Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2015

Kraker Peter, Lindstaedt Stefanie , Schlögl C., Jack K.

Visualization of co-readership patterns from an online reference management system

Journal of Informetrics, Elsevier, NULL, 2015

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In this paper, we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating knowledge domain visualizations. First, we investigate the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we use co-readership patterns to map the field of educational technology. The resulting visualization prototype, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
2015

Kraker Peter, Schlögl C. , Jack K., Lindstaedt Stefanie

The Quest for Keeping an Overview: Knowledge Domain Visualizations based on Co-Readership Patterns

In: Science 2.0, IEEE Computer Society Special Technical Community on Social Networking E-Letter, vol. 3, no. 1, 2015

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Given the enormous amount of scientific knowledgethat is produced each and every day, the need for better waysof gaining – and keeping – an overview of research fields isbecoming more and more apparent. In a recent paper publishedin the Journal of Informetrics [1], we analyze the adequacy andapplicability of readership statistics recorded in social referencemanagement systems for creating such overviews. First, weinvestigated the distribution of subject areas in user librariesof educational technology researchers on Mendeley. The resultsshow that around 69% of the publications in an average userlibrary can be attributed to a single subject area. Then, we usedco-readership patterns to map the field of educational technology.The resulting knowledge domain visualization, based on the mostread publications in this field on Mendeley, reveals 13 topicareas of educational technology research. The visualization isa recent representation of the field: 80% of the publicationsincluded were published within ten years of data collection. Thecharacteristics of the readers, however, introduce certain biasesto the visualization. Knowledge domain visualizations based onreadership statistics are therefore multifaceted and timely, but itis important that the characteristics of the underlying sample aremade transparent.
2013

Pammer-Schindler Viktoria, Simon Nina, Lindstaedt Stefanie

Reflective Learning at Work

Advances in Technology Enhanced Learning, Fridolin Wild, Paul Lefrere, Peter Scott, 2013

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2013

Breitweiser Christian, Terbu Oliver, Holzinger Andreas, Brunner Clemens, Lindstaedt Stefanie , Müller-Putz Gernot

iScope - Viewing Biosignals on Mobile Devices.

Joint International Conference on Pervasive Computing and the Networked World, Qiaohong Zu, Bo Hu, Atilla Elçi , Springer, 2013

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We developed an iOS based application called iScope to monitor biosignals online. iScope is able to receive different signal types via a wireless network connection and is able to present them in the time or the frequency domain. Thus it is possible to inspect recorded data immediately during the recording process and detect potential artifacts early without the need to carry around heavy equipment like laptops or complete PC workstations. The iScope app has been tested during various measurements on the iPhone 3GS as well as on the iPad 1 and is fully functional.
2012

Pammer-Schindler Viktoria, Kump Barbara, Lindstaedt Stefanie

Tag-based algorithms can predict human ratings of which objects a picture shows

Multimedia Tools and Applications, Springer US, 2012

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Collaborative tagging platforms allow users to describe resources with freely chosen keywords, so called tags. The meaning of a tag as well as the precise relation between a tag and the tagged resource are left open for interpretation to the user. Although human users mostly have a fair chance at interpreting this relation, machines do not. In this paper we study the characteristics of the problem to identify descriptive tags, i.e. tags that relate to visible objects in a picture. We investigate the feasibility of using a tag-based algorithm, i.e. an algorithm that ignores actual picture content, to tackle the problem. Given the theoretical feasibility of a well-performing tag-based algorithm, which we show via an optimal algorithm, we describe the implementation and evaluation of a WordNet-based algorithm as proof-of-concept. These two investigations lead to the conclusion that even relatively simple and fast tag-based algorithms can yet predict human ratings of which objects a picture shows. Finally, we discuss the inherent difficulty both humans and machines have when deciding whether a tag is descriptive or not. Based on a qualitative analysis, we distinguish between definitional disagreement, difference in knowledge, disambiguation and difference in perception as reasons for disagreement between raters.
2012

