Abstract Leveraging previously untapped data sources offers significant potential for value creation in the manufacturing sector. However, asset-heavy shop floors, extended machine replacement cycles, and equipment diversity necessitate considerable investments for achieving smart manufacturing, which can be particularly challenging for small businesses. Retrofitting presents a viable solution, enabling the integration of low-cost sensors and microcontrollers with older machines to collect and transmit data. In this paper, we introduce a concept and a prototype for retrofitting industrial environments using lightweight web technologies at the edge. Our approach employs WebAssembly as a novel bytecode standard, facilitating a consistent development environment from the cloud to the edge by operating on both browsers and bare-metal hardware. By attaining near-native performance and modularity reminiscent of container-based service architectures, we demonstrate the feasibility of our approach. Our prototype was evaluated with an actual industrial robot within a showcase factory, including measurements of data exchange with a cutting-edge data lake system. We further extended the prototype to incorporate a peer-to-peer network that facilitates message routing and WebAssembly software updates. Our technology establishes a foundational framework for the transition towards Industry 4.0. By integrating considerations of sustainability and human factors, it further extends this groundwork to facilitate progression into Industry 5.0.

The fast-growing complexity of decentralized infrastructures outpaces end-users from acquiring the required knowledge to operate them. A possible remedy for this ever-aggravating problem might be the integration of natural-language-driven interfaces that allow end-users to interact with those systems. This work focuses on a Distributed Analytics (DA) use case, which includes the challenge above. We propose a DA-tailored and module-based monitoring and transaction bot called HAICO, which assists users in keeping track of their activities. Our user study (n=50) shows that our approach indeed contributes to increased transparency and accessibility of digital assets in these ecosystems. The results show that integrating automated agents can lower the barriers for non-technology-versed users to foster efficiency and adoption time.

Curricula at university and learning paths in self-regulated learning span a complex planning space that is difficult to visualize. Students need to plan their decisions ahead to take a valid order of courses that align with their learning goals. Previous approaches used 2D skill tree visualizations to map the dependencies which, however, cannot convey mixtures of long-term goals and short-term action plans well. We present an approach that realizes learning plans as 3D skill tree structures in mixed reality. With the extra dimension, clearer layouts can be found which combine views on long-term goals and specific actions. By bringing the 3D learning plans to mixed reality, depth perception can help the students to understand the 3D structure of the tree. Moreover, nodes of the tree can be anchored at places in the real world which aids the students’ spatial memory to help them remember the plan. The application is evaluated in two user studies with 17 and 53 participants, respectively. Although the amount of text and typing should be minimized, the results show that 3D learning plans are understood by students. As the hardware becomes more available, the 3D learning plans can help students to structure their studies.

The advancements of mixed reality technologies enable a productive application of mixed reality in various fields. This increases the demand for skilled mixed reality developers. Current curricula do not offer dedicated mixed reality courses in higher education that provide the necessary competences. We demonstrate a lab course for mixed reality software engineering in a bachelor program at a technical university with its learning goals and the identified skills to support future mixed reality computer scientists. The course was conducted five times over two and a half years with a total of 38 students. In all instances, the same open-source software project was used as a boundary object to train agile software engineering, mixed reality development competences, and presentation skills. As the course teaches state-of-the-art agile workflows, its aim is to prepare students for scientific projects, a bachelor thesis and industry training scenarios in mixed reality.

With recent developments in information technology, we can realize learning experiences on the Web and in mixed reality. Many disciplines have profited from this, e.g. anatomy with the possibility to learn with 3D models in both environments. However, designing authoring workflows and learning paths can be different in these environments as the transfer of design ideas can affect the quality of the learning experiences. In this paper, we juxtapose a Web application and a mixed reality application of the same anatomy course. We highlight where differences need to be considered and which modules can be used in both environments, e.g. authentication and gamification. With the practical knowledge presented here, the design of learning experiences on the Web and in mixed reality can be enhanced. To support this, all code is available as open-source software on GitHub.

