WISKIDZ - Wissenschaftliche Karrieredynamiken in Deutschland im Zeitablauf
Oktober 2013 - September 2016
Extension: September 2016 - August 2019
The WISKIDZ project contributes to a better understanding of long-term developments in the recruiting behavior in public research and individual career paths after obtaining a doctoral degree. The analyses are based on dissertation data, which are supplemented by information on publications, patents and macro-economic data among others. The project essentially analyses two key issues. First, we aim to understand changes in recruiting behavior over time with a special focus put on disciplinary idiosyncrasies. We create and analyze genealogies of doctoral students and their advisors in selected fields (physics, electronics, management and medieval history) from 1945 to the present. Second, the project probes into the interdependencies of academic and non-academic employment opportunities of young researchers. The key points of interest are direct and indirect effects of exogenous changes in the labor market.
Funded by: Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung) within the funding line "FoWiN" [16FWN001]: Forschung zum Wissenschaftlichen Nachwuchs.
Die BibSonomy Genealogie erstellt nutzerbasiert einen Stammbaum der Forschung an deutschen Universitäten. Ausgangspunkt ist der Dissertationskatalog der Deutschen Nationalbibliothek. Nutzerbasiert werden Beziehungen zwischen den an der Dissertation beteiligten Personen (Autor_in, Betreuer_in etc.) ergänzt.
CIL - Collaborative Interactive Learning
February 2017 - June 2019
Technische Systeme lösen computerunterstützt immer komplexere Aufgaben. Während diese Systeme früher für bestimmte Aufgaben und Einsatzbedingungen entworfen wurden und zur Laufzeit auf diese Aufgaben und Bedingungen beschränkt waren, sind sie heute in der Lage, sich an neue Situationen anzupassen, von Beobachtungen zu lernen und sich selbst zu optimieren. Aus diesem Grund werden sie häufig als “smart” oder “intelligent”bezeichnet. Zukünftig wird es mehr und mehr Anwendungen geben, wo auch für selbst-lernende Systeme zur Entwurfszeit nicht mehr alle Daten bereitgestellt werden können, die sie zum Lernen benötigen, und wo eine simple Adaption (z. B. von Parametern) zur Laufzeit nicht ausreicht. Gründe hierfür sind z. B. die benötigte Datenmenge, der zur Beschaffung erforderliche Zeitaufwand oder finanzielle Kosten und insbesondere die Tatsache, dass diese Systeme zur Laufzeit mit Situationen konfrontiert werden, die zur Entwurfszeit nicht bekannt waren (vielleicht sogar in ihrer Art grundsätzlich nicht bekannt sein konnten). Benötigt wird daher eine ganz neue Art “smarter” Systeme mit lebenslanger Lernfähigkeit (entsprechend der gesamten Nutzungsdauer des Systems) in unsicheren und zeitvariaten (veränderlichen) Umgebungen. Diese Systeme müssen hochgradig autonom agieren, indem sie ihr eigenes Wissen bewerten, sich selbständig Informationsquellen (Menschen, andere Systeme, Internet etc.) beschaffen bzw. sich mit ihnen verbinden, Informationen anderer bewerten (z. B. hinsichtlich Aktualität) und dabei unterschiedliche maschinelle Lernverfahren nutzen (z. B. Collaborative Learning oder Active Learning).