Drachsler Hendrik, Verbert Katrien, Manouselis Nikos, Vuorikari Riina, Wolpers Martin, Lindstaedt Stefanie

Preface [Special issue on dataTEL–Data Supported Research in Technology-Enhanced Learning]

Int. J. Technology Enhanced Learning, 2012

Journal
Technology Enhanced Learning is undergoing a significant shift in paradigm towards more data driven systems that will make educational systems more transparent and predictable. Data science and data-driven tools will change the evaluation of educational practice and didactical interventions for individual learners and educational institutions. We summarise these developments and new challenges in the preface of this Special Issue under the keyword dataTEL that stands for ‘Data-Supported Technology-Enhanced Learning’.
2012

Devaurs Didier, Rath Andreas S., Lindstaedt Stefanie

Exploiting the User Interaction Context for Automatic Task Detection

Applied Artificial Intelligence, Taylor & Francis Group, 2012

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Detecting the task a user is performing on his/her computer desktop is important in order to provide him/her with contextualized and personalized support. Some recent approaches propose to perform automatic user task detection by means of classifiers using captured user context data. In this paper we improve on that by using an ontology-based user interaction context model that can be automatically populated by (1) capturing simple user interaction events on the computer desktop and (2) applying rule-based and information extraction mechanisms. We present evaluation results from a large user study we have carried out in a knowledge-intensive business environment, showing that our ontology-based approach provides new contextual features yielding good task-detection performance. We also argue that good results can be achieved by training task classifiers “offline” on user context data gathered in laboratory settings. Finally, we isolate a combination of contextual features that present a significantly better discriminative power than classical ones.
2011

Erdmann Michael, Hansch Daniel, Pammer-Schindler Viktoria, Rospocher Marco, Ghidini Chiara, Lindstaedt Stefanie , Serafini Luciano

Applications of Semantic Wikis - Bringing Complementary Models and People Together: A Semantic Wiki for Enterprise Process and Application Modelling

Context and Semantics for Knowledge Management}, Warren, P., Davies, J., Simperl, E., Springer, 2011

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This chapter describes some extensions to and applications of the Semantic MediaWiki. It complements the discussion of the SMW in Chap. 3. Semantic enterprise wikis combine the strengths of traditional content management systems, databases, semantic knowledge management systems and collaborative Web 2.0 platforms. Section 12.1 presents SMW+, a product for developing semantic enterprise applications. The section describes a number of real-world applications that are realized with SMW+. These include content management, project management and semantic data integration. Section 12.2 presents MoKi, a semantic wiki for modeling enterprise processes and application domains. Example applications of MoKi include modeling tasks and topics for work-integrated learning, collaboratively building an ontology and modeling clinical protocols. The chapter illustrates the wealth of activities which semantic wikis support.
2011

Kraker Peter, Lindstaedt Stefanie

Research Practices on the Web in the Field of Technology Enhanced Learning

ACM Webscience Conference 2011, 2011

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Recently, developments under the banners of Science/Research 2.0 have received a lot of attention in the scientific community. Along with Web 2.0 tools and technologies, a certain change in researcher practices can be observed. The study proposed for this paper was conducted to gain first insight into these practices among researchers in Technology Enhanced Learning (TEL). We conducted two focus groups with a total of 14 participants from the domains of knowledge management and e-learning. Only a limited amount of Science 2.0 practices were identified, mostly related to research design and publication. Potentials for support, however, exist in all steps of the TEL research process. We conclude that tools and technologies must either support existing practice to provide a benefit, or solve obvious shortcomings in existing practice.
2011

Granitzer Michael, Lindstaedt Stefanie

Web 2.0: Applications and Mechanisms J.UCS Special Issue

JUCS - Journal of Universal Computing, 2011

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2011

Granitzer Michael, Lindstaedt Stefanie

Semantic Web: Theory and Applications

Journal of Universal Computer Science, 2011

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2011

Rath Andreas S., Devaurs Didier, Lindstaedt Stefanie

An Ontology-Based Approach for Detecting Knowledge Intensive Tasks

Journal of Digital Information Management, Pichappan, P., Jacobs, D. , Digital Information Research Foundation, 2011