This paper outlines the objectives of the working group on developing a model Augmented Reality curriculum for higher education. We motivate the need for the model curriculum by the growing Augmented Reality industry and subsequent demand for trained professionals. While the industry is growing, the educational offers that train the required skills remain limited and fragmented. The working group will address this challenge by surveying the state of the art in Augmented Reality education are reviewing available data on industry requirements. Based on the results, the group will develop a new model Augmented Reality curriculum. The working group will also develop future work recommendations for the design of teaching materials and integration of Augmented Reality in computing curricula.

Abstract Today’s Model-Driven Web Engineering (MDWE) approaches automatically generate Web applications from conceptual, domain-specific models. This enhances productivity by simplifying the design process through a higher degree of abstraction. Due to this raised level of abstraction, the collaboration on conceptual models also opens up new use cases, such as the tighter involvement of non-technical stakeholders into Web development. However, especially in the early design stages of Web applications, common practices for requirement elicitation mostly rely on wireframes instead of MDWE, created usually in analog settings. Additionally, state-of-the-art MDWE should integrate established and emerging Web development features, such as Near Real-Time (NRT) collaborative modeling and shared editing on the generated code. The combination of collaborative modeling, coding and wireframing, all in NRT, bears a lot of potential for improving MDWE practices. The challenge when covering these requirements lies with synchronizing source code, wireframes and models, an essential need to cope with regular changes in the software architecture to provide the flexibility needed for agile MDWE. In this contribution, we present a MDWE approach with live code editing and wireframing capabilities. We present the conceptual considerations of our approach, the realization of it and the integration into an overarching development methodology. Following a design science approach, we present the cyclic iterations of developing and evaluating our artifacts, which show promising results for collaborative Web development tasks that could open the gate towards novel, collaborative and agile MDWE techniques.

Multimedia platforms dealing with movie streaming and video-based short messages have increased the global Internet video traffic substantially in the last couple of years.Over the same period, multimedia on the Web has been standardized in terms of codecs and browserbased JavaScript APIs.However, today the technological challenges concerning the distribution of large video files are mainly tackled by scaling up capacities in cloud data centers, or relying on content delivery networks.Both approaches favor financially strong, large companies, while independent video providers with highly demanded videos are disadvantaged.Peer-to-peer streaming provides an alternative by shifting the data streams to the clients.In this article, we conceptualize different methods to move video delivery from centralized cloud infrastructures to end user devices.We discuss their strengths & weaknesses and present design considerations.To exemplify a particular approach, we showcase the implementation and evaluation of OakStreaming, our system that streams videos peer-to-peer via WebTorrent in HTML5.

Peer reviewed

Near real-time collaboration using Web browsers is becoming rapidly more and more popular for many applications such as text editing, coding, sketching and others. These applications require reliable algorithms to ensure consistency among the participating Web clients. Operational Transformation (OT) and more recently Commutative Replicated Data Types (CRDT) have become widely adopted solutions for this kind of problem. However, most existing approaches are non-trivial and require trade-offs between expressiveness, suitable infrastructure, performance and simplicity. The ever growing number of potential use cases, the new possibilities of cutting-edge messaging protocols that shaped the near real-time Web, and the use of N-way communication between clients (e.g. WebRTC), create a need for peer-to-peer algorithms that perform well and are not restricted to only a few supported data types. In this paper, we present YATA, an approach for peer-to-peer shared editing applications that ensures convergence, preserves user intentions, allows offline editing and can be utilized for arbitrary data types in the Web browser. Using Yjs, its open-source JavaScript library implementation, we have evaluated the performance and multiple usage of YATA in Web and mobile browsers, both on test and real-world data. The promising evaluation results as well as the uptake by many commercial vendors and open-source projects indicate a wide applicability of YATA.

Recognizing the need for addressing the rather fragmented character of research in this field, we have held a workshop on learning analytics for workplace and professional learning at the Learning Analytics and Knowledge (LAK) Conference. The workshop has taken a broad perspective, encompassing approaches from a number of previous traditions, such as adaptive learning, professional online communities, workplace learning and performance analytics. Being co-located with the LAK conference has provided an ideal venue for addressing common challenges and for benefiting from the strong research on learning analytics in other sectors that LAK has established. Learning Analytics for Workplace and Professional Learning is now on the research agenda of several ongoing EU projects, and therefore a number of follow-up activities are planned for strengthening integration in this emerging field.