Ziel des Projekts ist die Erforschung einer Klasse grundlegend neuer Technologien zur Entwicklung oben skizzierter Systeme, die wir als Collaborative Interactive Learning (CIL) bezeichnen. Diese maschinellen Lernverfahren sind “kollaborativ“ in dem Sinn, dass mehrere Systeme untereinander und mit Menschen kooperieren, um gemeinsam Probleme zu lösen (auch solche, die alleine nicht gelöst werden können). Sie sind auch “interaktiv”, da es aktiv angeregten und geregelten Wissens- und Informationsfluss nicht nur zwischen diesen technischen Systemen, sondern auch zwischen Systemen und Menschen in unterschiedlicher Weise geben wird. Weiter unterscheiden wir bei CIL eine dedizierte ( dedicated, D-CIL ) und eine opportunistische Variante ( opportunistic, O-CIL ). Bei D-CIL sind Lernprozess, Aufgabe und beteiligte Gruppe von Menschen und Systemen klar definiert. Bei O-CIL sind sie Aufgaben variabel und Gruppen für heterogene Teilnehmer offen; die Systeme nutzen alle Informationsquellen, auch wenn diese sehr ungenau und vielleicht nur sporadisch verfügbar sind. Die leitende wissenschaftliche Fragestellung des Projekts ist somit definiert durch die Notwendigkeit, für CIL (bzw. D-CIL und O-CIL) völlig neuartige Konzepte, Technologien und Mechanismen in mehreren Wissenschaftsbereichen zu entwickeln und zu erforschen. Potentielle Anwendungen von D-CIL bzw. O-CIL wurden in vielen Bereichen identifiziert: voneinander lernende cyber-physische Systeme, Teams von autonomen Robotern, kooperierende autonome Fahrzeuge, verteilte Systeme zur Angriffserkennung in Rechnernetzen, Gestaltung von Zusammenarbeitsmechanismen zur Lösung von Aufgaben unter Einsatz von Mechanismen des Collaboration Engineering, Crowdsourcing zur Nutzung der Expertise einer undefinierten Masse von Menschen etc.
Das Projekt „Grundlagen Kollaboratives Interaktives Lernen“ wird durch das Förderprogramm zur weiteren Profilbildung in der Universität Kassel 2017 bis 2022 - Programmline „Zukunft“ durch die Universität Kassel gefördert.
CIDA - Computational Intelligence & Data Analytics
November 2017 - October 2019
FEE - Frühzeitige Erkennung und Entscheidungsunterstützung für kritische Situationen im Produktionsumfeld: Entwicklung von Assistenzfunktionen zur Unterstützung von Anlagenbedienern in kritischen Situation
September 2014 - December 2017
Ein moderner hoher Automatisierungsgrad von Produktionsanlagen erlaubt einen wirtschaftlichen Betrieb auch in Hochlohnländern wie Deutschland. Sie reduziert aber die Prozesserfahrung der Bediener und kann in kritischen Situationen zur Informationsüberflutung (sog. Alarmschauer) führen. Bei Kontrollverlust können Menschenleben und Umwelt gefährdet werden und großen Schäden an Vermögensgütern sowie teure Produktionsausfälle folgen. Ziel des BMBF-Forschungsprojekts FEE ist es daher kritische Situationen im Produktionsumfeld frühzeitig zu erkennen, und durch die Entwicklung von Assistenzfunktionen zur Unterstützung von Anlagenbedienern in kritischen Situation Entscheidungsunterstützung zu geben. Dazu werden mittels der in den Anlagen vorliegenden heterogenen Massendaten geeignete Big-Data-Echtzeit-Methoden entwickelt, um den Bediener frühzeitig zu warnen, mit Assistenzfunktionen und Eingriffsstrategien gezielt zu unterstützen, und proaktives statt reaktives Handeln zu ermöglichen.
PUMA - Academic Publication Management
August 2009 - July 2011
March 2013 - February 2015
Even though many researchers consider the open access idea important, the concrete positioning of content in institutional repositories (IR) often fails due to the fact that - from the authors' perspective - the effort of data entry is not accompanied by direct benefits. In this DFG project the IR-input will therefore be integrated into the work processes of the scientist, who can - at the same time - position the publication he has created in the university research report, update the list of publications on his website and transfer the entry to a cooperative publication management system.
The input is also supported by automatically gathering and offering metadata from different data sources (Sherpa Romeo list, OPAC, Library networks, cooperative publication management systems) at the time of entering the data. For this integration a unique digital author identification (DAI) will be introduced in the project. The PUMA platform will be developed as a showcase of the open access repository platform DSpace and will be connected to the library system PICA and the cooperative publication management system BibSonomy. The system is open for adjustment "out of the box" to other popular IR software, university research reports and university bibliographies. The results will be made available to other libraries as open source software.