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In the context detection field, an important challenge is automatically detecting the user's task, for providing contextualized and personalized user support. Several approaches have been proposed to perform task classification, all advocating the window title as the best discriminative feature. In this paper we present a new ontology-based task detection approach, and evaluate it against previous work. We show that knowledge intensive tasks cannot be accurately classified using only the window title. We argue that our approach allows classifying such tasks better, by providing feature combinations that can adapt to the domain and the degree of freedom in task execution.
2011

Granitzer Michael, Lindstaedt Stefanie

Knowledge Work : Knowledge Worker Productivity , Collaboration and User Support

J.UCS - Journal of Universal Computer Science, 2011

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2011

Lindstaedt Stefanie , Stern Hermann, Beham Günter, Prettenhofer P., Scheir Peter

Applying Language Technologies to Support Work-Integrated Learning

SDV. Sprache und Datenverarbeitung: International Journal for Language Data Processing, Current Trends in Technology Enhanced Learning, Schmitz, H.-C., Wolpers, M., Universitätsverlag Rhein-Ruhr, 2011

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2011

Lindstaedt Stefanie , Kump Barbara, Rath Andreas S.

Context-Aware Recommendation for Work-Integrated Learning

Context and Semantics for Knowledge Management. Technologies for Personal Productivity, Warren, P., Davies, J., Simperl, E., Springer, 2011

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Within this chapter we first outline the important role learning plays within knowledge work and its impact on productivity. As a theoretical background we introduce the paradigm of Work-Integrated Learning (WIL) which conceptualizes informal learning at the workplace and takes place tightly intertwined with the execution of work tasks. Based on a variety of in-depth knowledge work studies we identify key requirements for the design of work-integrated learning support. Our focus is on providing learning support during the execution of work tasks (instead of beforehand), within the work environment of the user (instead of within a separate learning system), and by repurposing content for learning which was not originally intended for learning (instead of relying on the expensive manual creation of learning material). In order to satisfy these requirements we developed a number of context-aware knowledge services. These services integrate semantic technologies with statistical approaches which perform well in the face of uncertainty. These hybrid knowledge services include the automatic detection of a user’s work task, the ‘inference’ of the user’s competencies based on her past activities, context-aware recommendation of content and colleagues, learning opportunities, etc. A summary of a 3 month in-depth summative workplace evaluation at three testbed sites concludes the chapter.
2011

Weber Nicolas, Lindstaedt Stefanie

A User Centered Approach for Quality Assessment in Social Systems

KMIS, 2011

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Analyzing the meaning of quality in information systems has a long tradition. As a result of the increasing amount of user generated content on the web, addressing quality is more relevant than ever. Since information is produced and consumed by different people in various contexts the perception of quality is always closely tied to the users’ situation. This work proposes an approach for assessing quality in social systems with respect to the users’ current needs.
2011

Stern Hermann, Pammer-Schindler Viktoria, Lindstaedt Stefanie

A Preliminary Study on Interruptibility Detection based on Location and Calendar Information

Third Workshop on Context-Systems Design, Evaluation and Optimisation (CoSDEO) 2011, December 6th - 8th, Copenhagen, Denmark, 2011., 2011

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Modern communication technology-such as mobile phonesincreases our level of availability, but also raises the risk of being inappropriately interrupted. In this paper, we present our on-going research on automatically detecting a user’s interruptibility. This is the first step towards (i) contextualizing the modus of message notification, ie making the notification more or less attention-grabbing, and (ii) contextualizing message ranking, ie, prioritizing messages according to their relevance for the user’s current level of activity. We describe our approach of automatically detecting a user’s interruptibility based on location and calendar information. Both kinds of data are easily available in a mobile setting using smartphones. Second, we present a preliminary study that evaluates (i) whether GPS information is available sufficiently for our purpose in a real-world setting, and (ii) whether the computed interruptibility corresponds to a user’s own perception of interruptibility.
2010

Beham Günter, Lindstaedt Stefanie , Ley Tobias, Kump Barbara, Seifert C.

