Projects

ACTIVE

Europe is in transition to a knowledge economy. Effective knowledge management is fundamental to successful economic activity, yet enterprises find it hard to transform much of their essential knowledge into transferable, easily accessible, and actionable knowledge assets. Such hidden knowledge is typically held by individual knowledge workers, being either tacit (unarticulated) or explicit but not widely available (e.g. emails, personal desktop files).

ACTIVE aims to increase the productivity of knowledge workers in a pro-active, contextual, yet easy and unobtrusive way. The aim is to convert tacit and unshared knowledge - the "hidden intelligence" of enterprises - into transferable, interoperable and actionable knowledge to support seamless collaboration and to enable problem solving. A key aspect will be support for informal procedural knowledge - the informal collaboration and problem-solving tasks that drive much knowledge work in the enterprise.

ACTIVE will integrate concepts, methods and tools from the fields of (i) Social Software and Web 2.0, (ii) Semantic Technologies, (iii) Context Mining, Context Modelling, and Context Sensitive Task Management, and (iv) Knowledge Process Mining, Knowledge Process Modelling and Pro-Active Knowledge Process Support into highly innovative application systems. The development will be accompanied by an analysis of key economic and organizational factors and incentive mechanisms, and strongly user-centric system development and evaluation.

The key result of ACTIVE will be a breakthrough which empowers enterprises to make knowledge technology effective for a much larger share of their essential knowledge.

ACTIVE will generate sustainable impact by deploying the tools and applications in three industry sectors: consulting, telecommunication and engineering ("ACTIVE technology"). The added value of ACTIVE technology will be evaluated in economic, organizational, and user studies, which conclude with rigorous field tests. A major focus of ACTIVE will be uptake by industry beyond the immediate consortium.

COllaboration and INteroperability for networked enterprises (COIN)

“By 2020 enterprise collaboration and interoperability services will become an invisible, pervasive and self-adaptive knowledge and business utility at disposal of the European networked enterprises from any industrial sector and domain in order to rapidly set-up, efficiently manage and effectively operate different forms of business collaborations, from the most traditional supply chains to the most advanced and dynamic business ecosystems.”

The mission of the COIN IP is to study, design, develop and prototype an open, self-adaptive, generic ICT integrated solution to support the above 2020 vision. COIN business-pervasive open-source service platform will be able to expose, integrate, compose and mash-up in a secure and adaptive way existing and innovative to be developed Enterprise Interoperability and Enterprise Collaboration services, by applying intelligent maturity models, business rules and self-adaptive decision-support guidelines to guarantee the best combination of the needed services in dependence of the business context, as industrial sector and domain, size of the companies involved, openness and dynamics of collaboration.

This way, the Information Technology vision of Software as a Service (SaaS) will find its implementation in the field of interoperability among collaborative enterprises, supporting the various collaborative business forms, from supply chains to business ecosystems, and becoming for them like a utility, a commodity, the so-called Interoperability Service Utility (ISU).
The COIN project will finally develop an original business model based on the SaaS-U (Software as a Service-Utility) paradigm where the open-source COIN service platform will be able to integrate both free-of-charge and chargeable, open and proprietary services depending on the case and business policies.

e-Freight

The e-Freight project is aimed at supporting, from a transport perspective, the three pillars of European Policy namely:

• Strengthening of the internal market and competitiveness;
• Improving regulation to create a more dynamic business environment;
• Promoting sustainable development.

Specifically e-Freight will contribute to the goals of the Freight transport Logistics Action Plan (Oct 2007), and ITS Action Plan (Oct 2008) pertaining to the development of:

1. A standard framework for freight information exchange covering all transport modes and all stakeholders.
2. A European Single Transport Document for carriage of goods with all the necessary legislative support,
   irrespective of mode.
3. A Single Window (single access point) for administrative procedures in all modes.
4. Simple, harmonised border crossings procedures for all modes of transport for all EU member states.
5. Simple procedures and the necessary infrastructure for establishing secure and efficient transport corridors between Europe, USA, and Asia.