In this paper, we propose a new two-phase approach for finding overlapping communities in signed social networks. Moreover, we evaluate the importance of three node classes: extra, overlapping and intra. Results indicate that the overlapping nodes can competitively predict signs in comparison to intra and extra nodes. Finally, we propose extended frustration as a measure to evaluate errors for fuzzy community detection algorithms in signed social networks.

In very recent years, the advent of Learning Analytics (LA) has resulted in a number of publications reporting on empirical research. This literature overview identifies the mainstream of empirical LA research, and emphasizes insufficiently investigated directions that display a higher innovation potential. The mainstream consists of learning trajectory visualizations aimed to predict learner success. Single studies prove innovative by addressing in particular: informal educational settings, video and audio records as data sources, automated assessment and error/misconception analysis. A central issue of empirical LA research consists of the frequent lack of an explicit theoretical framework from educational perspective. We maintain that educational and psychological theories are urgently needed for significant progress of upcoming LA research.

The aim to support learning communities by Web 2.0 technology leads to their investigation through the prism of learning theories. However, self-observation and self-modeling requires appropriate tools and skills. In this paper we focus on users of a forum platform and propose several tools that perform community detection, social network analysis, text mining, natural language processing, and clustering. The outcomes serve as inputs for community models that are automatically established using the i * information modeling approach. Stakeholders can recognize issues in their communities by visual analytics of the models. Based on this, they can refine community learning processes and community environments by retrieving new community requirements from the models. The process of model establishment was evaluated by experts in i * information modeling and the results show their acceptance of the proposed techniques. This solution enables also support of various well-known modeling approaches (like IMS Learning Design).

Collaborative research projects involve distributed construction of software prototypes as part of the project methodology. A major challenge thereby is the need to establish a developer community that shall effectively and efficiently align development efforts with requirements offered by researchers and other stakeholders. These projects are inherently different in nature compared to commercial software projects. The literature offers little research on this aspect of software engineering. In this paper, we outline the challenges in this context and present a methodology for distributed software engineering in collaborative research projects. The methodology covers all major aspects of the software engineering process including requirements engineering, architecture, issue tracking, and social aspects of developer community building in collaborative projects. The methodology can be tailored to different project contexts and may provide support in planning software engineering work in future projects.

Topic modeling is a machine learning technique that identifies latent topics in a text corpus. There are several existing tools that allow end-users to create and explore topic models using graphical user interfaces. In this paper, we present a visual analytics system for dynamic topic models that goes beyond the existing breed of tools. First, it decouples the Web-based user interface from the underlying data sets, enabling exploration of arbitrary text data sets in the Web browser. Second, it allows users to explore dynamic topic models, while existing tools are often limited to static topic models. Finally, it comes with a tool server in the backend that allows the design and execution of scientific workflows to build topic models from any data source. The system is demonstrated by building and exploring a dynamic topic model of CIKM proceedings published since 2001.

There are many mobile apps supporting informal learning tasks like sense-making out of multimedia materials. However, regardless how well these have been implemented, their scope and scalability is limited either by over-specialization and consequently limited transferability or by over-generalization - with a lack of informal learning support for most Web 2.0 apps. Our cloud-based mobile Web information system approach is theoretically founded and designed for scalability in informal learning. As a proof of concept we present a semantic video annotation scenario for supporting informal learning at workplace. As the approach has been designed for community learning analytics, we can present results from a preliminary evaluation. We conducted our research with a strong commitment towards open source software development, so that our solutions are already available and can have impact beyond the usual scope of a funded project.

