|LVA-Leitung:||Werner Retschitzegger (Topic 1 - Topic 2 - Topic 3)
|Vorbesprechung:||persönliche Termin-Vereinbarung mit dem LVA-Leiter|
|Typ:||PR, 5h, Block|
Topic 1: TheHiddenU - A Social Nexus for Privacy-Assured Personalisation Brokerage (Retschitzegger, PDF-Version)Social networks on the Web have seen enormous growth over the past few years reaching now truly widespread adoption. Since every social network is focused on serving specific human needs, social networkers are present in a number of different networks, leading to scattered social content. This restraint view on social content carries the potential pitfall of untargeted services like indiscriminated product offers of service providers, being a major obstacle in generating revenue. This situation is aggravated by the fact that social networkers are particularly reluctant to share social content with service providers - which would be, however, necessary to enable personalization - at least as long as it is obscure and beyond their control, if and how their social content is being exploited.
In the course of a FIT-IT project we will develop TheHiddenU, a system whose main goal is to exploit the encouraging win-win situation between social networkers and service providers with respect to personalization, by inventing semantic-based mechanisms to leverage techniques for integrating, profiling and privatising social content. The innovative character of TheHiddenU stretches over three unique but highly interwoven research goals. Firstly, TheHiddenU aims at providing a single point of access to social networks in terms of an integrated semantic representation of scattered social content by employing a hybrid integration approach for schema level and instance level. Secondly, TheHiddenU foresees semantic-based profiling mechanisms in order to discover the "hidden" you and brokerage facilities bringing together social networkers and service providers in a controlled way, thus enabling highly personalized services. Thirdly, TheHiddenU focuses on privacy concerns by providing social networkers with awareness and ample control regarding disclosure and usage of their social content.
The solutions for these challenges are realized by means of TheHiddenU prototype and provide the technical prerequisites for a brand new, sustainable business model for the Social Web - personalisation brokerage. The method for evaluating TheHidden builds on three major pillars, comprising experiments, empirical studies, and a case study, which will be conducted in cooperation with our demonstrators. Thus, TheHiddenU will represent a research test bed as well as an industrial showcase for further commercial exploitation. Ziel dieses Seminars ist es, in Form von Gruppenarbeiten einen Überblick über die spezifischen Probleme der Integration von sozialen Netzwerken zu geben und Möglichkeiten zur Personalisierung unter größtmöglicher Berücksichtigung der Privatsphäre der Benutzer zu geben sowie den Brokerage-Aspekt eingehend zu beleuchten. Es sollen von den Seminar-Gruppen interessante Ansätze in diesem Gebiet vorgestellt werden und insbesondere auch neue Entwicklungen und offene Forschungsthemen behandelt werden. Basisliteratur:
- Halpin, H.: Ten Theses on the Future of Social Networking. Proc. of W3C Workshop on the Future of Social Networking, Barcelona, 2009
- Kobsa, A.: Privacy-enhanced personalization. Commun. ACM 50(8): 24-33, 2007
- Kobsa, A.: Generic User Modeling Systems. The Adaptive Web, Springer, LNCS 4321, pp. 136-154, 2007
- Sriharee, N., Senivongse, T.: Matchmaking and ranking of semantic web services using integrated service profile. Int. J. of Metadata, Semantics and Ontologies, 1(2): 100-118, 2006
- Bleiholder, J., Naumann, F.: Data fusion. ACM Computing Surveys, 41(1): 1-41, 2008
Topic 2: BeAware! Lost in Time, Space, and Meaning or How to Gain Situation Awareness in Large-Scale Control Systems (Retschitzegger, PDF-Version)Large-scale control systems, as encountered, e.g., in the domain of road traffic management, typically deal with highly-dynamic environments providing a vast amount of information, stemming from multiple heterogeneous sources, about a large number of real-world objects anchored in time and space. In such systems, human operators are at permanent risk to get lost in the induced information overload failing to be aware of the overall meaning of the available information and its implications. This endangers the timely and correct identification, resolution and pro-active prevention of critical situations potentially causing serious impacts in the real world.
In the course of a FIT-IT project1 we are currently developing BeAware!, an ontology-driven framework for supporting situation awareness in large-scale control systems. A situation awareness ontology should facilitates the definition of domain-independent situation types consisting of constituting objects and relations in-between, heavily building on existing work in the area of qualitative spatio-temporal reasoning. The situation assessment mechanisms of BeAware! are responsible for the identification of sets of interrelated objects that satisfy the situation types of interest. To ensure the efficiency of this assessment process, a prior knowledge on relations between objects is encoded within the ontology in order to check the satisfiability of a situation type and assessment shortcuts for inferring relations between objects based on their subsumption lattices and their set-theoretic characteristics are introduced. In this respect, the concept of "conceptual neighbourhoods" of relations is used to assess situations being similar to an existing situation type as well as to assess evolving future situations. Concerning implementation of BeAware!, a pipes-and-filters architecture for ontology-driven information systems is proposed which rely on data asynchronously pushed from their sources. The real-world adequacy of the developed framework is demonstrated in the domain of road traffic management using real-world traffic situations from the Austrian highways agency's (ASFINAG) traffic management system. For more information about BeAware! please visit the project homepage:
- Kokar, M.M., Matheusb, C.J., Baclawski, K.: Ontology-based situation awareness. International Journal of Information Fusion 10(1) (2009) 83-98
- Jens Bleiholder, Felix Naumann: Data fusion. ACM Comput. Surv. 41(1): (2008)
Topic 3: TROPIC - A Framework for Model Transformations on Petri Nets in Color (Retschitzegger, PDF-Version)Model transformations play an important role in software engineering in general and in the area of model-driven engineering in particular, representing the key mechanisms for model translations (e.g., translating an ER model into a UML class model), model augmentations (e.g., weaving aspects into a UML class model), and model alignments (e.g., mapping a content model to its GUI view), to mention just a few.
The aim of this project2 is to establish a framework called TROPIC (Transformations on Petri Nets in Color) for developing model transformations which tackles these limitations. First, TROPIC allows to specify model transformations on different abstraction levels, providing both a declarative mapping language based on UML 2 component diagrams which hides implementation details, and derived from that, an executable transformation language using Coloured Petri Nets. Second, TROPIC facilitates reusability by providing an initial library of generic transformation operators which can be bound to arbitrary metamodels and by allowing to extend this library on demand with new, user-defined, transformation operators, optionally composed out of already existing ones. Finally, TROPIC overcomes the impedance mismatch by supporting a dedicated runtime model in terms of Coloured Petri Nets, allowing for a homogeneous representation of all transformation artefacts (i.e., models, metamodels and the transformation logic itself), which fosters understandability and debuggability of model transformations.
The methodology for evaluating the proposed framework builds on three major pillars. First, appropriate case studies for transforming heterogeneous structural as well as behavioural models will be set up and implemented with different existing model transformation languages, including TROPIC, the results being evaluated on basis of a suitable subset of the ISO 9126 software quality model. Second, the findings of these case studies will be further critically reflected by conducting an empirical study with students from our model engineering courses. Third, dedicated workshops will be held together with internationally renowned inventors of other model transformation languages to additionally review the value of our proposed framework. For more information about TROPIC please visit the project homepage:
- Portal Site: http://www.model-transformation.org
- Czarnecki, K, and Helsen, S : Classification of Model Transformation Approaches.
In: Proceedings of the OOPSLA'03 Workshop on the Generative Techniques in the Context
Of Model-Driven Architecture, Anaheim, California, USA.
- Object Management Group (OMG). 'MOF QVT Final Adopted Specification'. ptc/05-11-01, March 31, 2007