EnvIronmental Services Infrastructure with Ontologies (ENVISION)

The ENVISION project provides an ENVIronmental Services Infrastructure with Ontologies that aims to support non ICT-skilled users in the process of semantic discovery and adaptive chaining and composition of environmental services. Innovations in ENVISION are: on-the-Web enabling and packaging of technologies for their use by non ICT-skilled users, support for migrating environmental models to be provided as models as a service (Maas), and the use of data streaming information for harvesting information for dynamic building of ontologies and adapting service execution.

The ENVISION Environmental Decision Portal supports the creation of web-based applications enabled for dynamic discovery and visual service chaining. The ENVISION Ontology Infrastructure provides support for visual semantic annotation tools and multilingual ontology management. The ENVISION Execution Infrastructure comprises a semantic discovery catalogue and a semantic service mediator based on a generic semantic framework and adaptive service chaining with data-driven adaptability.

Scenario requirements and pilots from the ENVISION user partners focus on landslide hazard assessment and environmental pollution (oil spills) decision support systems. The benefit of ENVISION for the wider community will be better accessibility to modelling tools using the Web and it will provide greater flexibility through improved connections to distributed sources of information.

Incentives for Semantics (INSEMTIVES)

A critical mass of semantically annotated Web pages or multimedia repositories, as well as business-relevant, widely-accepted ontologies would provide a feasible basis for the development of real-world semantic applications, for the adoption of this technology at industrial level, and, why not, for the realization of the Semantic Web vision.

It is therefore understandable that the question of how to create semantic content effectively and efficiently has been investigated in several areas related to semantic technologies, ranging from ontology engineering, ontology learning and ontology population, to the semantic annotation of text, media and Web services resources. The result is a maturing inventory of techniques and tools which primarily aim at a complete (or at least partial) automation of the semantic content generation and management tasks, as a means to lower costs and improve productivity. Whilst the quality of such (fully) automated approaches has constantly improved, it is still far from outweighing the manual effort savings achieved, especially when it comes to the creation of meta-data for non-textual sources or the development of a widely accepted ontology, tasks which are human-driven through their very nature.

The declared aim of this project is to bridge the gap between human and computational intelligence in current semantic content authoring R&D landscape and to produce methodologies, methods and tools optimally exploiting and combining the two to enable the massive creation and feasible management of semantic contents in an economically based manner, and consequently, to provide the missing building block towards the world wide uptake of semantic technologies. Besides automated ways of semantic content creation, the participation of users who actively contribute to the semantic annotation is the main purpose of the proposed R&D project. For the attraction and motivation of users to engage and cooperate in this process, concepts of community have proven to be a critical success factor.

Large Knowledge Collider (LarKC)

The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced "lark"), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web. This will be achieved by:

• Enriching the current logic-based Semantic Web reasoning methods with methods from information retrieval, machine learning, information theory, databases, and probabilistic reasoning.
• Employing cognitively inspired approaches and techniques such as spreading activation, focus of attention, reinforcement, habituation, relevance reasoning, and bounded rationality.
• Building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via "computing at home".

The consortium is an interdisciplinary team of engineers and researchers in Computing Science, Web Science and Cognitive Science, well qualified to realize this ambitious vision. The Large Knowledge Collider will be an open architecture. Researchers and practitioners from outside the consortium will be encouraged to develop and plug in their own components to drive parts of the system. This will make the Large Knowledge Collider a generic platform, and not just a single reasoning engine. The success of the Large Knowledge Collider will be demonstrated in three end-user case studies. The first one is from the telecommunication sector. It aims at real-time aggregation and analysis of location data obtained from mobile phones carried by the population of a city, in order to regulate city infrastructure functions such as public transport and to provide context-sensitive navigation information. The other two case studies are in the life-sciences domain, related respectively to drug discovery and carcinogenesis research. Both will demonstrate that the capabilities of the Large Knowledge Collider go well beyond what is possible with current Semantic Web infrastructure.