Streaming video has recently surpassed peer-to-peer networks in terms of network capacity hunger.Reports estimate a share of 40 % of peak network capacity dedicated to entertainment, mostly streaming video.A large share of this traffic originates from web-based services.YouTube alone takes up to 8 % of the prime time Internet traffic.While transmission currently works in a best effort system, multimedia information systems on the web are far from being perfect.Retrieval, annotation, validated and useful metadata, reliable and trusted services, and user interaction and context-based adaptation are still under discussion and issues to research.Currently, the Web itself faces dramatic changes, looking for example at the spread of social networks, like Facebook, Twitter or the YouTube community, which become part of everyday life of more and more people.Technologies like Linked Data, HTML5, WebM, or WebRTC are enablers that make these changes possible and let people experience the Web without knowing details about technology.Also the availability of the Web has changed a lot.Many people create multimedia data on the go, put videos and photos on microblogs, or share audiovisual data with their loved ones or colleagues.These activities also have a deep effect on multimedia data formats and usage, multimedia systems and multimedia service providers."Multimedia everywhere" was a common concept before, but this has changed to "relevant media at your finger tips", so new methods for finding, annotating, sharing, remixing, summarizing, transmitting, storing and consuming multimedia data have to be found.

Together with the current shift to cloud-based solutions, various Web applications have been enriched with collaborative features. These collaborative features enable users to work together on digital products like documents, diagrams and videos at the same time on a global scale. Implementing them

Collaboration on digital products---for instance in science, design or production---is typically being practiced using cumbersome means like sending document drafts back and forth among collaborators. Recent advances in Web technologies allow collaborators to synchronously edit artifacts. From an en

Current learning services are increasingly based on standard Web technologies and concepts. As by-product of service operation, Web logs capture and contextualize user interactions in a generic manner, in high detail, and on a massive scale. At the same time, we face inventions of data standards for capturing and encoding learner interactions tailored to learning analytics purposes. However, such standards are often focused on institutional and management perspectives or biased by their intended use. In this paper, we argue for Web logs as valuable data sources for learning analytics on all levels of Bronfenbrenner's Ecological System Theory and introduce a simple framework for Web log data enrichment, processing and further analysis. Based on an example data set from a management service for widget-based Personal Learning Environments, we illustrate our approach and discuss the applicability of different analysis techniques along with their particular benefits for learners.

The innovation potential of niche communities often remains inaccessible to service providers due to a lack of awareness and effective negotiation between these two groups. Requirements Bazaar, a browser-based social software for Social Requirements Engineering (SRE), aims at bringing together communities and service providers into such a negotiation process. Communities should be supported to express and trace their requirements and eventually receive a realization. Service providers should be supported in discovering relevant innovative requirements to maximize impact with a realization. In this paper we present Requirements Bazaar with focus on four aspects: requirements specification, a workflow for co-creation, workspace integration and personalizable requirements prioritization.

The plethora of talks and presentations taking place at academic conferences makes it difficult, especially for young researchers to attend the right talks or discuss with participants and potential collaborators with similar interests. Participants may not have a priori knowledge that allows them to select the right talks or informal interactions with other participants. In this paper we present the context-aware mobile recommendation services (CAMRS) based on the current context (whereabouts at the venue, popularity and activities of talks and presentations) sensed at the conference venue. Additionally, we augment the current context with the academic community context of conference participants which is inferred by using social network analysis and link prediction on large-scale co-authorship and citation networks of participants. By combining the dynamic and social context of participants, we are able to recommend talks and people that may be interesting to a particular participant. We evaluated CAMRS using data from two large digital libraries - the DBLP and CiteSeerX, and participants from two conferences - ICWL 2010 and EC-TEL 2011. The result shows that the new approach can recommend novel talks and helps participants in establishing new connections at conference venue.

Mobile Augmented Reality (MAR) enables overlays of semantically-enriched multimedia on video streams of smart phone cameras. These new ways to interact with digital objects via position and 3D movement can be helpful for on-site professional communities. However, current MAR applications lack real-t

Nowadays, many online communities provide means for users to contribute in the evaluation of community created media by tagging, commenting and rating. Judging the users expertise in such collaborative systems is an important issue. As these systems are becoming increasingly popular, they are a

The European Commission (EC) has spent hundreds of millions of euros on collaborative Technology Enhanced Learning (TEL) projects in recent years. Consequently the EC is interested in the impact generated by those projects. Spawning sustained collaboration ties can be interpreted as one aspect of project impact. In this paper we present a novel way of analyzing this latent impact of TEL projects by applying social network analysis on the projects' collaboration structures. Our analysis includes TEL projects funded under FP6, FP7 and eContentplus, and identifies central projects and strong, sustained organizational collaboration ties.