EveryAware - Enhance Environmental Awareness through Social Information Technologies
March 2011 - February 2014
There is now overwhelming evidence that the current organization of our economies and societies is seriously damaging biological ecosystems and human living conditions in the very short term, with potentially catastrophic effects in the long term. A grassroots approach can help enact novel policies, with a key contribution from information and communication technologies. Nowadays, low-cost sensing technologies allow citizens to directly assess the state of the environment, and social networking tools allow effective data and opinion collection and real-time information dissemination processes.
The project develops a unified framework by creating a new technological platform that combines sensing technologies, networking applications and data processing tools; the Internet and existing mobile communication networks will provide the infrastructure. Case studies involving different numbers of participants will test the scalability of the platform, aiming to involve as many citizens as possible while leveraging the low cost and high usability of the sensing devices. The integration of participatory sensing with monitoring of subjective opinions is novel and crucial, as it exposes the mechanisms by which the local perception of an environmental issue, corroborated by quantitative data, evolves into socially shared opinions, eventually driving behavioral changes. Critically, enabling this level of transparency allows for effective communication of desirable environmental strategies to the general public and to institutional agencies.
VENUS - Design of socio-technical networking applications in situative ubiquitous computing systems
January 2010 - December 2013
VENUS is a research cluster at the interdisciplinary Research Center for Information System Design (ITeG) at Kassel University, funded by the State of Hesse as part of the program for excellence in research and development (LOEWE).
Many areas of private and personal life are already pervaded by IT applications. The Internet has become a part of everyday life for many people. More and more mobile phones allow high-speed Internet access. Social networks have influenced the nature of connections between people and will continue to enrich our lives with new forms of communication, coordination and interaction. The computerization and networking of everyday life is progressing continuously and rapidly.
The visionary Mark Weiser wrote: Ubiquitous computing technologies “weave themselves into the fabric of everyday life until they are indistinguishable from it”. Thus, the provision and processing of information will be part of the surrounding infrastructure. Information and services will be ubiquitously available. The technology moves into the background and offers customized services adapted to the needs of the user.
From a technical perspective, ubiquitous computing (UC) leads to context-aware applications that adapt dynamically to their runtime environment in order to provide the user with services that are tailored to the particular situation. Hence, ubiquitous computing and self-adaptivity go hand in hand. This implies a variety of technical and non-technical consequences. The ubiquitous availability of services and the associated self-adaptation of applications create new challenges that clearly are not only technical in nature.
The goal of VENUS is to explore the design process of future networked, ubiquitous systems, which are characterized by situation awareness and self-adaptive behavior. The project will explore and extend the foundations of such systems and will in particular develop a design methodology that supports the development of socially acceptable ubiquitous computing applications, i.e. applications that not only satisfy the functional requirements but also comply with the given user requirements in terms of usability, trust, legal regulations and so on. Thus, VENUS focuses on the interactions between the new technology, the individual user and the society. The long-term goal of VENUS is the creation of a comprehensive interdisciplinary development methodology for the design of ubiquitous computing systems.
Commune - Detection of Groups of Interest in Collaborative Tagging Systems
January 2010 - June 2011
July 2011 - February 2013
The amount of available information exponentially increases with the change towards the information society. Formerly aspired archetypes of omniscient knowledge holders are superseded by the ability to quickly find and access world wide instantly available information. Scholars at schools and universities experience that it is not necessary to know everything, but to know where to find the information needed, which manifests in the colloquial phrase of "googling" for information.
This leads to the central problem that no single person is able to survey today's oversupply of information. Therefore, information is preselected and presorted prior access and perception. This gives rise to the question, who pre-processes information. Central and intransparent information preselection forms the worst case from a democratic point of view, as it gives place to politically motivated censorship (e.g., Google-Censorship in china).
Opposed to central information provision, in the "Web 2.0" information are provided and retrieved according to democratic principles. Each individual may provide, review and tag knowledge. But this gives raise to many new problems. A sociologist, e.g., searches with other expectations for the tag "migration" than a computer scientist, and reviews of the one may be irrelevant or even misleading for the other. Such a distinction of individuals not only depends on profession. As manifold a society is, as manifold are the groups of interests it comprises. Based on generated, reviewed and accessed information, technical methods for automatically detecting groups of interests can be engineered. Such methods may then be used for providing interest weighted views on the stored and managed knowledge base. Even preferences and interests of fringe groups which otherwise would be marginalized out as statistical outliers may be accounted.