MyExperiences: Visualizing Evidence in an Open Learner Model

Adjunct Proceedings of the 18th Conference on User Modeling, Adaptation, and Personaization, Posters and Demonstrations, Bohnert, B., Quiroga, L. M., 2010

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When inferring a user’s knowledge state from naturally occurringinteractions in adaptive learning systems, one has to makes complexassumptions that may be hard to understand for users. We suggestMyExperiences, an open learner model designed for these specificrequirements. MyExperiences is based on some of the key design principles ofinformation visualization to help users understand the complex information inthe learner model. It further allows users to edit their learner models in order toimprove the accuracy of the information represented there.
2010

Ullmann Thomas Daniel, Wild Fridolin, Scott Peter, Duval Erik, Parra G., Reinhardt W., Heinze N., Kraker Peter, Fessl Angela, Lindstaedt Stefanie , Nagel T., Gillet D.

A science 2.0 infrastructure for technology-enhanced learning

Computer Science Education, 2010

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Science 2.0 is a rather young concept and despite its short historyalready induced numerous controversial positions, oscillating between newtechnologies and new practices. Even though many TEL researchers already useScience 2.0 tools, although not always labeled as such, there is no commonlyshared practice and tools in use. Within this paper, we investigate the conceptof Science 2.0 and propose an embracing definition. From there we investigateexisting practice with pilot studies and propose a framework for further indepthstudy and elicitation of Science 2.0 practices of technology-enhancedlearning researchers. Furthermore, we propose a mash-up architecture andconcrete infrastructure to leverage Science 2.0 practice and technologies in ourfield, including the proposal of a publication feed format, a retrieval API, andthe provision of an initial set of data sources and services. We illustrate the useof this infrastructure with several Science 2.0 application examples, therebydemonstrating the strength of this infrastructure and architecture.
2010

Verbert Katrien, Duval Erik, Lindstaedt Stefanie , Gillet Denis

Context-aware recommender systems

Journal of Universal Computer Science, Springer, 2010

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2010

Stern Hermann, Kaiser Rene, Hofmair P., Lindstaedt Stefanie , Scheir Peter, Kraker Peter

Content Recommendation in APOSDLE using the Associative Network

Journal of Universal Computer Science, 2010

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One of the success factors of Work Integrated Learning (WIL) is to provide theappropriate content to the users, both suitable for the topics they are currently working on, andtheir experience level in these topics. Our main contributions in this paper are (i) overcomingthe problem of sparse content annotation by using a network based recommendation approachcalled Associative Network, which exploits the user context as input; (ii) using snippets for notonly highlighting relevant parts of documents, but also serving as a basic concept enabling theWIL system to handle text-based and audiovisual content the same way; and (iii) using the WebTool for Ontology Evaluation (WTE) toolkit for finding the best default semantic similaritymeasure of the Associative Network for new domains. The approach presented is employed inthe software platform APOSDLE, which is designed to enable knowledge workers to learn atwork.
2009

Lindstaedt Stefanie , Moerzinger R., Sorschag R. , Pammer-Schindler Viktoria, Thallinger G.

Automatic Image Annotation using Visual Conent and Folksonomies

Multimedia Tools and Applications, Springer US, 2009

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Automatic image annotation is an important and challenging task, andbecomes increasingly necessary when managing large image collections. This paperdescribes techniques for automatic image annotation that take advantage of collaborativelyannotated image databases, so called visual folksonomies. Our approachapplies two techniques based on image analysis: First, classification annotates imageswith a controlled vocabulary and second tag propagation along visually similar images.The latter propagates user generated, folksonomic annotations and is thereforecapable of dealing with an unlimited vocabulary. Experiments with a pool of Flickrimages demonstrate the high accuracy and efficiency of the proposed methods in thetask of automatic image annotation. Both techniques were applied in the prototypicaltag recommender “tagr”.
2009

Granitzer Michael, Rath Andreas S., Kröll Mark, Ipsmiller D., Devaurs Didier, Weber Nicolas, Lindstaedt Stefanie , Seifert C.