In this paper we attempt to address the issue of supporting self-regulation by Personal Learning Environments (PLE), which provide the learner with a freedom to design and compose his or her learning environment according to personal preferences and context demands. Psychology and neuroscience offer a lot of highly relevant results that should be taken into account. We report on our experiments mainly with PhD students, which represent a community of advanced learners. This needs to be considered when interpreting their feedback, as for most of the learners is self-regulation even more challenging. Even students at this high level appreciate pedagogical support in the learning process.

This paper reports on the development of WeBuild, a mobile learning game designed to engage learners difficult to reach with IT learning. The development is based on a mobile game engine for the Android smart phone that was devised to support the required multiplayer and location based services. We played and tested the mobile learning game in a training facility of the building industry. The results indicate that the learners accepted the game for the low entry barriers and were motivated to use the game in an educational context. This paper describes the WeBuild prototype and the underlying game engine. Eventually, it presents results from the game session that was carried to assess interface and gameplay usability, technical functionality and motivational aspects of the game design.

The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS) middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also reach transparently remote computing resources. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve complicated algorithms and large computations, can benefit from offloading with around 95% energy savings and significant performance gains compared to local execution only.

Psycho-pedagogical theories have a high impact on learning. Our aim is to analyze results of behavioral and cognitive psychology to help designers of learning experiences with specification of requirements. We have reviewed literature on human decision making processes, organized a survey and a workshop with PhD students to collect various opinions on these issues, and here we summarize the outcomes.

When Internet users search for information, surf on websites or discuss with others, their actions are driven by certain goals. Extraction of users' goals can enable higher effectiveness and accuracy of web services. Supporting users in based on their goals can be highly beneficial, especially supporting of learners in the preparation for an exam as a learning process, Different phases of learning are identified when users learn collaboratively. We scrutinize how goals are constructed and achieved within a community, examining not only social activities based on patterns of behavior, but also emotions and intents users express in their posts. As a result we elicit users' goals. We achieved good accuracy in defining emotions of users and recognizing their intents and social patterns in our case. Here we discuss how the obtained results contribute to mining of learning community goals.

This paper describes an experiment investigating interactions in a big forum in order to support students in learning English. Groups of collaborating users form communities that generate a lot of data that can be analyzed. We distinguish different phases of the self-regulated learning process and aim to identify them in learners' activities. Then we attempt to recognize patterns of their behavior and consequently their roles in a community. Based on this analysis we try to explain a success or failure of a community. We conclude that heterogeneity of members helps a learning community to function.

How is our knowledge organized? What research fields in computer science do exist? How are they interconnected? Previous work on knowledge mapping focused on building the map of all of sciences or a particular domain based on ISI published JCR (Journal Citation Report) dataset. Although this dataset covers most of important journals, it lacks of computer science conference and workshop proceedings. That results in an imprecise and incomplete analysis on the map of computer science knowledge. This paper presents an analysis on the computer science knowledge network with the aims to understand its structure and to answer the above questions. Based on the combination of two important digital libraries for computer science (DBLP and CiteSeerX), the knowledge networks are created at venue (journals, conferences and workshops) level and social network analysis is applied to determine clusters of similar venues, interdisciplinary venues and high prestige venues.

Storytelling is a natural and effective approach to human communication. The enrichment of stories using multimedia technologies has been established in knowledge sharing for professional communities since long ago. However, mobile multimedia production and consumption for storytelling raises several issues for mobile data management. We start with a requirements analysis for various application scenarios ranging from business to common life with mobile multimedia storytelling. A mobile multimedia data management model is proposed based on the presented scenarios. A test bed for the measurement of mobile multimedia community information system success is briefly described for the evaluation of our approach.

With the advent of mobile smart phones, new types of virtual communities arrived, i.e. mobile communities. Mobile communities, with respect to their IT needs, introduce new requirements compared to traditional online web communities. On the other hand, cloud computing is emerging as computing concept that promises provision of computational resources on demand and abstraction of technical details from the clients. We propose Mobile Community Cloud Platform (MCCP) as a cloud computing system that can leverage the full potential of mobile community growth. An analysis of the core requirements of common mobile communities is provided before we present the design of our cloud computing architecture that supports building and evolving of mobile communities.