The Hertie Chair for Knowledge & Data Engineering runs the collaborative publication and bookmark sharing and tagging system BibSonomy. Researchers and students use the system for providing and accessing information but it also serves as a testbed for new methods of presenting and pre-processing information. Next, new methods for automatically detecting groups of interests will be developed and tested. This especially gives rise to new views on the literature which is managed by BibSonomy, but will be generally applicable to other systems. This supports research and teaching, as bibliographies related to a specific field which are commonly provided by single lecturers are superseded by a selection rating of literature based on a corresponding group of interest. A student new to a certain field of research may therefor search well-directed for appropriate literature.
In the context of this research project, new algorithms for detecting groups of interests in collaborative tagging systems will be developed and evaluated. Existing methods have to be adopted to new data structures and new methods developed accordingly. Different methods have to by evaluated objectively. As there are no gold-standards for groups of interests in collaborative tagging systems, new measures for assessing the quality of a given partition in groups of interests have to be developed. The best methods for detecting groups of interests will be implemented in BibSonomy and evaluated in a live setting.
Industry Project with K+S IT-Services GmbH
March 2005 - December 2012
Investigation and implementation of search engines with K+S IT-Services GmbH
Informational Self-Determination in the Web 2.0
April 2009 - September 2010
October 2010 - September 2012
The new generation of the internet ( "Web 2.0" or "social internet") is characterized by a very liberal provision of information through the users. Against this background, this DFG project's goal is to explore and to shape the opportunities and risks of the new Web2.0 technologies in a selected scenario and in close interaction between scientists and lawyers.
After a review of the situation and subsequently the creation of medium-term scenarios, the project will analyze the technical and legal opportunities and risks related to typed roles. Generic concepts will be developed for the design of applications complying with data protection law (identity management, avoidance of personal reference and educational profile, responsibilities). Honouring these concepts, algorithms and procedures for two specific tasks will be developed: Recommender systems for cooperative tagging systems and collaborative spam detection methods for such systems. They are evaluated using real data. The most successful approaches will be implemented in the collaborative publication management system BibSonomy and will be evaluated in the current operation. Finally, it will be analyzed to which extent, on account of the new complex of problems of Web 2.0, dogmatics and interpretation of data protection law have to be modified, and if possibly legislative activities are necessary or advisable.
WebZubi - Ein Web2.0-Netzwerk zur Gestaltung innovativer Berufsausbildung für gewerblich-technische Auszubildende
April 2009 - March 2012
Development of ontology learning methods and evaluation of the Webzubi platform
The Web 2.0 provides excellent prospects for an improvement of apprenticeship by using interactive communication and learning platforms. Up to now the new elements of the Web 2.0 are not used in the project partners' training management. To increase motivation and thereby the quality of education of commercial-technical apprentices, a new Web 2.0 platform shall be implemented. Target audience are commercial-technical apprentices from DB Mobility Logistics AG and associated partners. This pilot project reaches more than 3,000 commercial-technical apprentices altogether. With the help of Web 2.0 technologies, the apprentices shall be prepared for the increasing interoperation in professional life. The challenge for the University of Kassel in this BMBF financed project is the development of semantics-based navigation and recommendation components.
TAGora - Semiotic Dynamics in Online Social Communities
June 2006 - August 2009
Our research group is a member of the EU project TAGora. The focus of the project is the investigation of WEB2.0 applications, which enable users to create user specific contents themselves.
Novel user structures emerge through the mapping of social structures in the internet, differing from data models wich have been investigated so far. Aspects are the appearance of semiotic relations and their development over time. In order to investigate and develop approaches and solutions for models and analysis methods, collaboration is carried out in the interdisciplinary context.
Research partners are: University of Roma (La Sapienza), Sony CSL, University of Koblenz-Landau and University of Southampton.