Machine Learning based Work Task Classification

Journal of Digital Information Management, 2009

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Increasing the productivity of a knowledgeworker via intelligent applications requires the identification ofa user’s current work task, i.e. the current work context a userresides in. In this work we present and evaluate machine learningbased work task detection methods. By viewing a work taskas sequence of digital interaction patterns of mouse clicks andkey strokes, we present (i) a methodology for recording thoseuser interactions and (ii) an in-depth analysis of supervised classificationmodels for classifying work tasks in two different scenarios:a task centric scenario and a user centric scenario. Weanalyze different supervised classification models, feature typesand feature selection methods on a laboratory as well as a realworld data set. Results show satisfiable accuracy and high useracceptance by using relatively simple types of features.
2009

Lindstaedt Stefanie , Hambach S., Müsebeck P., de Hoog R., Kooken J., Musielak M.

Context and Scripts: Supporting Interactive Work-Integrated Learning

Computer Supported Collaboration Learning Practices, CSCL09, 8-13 June 2009, Rhodes, Greece, Dimitracopoulou A., O’Malley, C., Suthers D., Reimann P. , 2009

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Computational support for work-integrated learning will gain more and moreattention. We understand informal self-directed work-integrated learning of knowledgeworkers as a by-product of their knowledge work activities and propose a conceptual as wellas a technical approach for supporting learning from documents and learning in interactionwith fellow knowledge workers. The paper focuses on contextualization and scripting as twomeans to specifically address the latter interaction type.
2008

Ley Tobias, Ulbrich Armin, Scheir Peter, Lindstaedt Stefanie , Kump Barbara, Albert D.

Modelling Competencies for Supporting Work-integrated Learning in Knowledge Work

Journal of Knowledge Management, , 2008

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2008

Ley Tobias, Ulbrich Armin, Lindstaedt Stefanie , Scheir Peter, Kump Barbara, Albert Dietrich

Modeling competencies for supporting work-integrated learning in knowledge work

Journal of knowledge management, Emerald Group Publishing Limited, 2008

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Purpose – The purpose of this paper is to suggest a way to support work-integrated learning forknowledge work, which poses a great challenge for current research and practice.Design/methodology/approach – The authors first suggest a workplace learning context model, whichhas been derived by analyzing knowledge work and the knowledge sources used by knowledgeworkers. The authors then focus on the part of the context that specifies competencies by applying thecompetence performance approach, a formal framework developed in cognitive psychology. From theformal framework, a methodology is then derived of how to model competence and performance in theworkplace. The methodology is tested in a case study for the learning domain of requirementsengineering.Findings – The Workplace Learning Context Model specifies an integrative view on knowledge workers’work environment by connecting learning, work and knowledge spaces. The competence performanceapproach suggests that human competencies be formalized with a strong connection to workplaceperformance (i.e. the tasks performed by the knowledge worker). As a result, competency diagnosisand competency gap analysis can be embedded into the normal working tasks and learninginterventions can be offered accordingly. The results of the case study indicate that experts weregenerally in moderate to high agreement when assigning competencies to tasks.Research limitations/implications – The model needs to be evaluated with regard to the learningoutcomes in order to test whether the learning interventions offered benefit the user. Also, the validityand efficiency of competency diagnosis need to be compared to other standard practices incompetency management.Practical implications – Use of competence performance structures within organizational settings hasthe potential to more closely relate the diagnosis of competency needs to actual work tasks, and toembed it into work processes.Originality/value – The paper connects the latest research in cognitive psychology and in thebehavioural sciences with a formal approach that makes it appropriate for integration intotechnology-enhanced learning environments.Keywords Competences, Learning, Workplace learning, Knowledge managementPaper type Research paper
2008