Advances in mobile communication technologies lead to a coalescence of location-based, multimedia services for user communities. However, easy development and maintenance of device-independent mobile services are still challenging. We have developed a service-oriented framework for mobile multimedia processing based on international standards like MPEG-7. Quality of mobile service experience is constantly monitored in framework. The scenario “Virtual Campfire” is used in the German excellence cluster UMIC (Ultra High-Speed Information and Communication) to demonstrate future mobile social software with real-time multimedia processing, semantic enrichment of multimedia materials by user communities and complex collaboration over the mobile we like storytelling on different mobile devices. Adaptive Web access, service calls and service monitoring are to be demonstrated as the prototype, which offers approaches to meeting the aforementioned challenges.

Multimedia information systems have been developed into service-ware. With the paradigms of web services, service oriented architectures (SOA), and Web 2.0 widgets, multimedia has become truly ubiquitous. However, interoperability, scalability, reliability and security are arising challenges at mobile multimedia service development. This paper focuses on the analysis, design, development and evaluation of a middleware that allows access from mobile devices to a bundle of multimedia services. The services are based on the international multimedia metadata description standard MPEG-7. The implementation is based on new generation of service-oriented application servers called Lightweight Application Server (LAS). Mobile web services refer to the fact that mobile servers host web services. A prototype was developed as a proof of concept, showing how to access MPEG-7 based multimedia services from a Mobile Host and the analysis results of providing MPEG-7 based multimedia services in the form of web services from the Mobile Host to other mobile devices. An alternative solution is to apply enterprise service bus technology as the middleware. The performance evaluation results of both approaches show the reliable accessibility of MPEG-7 based multimedia services via the enterprise service bus solution.

Nowadays various mobile platforms from PDA, smart phones to iPhones can deliver road warriors or trippers much mobile information. However, most mobile applications are lacking the "social intelligence" of real companionship. One reason is that community context and spatiotemporal context information are not well taken into consideration. In this paper we propose an ontology-based context model using OWL/RDF. With the enhanced interoperability substantial context information can be expressed and reasoned across systems. Based on the context model and the middleware Context-Aware Adaptation Service (CAAS), we introduce a mobile tourist guide as proof- of-concept that provides users context-aware information. We employ the MPEG-7 and MPEG-21 metadata standards to realize multimedia adaptation to device preferences. The evaluation result proves the feasibility of the context model and shows the easy extensibility of CAAS.

Nonaka and his knowledge transformation model SECI revolutionized the thinking about organizations as social learning systems. He introduced technical concepts like hypertext into organizational theory. Now, after 15 years Web 2.0 concepts seem to be an ideal fit with Nonaka's SECI approach opening new doors for more personal, dynamic, and social learning on a global scale. In this paper, we present an extended view of blended learning which includes the combination of formal and informal learning, knowledge management, and Web 2.0 concepts into one integrated solution, by discussing what we call the Web 2.0 driven SECI model based learning process.

The present paper presents a longitudinal study of the course ‘High-tech Entrepreneurship and New Media’. The course design is based on socio-cultural theories of learning and considers the role of social capital in entrepreneurial networks. By integrating student teams into the communities of practice of local start-ups, we offer learning opportunities to students, companies and academia. The student teams are connected to each other and to their supervisors in academia and practice through a community-system. Moreover, the course is accompanied by a series of lectures and group discussions. In this paper we want to present our experiences and to reflect upon the design changes between the first and the second instance of the course. The evaluation of the course showed that the work on real-world problems and the collaboration in teams together with partners from start-up companies were evaluated as very positive, although design flaws, and cultural and professional diversities limited the success of the first instance in 2001. For the second course in 2002, the didactical design was improved significantly according to evaluation results, which brought evidence that the design changes resulted in better collaborative practices and more stable relationships between start-up companies and students. Furthermore, it was found that especially the differences in cultural background and different historical experiences between the two distinct groups of ‘students’ and ‘entrepreneurs’ might make processes of social identification more difficult and, therefore, successful community-building less likely’.

