There is a significant gap between the services provided by dedicated information systems and general desktop systems for document communication and preparation. This situation is a serious knowledge-management problem, which often results in information loss, poor communication, and confusion among users. Semantic desktops promise to bring knowledge-based services to common desktop applications and, ultimately, to support knowledge management by adding advanced functionality to familiar computing environments. By custom tailoring these systems to different application domains, it is possible to provide dedicated services that assist users in combining document handling and communication with structured workflow processes and the services provided by dedicated systems. This paper presents a model for developing custom-tailored document processing for semantic-desktop systems. Our approach has been applied to the domain of military command and control, which as based on highly-structured document-driven processes.
Creating Profound Change and Radically New Knowledge as Core Challenges in Knowledge Management
This paper introduces an alternative approach to innovation: Emergent Innovation. As opposed to radical innovation Emergent Innovation finds a balance and integrates the demand both for radically new knowledge and at the same time for an organic development from within the organization. From a knowledge management perspective one can boil down this problem to the question of how to cope with the new and with profound change in knowledge. This question will be dealt with in the first part of the paper. As an implication the alternative approach of Emergent Innovation will be presented in the second part: this approach looks at innovation as a socio-epistemological process of “learning from the future”.