Lindstaedt Stefanie , Ley Tobias, Scheir Peter, Ulbrich Armin

Applying Scruffy Methods to Enable Work-integrated Learning

The European Journal of the Informatics Professional, 2008

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This contribution introduces the concept of work-integrated learning which distinguishes itself from traditional e-Learning in that it provides learning support (i) during work task execution and tightly contextualized to the work context,(ii) within the work environment, and (iii) utilizes knowledge artefacts available within the organizational memory for learning. We argue that in order to achieve this highly flexible learning support we need to turn to" scruffy" methods (such as associative retrieval, genetic algorithms, Bayesian and other probabilistic methods) which can provide good results in the presence of uncertainty and the absence of fine-granular models. Hybrid approaches to user context determination, user profile management, and learning material identification are discussed and first results are reported.
2008

Lindstaedt Stefanie , Ley Tobias, Scheir Peter, Ulbrich Armin

Aplicación de métodos "desaliñados" para facilitar el aprendizaje integrado en el trabajo

Novatica, Revista de la Asociación de Téchnicos de Informática, N° 193, mayo-junio 2008, ano XXXIV, ATI, 2008

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2008

Scheir Peter, Lindstaedt Stefanie , Ghidini C.

A Network Model Approach to Retrieval in the Semantic Web

International Journal on Semantic Web and Information Systems, Sheth, A., IGI Global, 2008

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2007

Strohmaier M., Lindstaedt Stefanie

Rapid Knowledge Work Visualization for Organizations

Journal of Knowledge Management, Emerald Group Publishing Limited, 2007

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Purpose: The purpose of this contribution is to motivate a new, rapid approachto modeling knowledge work in organizational settings and to introducea software tool that demonstrates the viability of the envisioned concept.Approach: Based on existing modeling structures, the KnowFlowr Toolsetthat aids knowledge analysts in rapidly conducting interviews and in conductingmulti-perspective analysis of organizational knowledge work is introduced.Findings: It is demonstrated how rapid knowledge work visualization can beconducted largely without human modelers by developing an interview structurethat allows for self-service interviews. Two application scenarios illustrate thepressing need for and the potentials of rapid knowledge work visualizations inorganizational settings.Research Implications: The efforts necessary for traditional modeling approachesin the area of knowledge management are often prohibitive. Thiscontribution argues that future research needs to take economical constraintsof organizational settings into account in order to be able to realize the fullpotential of knowledge work management.Practical Implications: This work picks up a problem identified in practiceand proposes the novel concept of rapid knowledge work visualization for makingknowledge work modeling in organizations more feasible.Value: This work develops a vision of rapid knowledge work visualization andintroduces a tool-supported approach that addresses some of the identified challenges.
2007

Kröll Mark, Rath Andreas S., Weber Nicolas, Lindstaedt Stefanie , Granitzer Michael

Task Instance Classification via Graph Kernels

Mining and Learning with Graphs (MLG 07), Florenz, Italy, August 1-3, 2007, 2007

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2007

Thurner-Scheuerer Claudia, Lindstaedt Stefanie

Die PWM ist ein Raum für Interaktion, Inhalte und Lösungen

GfWM-Newsletter, GfWM, Frankfurt am Main (Deutschland), 2007

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2006

Birk Andreas, Dingsøyr Torgeir, Lindstaedt Stefanie , Schneider Kurt

Learning Software Organisations and Requirements Engineering: First International Workshop

Journal of universal knowledge management, 2006

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Requirements engineering has grown into a focus topic for most software-dependentcompanies. Both outsourcing and in-house development call for effective elicitation ofrequirements, and for rich communication between customers and software developers.Organizational learning is, therefore, a natural complement when we discuss requirementsengineering practice and its improvement. Through organizational learning, processes and toolsare systematically improved, reflection and explicit learning becomes part of the companyculture. Many companies are still struggling to reach this goal.The LSO+RE workshop has provided a forum for discussing the intersection of requirementsengineering and learning software organizations in depth. This article introduces the topic andthe articles from the LSO+RE workshop that have been selected for this special issue ofJ.UKM.
2005

