To new ERCIM Working Groups have been established recently: The Working Group "Social Network Analysis" focusing on algorithmic aspects of network data analysis and the Working Group "Models and Logics for Quantitative Analysis" exploring and developping methods for formal verification of modern advanced software systems.
Social Network Analysis
The ERCIM working group on Social Network Analysis (SNA) has recently been formed in 2009 with a view to foster European collaboration in research on data analysis for social networks. The main objective of the SNA group is to build a strong network of researchers with expertise on algorithmic aspects of network data analysis. The first action will be to foster collaboration through the organisation of scientific meetings with the medium-term objective of collaborating on funded research programmes in this area.
Research in network data analysis is being transformed by access to large-scale data resources. The availability of this data in electronic format presents some interesting challenges and opportunities for data analysis. In particular, social networking sites are prominent sources of such data. Given that the defining characteristics of social networks are that at least some of the nodes in the network are human actors, the analysis of such networks can be used to provide useful insights into how people interact. However, fundamental research problems exist, and many of these problems are common among several research domains.
Areas of interest include:
- Algorithmic aspects of large-scale networked data analysis
- Information retrieval over social media
- Data mining and semantic web approaches for social media enrichment.
The SNA working group sees significant synergies with existing ERCIM working groups such as Computing and Statistics & Data and Information Spaces (DIS).
The initial meeting of the SNA WG attracted 29 participants from 9 universities and 2 industry partners with a keynote lecture from Prof. Barry Smyth of UCD, Dublin. The meeting led to agreement on the name and scope of the working group with a follow-up meeting to be held in Italy in November during ERCIM week.
Pádraig Cunningham, SNA Working Group coordinator
University College Dublin, Ireland
Models and Logics for Quantitative Analysis
A new ERCIM Working Group on Models and Logics for Quantitative Analysis (MLQA) was officially established in September 2009. The remit of the Working Group is to explore and develop methods for formal verification of modern advanced software systems. Such methods have already been successfully applied to self-contained and relatively simple systems. The group will develop new methods and expand the applicability of previous methods in order to formally verify the functionality of complex interacting modern software systems. This will be done by combining recent theory and methods from computer science and mathematical modelling.
A large fraction of contemporary Information Technology systems are either Embedded Systems (offering autonomous and intelligent control of complex physical systems) or Service-Oriented Architectures (providing Web services designed to support machine-to-machine interaction over a network). This tendency will greatly increase in what will become the Internet of the Future, an integrated system comprising telecommunications, the Internet, and small systems embedded in domestic appliances. Cutting-edge examples include intelligent vehicles that actively prevent accidents, intelligent homes that actively support your lifestyle, and services for handling electronic shopping and secure payments. On a larger scale, the future integration of medical equipment, emergency support systems, electronic hospital records and next-generation communication technology are examples pointing towards the trend of Service-Oriented Systems incorporating a number of embedded components. On an even larger scale, we begin to see IT Guided Workflow Systems where the humans mainly play the role of domain experts (eg a doctor who is an expert in a given treatment) rather than being in charge of the overall workflow (eg monitoring the treatment history from the point of view of the patient). Outside the traditional domains of IT systems, the use of computer science modelling and analysis techniques is also growing in the life sciences, in particular the modelling of components of biological systems.
Figure 1: The research challenges of MLQA.
The need for stability in the IT infrastructure of our future society demands that a number of fundamental properties be validated for the IT systems of interest. This spans properties related to security (eg ‘no virus can allow outsiders to get access to my Internet banking account’), performance/ dependability (eg ‘my critical Internet service will be available 99.99% of the time’) and resource usage (eg ‘the control system rotates and adjusts the windmill such that at least 60% of the potential wind energy is utilized’). Even the formulation of these properties becomes nontrivial when addressing IT Guided Workflow Systems that have humans as ‘subsystems’ and when addressing the description of three-dimensional behaviour in biological systems.
The challenge in the modelling and validation of embedded and service-oriented systems is that due to their interaction with the surrounding physical environment, they must include aspects that are discrete (eg providing security guarantees), stochastic (eg dealing with performance) and continuous (eg providing measurements of resource usage). A shift is required in the development of IT systems from the study of discrete properties to also include stochastic and continuous properties, not least when addressing IT Guided Workflow Systems. The use of stochastic and continuous properties is equally important in the life sciences.
To meet the above challenge we need powerful modelling methods and algorithms for the analysis of discrete, stochastic and continuous properties. The aim of this Working Group is to create both a venue for knowledge sharing in this exciting area and a network for young researchers; furthermore to share tools for performing analyses and to create joint European research projects on quantitative analysis.
The Working Group was created following a meeting/workshop during the ETAPS 2009 conference held in York in March, where 33 participants enjoyed six invited talks and twelve short presentations.
The activities of the ERCIM Working Group on Models and Logics for Quantitative Analysis (MLQA) will study process models that are appropriate for describing the behaviour of systems and logics that are suitable for describing their quantitative properties.
The activities will:
- model behaviour of processes by means of transition systems, automata or process calculi
- model quantitative properties using logics for expressing not only discrete but also stochastic and continuous properties
- focus on algorithms, theory and tools
- study applications with particular emphasis on embedded systems and service-oriented systems, but aim also to treat IT Guided Workflow Systems and biological systems.
Flemming Nielson, MLQA Working Group coordinator
DTU Informatics, Denmark
ERCIM Working groups are open to any researcher in the specific scientific field.Scientists interested in joining the Working Group should contact the coordinator.