NEPOMUK - Networked Environment for Personalized, Ontology-based Management of Unified Knowledge
January 2006 - December 2008
As a member of the research centre L3S Hanover we take part in the EU project NEPOMUK. The aim of this project is to extend the computer desktops by semantic abilities in order to improve the collaboration and exchange of information within and between the working groups. Vision is the "Social Semantic Desktop" which unites the abilities of the semantic web with those of social network analysis (SNA).
Within a consortium of researchers, industry and a growing community the research area knowledge engineering deals in particular with the discovery and structurization of communities and in this connection examines methods from the field of SNA. Thus, relations between users, resources and meta data are used to recognize users with similar interests. This shall improve the exchange of knowledge between users unknown to each other.
June 2006 -
Through the assignment of tags to relevant resources (e.g. URLs), folksonomies allow an individual categorization of one's own knowledge, and at the same time collective use of the gathered data. Despite the tags' function of giving a rough preview, which may be used for navigation and orientation within the huge amount of data, a systematic search as known from conventional search engines for the World Wide Web, offers a reasonable completion/extension for information retrieval. For this reason the project, which is supported by a Microsoft award, investigates the implementation and further development of methods based on link popularity as regards the tripartite structure of the folksonomy. In addition to facilitating a "ranked" search for information, a comparison of the amounts of information as well as the users' behaviour e.g. regarding trend discovery can be accomplished.
KDubiq - Knowledge Discovery in Ubiquitous Environments
December 2005 - May 2008
KDubiq is the first Coordination Action (CA) for Ubiquitous Knowledge Discovery, 100% funded by the European Union under IST (Information Society Technology), FET Open (Future and Emerging Technologies) in the 6th Framework Programme under the number IST-6FP-021321. We are actively involved as a chair of the working group 4 (WG4).
The purpose of this working group is to investigate possible data types for ubiquitous KDD systems and elaborate an overview on the current state of the art in representing and processing data in ubiquitous knowledge discovery applications with a particular focus on Web 2.0 mining and sensor networks.
PROLEARN - Technology Enhanced Professional Learning
April 2004 - December 2007
Our research group is a member of the PROLEARN Network of Excellence financed by the IST (Information Society Technology) programme of the European commission dealing with technology enhanced professional learning. Our mission is to bring together the most important research groups in the area of professional learning and training, as well as other key organisations and industrial partners, thus bridging the currently existing gap between research and practical experience in this area.
PROLEARN's goal is to achieve a greater focus on questions of European importance and a better integration of research efforts. Therefore PROLEARN will initiate and improve cooperations between various actors of academia and industry in the area of technology enhanced learning.
COMO - COncepts and MOdels
December 2005 - November 2007
COMO project is a German-Russian cooperation for the investigation of conceptual structures and structures of abstract models within knowledge engineering. Proposals for a conceptual reorganization of the logic as regards practical utilization are to be linked with efforts as for abstract models, in order to being able to solve open questions regarding the pragmatical application of current algebraic-logic theories.
On the one hand the practical problems of communication associated with the use of different semantics (ontologies) are of particular importance. On the other hand, problems of granularity at system descriptions in connection with modal and temporal logic are investigated with general conceptions developed in the conceptual system theory.
PADLR - Personalized Access to Distributed Learning Resources
The research unit Knowledge and Data Engineering of the University of Kassel is partner in the Research Center L3S and works there on a module of the project Personalized Access to Distributed Learning Resources (PADLR), where it develops a so-called Courseware Watchdog. This serves to find teaching materials in the WWW or P2P-network Edutella, Edutella and to present it to the user.
Learning material can be collected with the help of an ontology-based focused Webcrawler and by connecting to the P2P-network Edutella. Subjective Clustering extends well-known algorithms with ontology based background knowledge and permits thus the description of preferences and production of subjective views. A visualization based on Formal Concept Analysis offers intelligent browsing capabilities. Strategies for ontology evolution make it possible to reflect modifications within the ontology which are in the interest of the learner.
February 2002 - December 2004
KDNet is an open network of participants from science, industry and administration. The principal purpose of this international project is the integration of problems from the business everyday life in research discussions and co-operation regarding the future of Knowledge Discovery and Data Mining. The project is promoted by the European Commission as Framework of Excellence in the 5th Master program and runs since February 2002.