Lindstaedt Stefanie , Farmer Johannes

Integration of Knowledge Management and (e) Learning J. UCS Special Issue

Journal of Universal Computer Science, 2005

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2005

Timbrell G., Koller S., Schefe N., Lindstaedt Stefanie

A Knowledge Infrastructure Hierarchy Model for Call-Centre Processes

Journal of Universal Computer Science, 2005

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This paper explores a process view of call-centres and the knowledge infrastructuresthat support these processes. As call-centres grow and become more complex in their functionand organisation so do the knowledge infrastructures required to support their size andcomplexity. This study suggests a knowledge-based hierarchy of ‘advice-type’ call-centres anddiscusses associated knowledge management strategies for different sized centres. It introducesa Knowledge Infrastructure Hierarchy model, with which it is possible to analyze and classifycall-centre knowledge infrastructures. The model also demonstrates different types ofinterventions supporting knowledge management in call-centres. Finally the paper discusses thepossibilities of applying traditional maturity model approaches in this context.
2005

Tochtermann K., Lindstaedt Stefanie

Wissensinfrastrukturen - Die optimale Unterstützung Ihrer Geschäftsprozesses

wissensmanagement - Das Magazin für Führungskräfte, 2005

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2005

Lindstaedt Stefanie , Strohmaier M.

Special Issue on 'Knowledge Infrastructures for the Support of Knowledge Intensive Business Processes'

Journal of Universal Knowledge Management, Graz, Austria, 2005

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2005

Lindstaedt Stefanie , Strohmaier M.

Integrating Business Processes and Knowledge Infrastructures

Journal of Universal Computer Science, 2005

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The integration of available knowledge management technologies, concepts andmethods into organizational business processes is a pressing and challenging researchissue today. Researches and practitioners in the areas of process and knowledgemanagement alike seek for solutions that aid the flexible alignment of knowledgemanagement efforts to an organization’s most value generating activities. Theadvantages inherent in such efforts are manifold: The execution of business processesis supported from a knowledge perspective, the economic benefit of knowledgemanagement can be illustrated more easily and knowledge management activitiesbecome “alive” because of the integration in organizational business processes -which in turn thrives business performance.The special issue “Integrating Business Processes and KnowledgeInfrastructures” makes more detailed versions of the contributions to BPOKI’04available. BPOKI’04 is a special track series on Business Process OrientedKnowledge Infrastructures that took place the first time during I-Know’04, the 4thInternational Conference on Knowledge Management (http://www.iknow.at/BPOKI).The purpose of this special issue is to provide readers with an overview of up-todateresearch on the intersection between business process and knowledgemanagement. Contributions of this special issue consider both, organizational as wellas technological aspects of this topic, and fall in one of the following four categories:1) Business Process Modelling 2) Business Process Learning 3) Business ProcessSupport and 4) Business Process Execution.
2004

Lindstaedt Stefanie , Farmer J.

Kooperatives Lernen in Organisationen

CSCL-Kompendium - Lehr- und Handbuch für das computerunterstützte kooperative Lernen', Haake, J., Schwabe, G., Wessner, M., Oldenbourg Wissenschaftsverlag, München,Germany, 2004

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2004

Lindstaedt Stefanie

Special Issue on ‘(Virtual) Communities of Practice within Modern Organizations’

Journal of Universal Computer Science, Verlag der Technischen Universität Graz, 2004

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2002

Lindstaedt Stefanie , Scheir Peter, Sarka W.

Generic Knowledge Management System (GKMS)

TELEMATIK 03/2002, Telematik Ingenieur Verband, Graz, Austria, 2002

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2002

Lindstaedt Stefanie

Integration von Arbeits- und Lernprozessen

Fachtagung der Senatsverwaltung für Wirtschaft, Arbeit und Frauen, Berlin, am 21./22. November 2002, BBJ-Verlag, Berlin, Germany, 2002

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2001

Lindstaedt Stefanie

Web Globalization: Vision, Strategie

www.ContentManager.de, 2001

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