User-driven annotation of learning content allows the user to interact with it in a flexible and an intuitive manner and hence personalize the content. This interaction, in most cases, follows the "paper and pen" note-taking paradigm. Though not without its advantages, this paradigm does not scale when the courses are delivered online as web pages. These paper notes are not synchronous with the content, hence may seem out of context, they may be misplaced, and don’t make allowances for collaborative learning. In this paper we describe u-Annotate, a user-driven freeform digital ink annotation application for web e- Learning content which aims at facilitating the learner to annotate the online content with the aid of pen computing devices such as graphic tablets, etc. Learners can freely mark up the content, save the annotations for recall at a later date, as well as share these with other learners.

Social software is used widely in organizational knowledge management and professional learning. The PROLEARN network of excellence appreciates the trend of lowering the barriers between knowledge and learning management strategies for organizations and individuals. But, companies should not underestimate the needs for systematic support based on sound theories and technologies. We illustrate the requirements by examples and research issues for collaborative adaptive learning platforms for workplace learning in organizations

Our shared belief is that learning, like other human activities, cannot and is not confined within rigidly defined course systems or learning repositories, inclosing learning resources which cannot be tailored to the different learner's needs, skills, interests, preferences, goals, etc. Therefore, a learning environment, besides supporting communication between knowledge providers and consumers, has to be organized in a flexible manner based on different learner profiles. Learner modeling has become a highly challenging task to provide personalized, adaptive and context-based learning. The work presented in this paper addresses this issue by providing a meta-level solution for the description, transformation and matching of learner models, based on standards such as IMS LIP, IEEE PAPI, XML to foster the reuse and exchange of learner models between learning platforms, both by universities and corporations.

Intergenerational learning is based on processing experiences from one generation to another. However, this process is up to now mostly based on face to face communication neglecting the capabilities of computer supported learning communities. In this paper we describe ACIS (Afghan Community IS), a system that has been designed to support intergenerational learning communities by geographical hypermedia information systems in the area of cultural heritage. ACIS is designed to bring together generations of scientists in cultural heritage management which has been disrupted by the civil war and the Taliban regime in Afghanistan. ACIS has been deployed for a project in the conservation of cultural heritage in Afghanistan to prove the validity of the concepts.

Knowledge-based hypermedia systems are used in scholarly communication since more than 2000 years, e.g. the Babylonian Talmud. Many different computer-based hypermedia systems have been successfully created for the humanities, too. But, cross-university or even university-wide use of these systems for e-learning purposes in the humanities is seldom if ever. In this paper, we argue, that only a deep analysis of hypermedia usage in scholarly communication and teaching can disclose non-trivial technical and community-aware requirements for open e-learning systems in the humanities. With these requirements we analyze some of the existing solutions and provide a case study for a cross-university hypermedia e-learning system called MECCA.

We present experiences made with a course in applied computer science which was based on the concept of communities of practice. Within the scope of the course "entrepreneurship and new media" we offered a project lab which was accompanied by a set of lectures given by internal and external lecturers. In the project groups, the students worked in close cooperation with start-up companies. The students were connected through a community system to each other and to their supervisors in academia and practice. As the communities of practice emerged we discuss the role they may play in teaching.

Research in process-centered environments (PCEs) has focused on project management support and has neglected method guidance for the engineers performing the (software) engineering process. It has been dominated by the search for suitable process-modeling languages and enactment mechanisms. The consequences of process orientation on the computer-based engineering environments, i.e., the interactive tools used during process performance, have been studied much less. In this article, we present the PRIME (Process Integrated Modeling Environments) framework which empowers method guidance through process-integrated tools. In contrast to the tools of PCEs, the process-integrated tools of PRIME adjust their behavior according to the current process situation and the method definitions. Process integration of PRIME tools is achieved through (1) the definition of tool models; (2) the integration of the tool models and the method definitions; (3) the interpretation of the integrated environment model by the tools, the process-aware control integration mechanism, and the enactment mechanism; and (4) the synchronization of the tools and the enactment mechanism based on a comprehensive interaction protocol. We sketch the implementation of PRIME as a reusable implementation framework which facilitates the realization of process-integrated tools as well as the process integration of external tools. We define a six-step procedure for building a PRIME-based process-integrated environment (PIE) and illustrate how PRIME facilitates change integration on an easy-to-adapt modeling level.