MUSING

MUSING aims at developing a new generation of Business Intelligence (BI) tools and modules founded on semantic-based knowledge and content systems. MUSING will integrate Semantic Web and Human Language technologies and combine declarative rule-based methods and statistical approaches for enhancing the technological foundations of knowledge acquisition and reasoning in BI applications. The breakthrough impact of MUSING on semantic-based BI will be measured in three strategic, vertical domains: Finance, through development and validation of next generation (Basel II and beyond) semantic-based BI solutions, with particular reference to Credit Risk Management; Internationalisation, through development and validation of next generation semantic-based internationalisation platforms; Operational Risk Management, through development and validation of semantic-driven knowledge systems for measurement and mitigation tools, with particular reference to IT operational risks faced by IT-intensive organisations.

S-Cube

S-Cube, the Software Services and Systems Network, will establish an integrated, multidisciplinary, vibrant research community which will enable Europe to lead the software-services revolution, thereby helping shape the software-service based Internet which is the backbone of our future interactive society.

An integration of research expertise and an intense collaboration of researchers in the field of software services and systems are needed to address the following key problems:

• Research fragmentation: Current research activities are fragmented and each research community (e.g., grid computing or software engineering) concentrates mostly on its own specific techniques, mechanisms and methodologies. As a result the proposed solutions are not aligned with or influenced by activities in related research fields.
• Future Challenges: One challenge, as an example, is to build service-based systems in such a way that they can self-adapt while guaranteeing the expected level of service quality. Such an adaptation can be required due to changes in a system’s environment or in response to predicted and unpredicted problems.

SEALS

Semantic technologies are at the heart of the future Web providing ways to express knowledge and data so that it can be properly exploited. These technologies will empower a new class of Information and Communication Technologies much more scalable, interoperable, and with a higher degree of process automation support that will fulfill the needs of an emergence market that will exceed $10 billion by 2010. This is a very active research area, but still suffers from a lack of standard benchmarks and infrastructures for assessing research outcomes. SEALS addresses two key challenges: the creation of a lasting reference infrastructure for semantic technology evaluation and the continuous benchmarking of semantic technologies at a large scale via public worldwide evaluation campaigns.

Semantics and Ontologies for Feedback-driven Adapting Recommender Systems (SOFAR)

Consumers increasingly buy products through the Internet, but they lack assistance for searching the “right” product. Recommender systems address this problem by asking targeted questions. The success (or failure) of such a recommendation process is defined in terms of conversion rate or click-out rate. It is very difficult to predict improvements for given changes of the recommendation process, however, and manual changes are usually very expensive.

Therefore, SOFAR ("Semantics and Ontologies for Feedback-driven Adapting Recommender Systems") proposes automated adaptations of recommendation processes making use of semantic technology. The approach makes Internet content accessible for searching products.

Service Bundler

The mission of the Service Bundler project is to study, design, develop and prototype an open, self-adaptive and generic SaaS (Software-as-a-Service) integrated platform with its primary research focus on composition and monitoring of services. We will develop a Service Bundler business-pervasive platform that will enable to integrate, compose and expose in a secure and adaptive way innovative services. This will be done by applying business rules and self-adaptive decision-support guidelines to guarantee the best combination of the needed services by taking into account the business context. The role of the Service Bundler project would be to provide a set of core technologies for the base seekda Service Platform. We aim to allow the use of abstract process templates – enabling the composition of available Web Services – such that, with the support of a monitoring mechanism, they can be executed consecutively without any user interaction in-between. Even if some of these services would not perform as initially expected, these should remain transparent to the end user. From an external perspective, such a composition (or bundle as we call it in this proposal) of services would act like one service, offering a specific eCommerce functionality. The fact that this functionality is only reached after executing multiple services should be hidden behind seekda’s platform.

Service Detective

The goal of Service-Detective is thus to overcome shortcomings of current Web Service search engines by:

• Employing automated methods to gather Web Services and related resources.
• Leveraging automatic means to create semantic service descriptions from information available on the Web.
• Describing the aggregated information in semantic models and allowing reasoning over it.
• Building meaningful clusters of the collected services and of search results.

 

The Service-Detective project will deliver a search engine that enables users to find up-to- date information on available Web Services. It will employ automated crawling, information retrieval methods and analysis techniques and shall be able to scale with the increasing number of services, as this approach does not rely on a central editorial team that would necessarily become a bottleneck once the number of deployed services reaches Web scale. Consequently, the approaches developed by Service-Detective can adapt quickly to changes in terms of the available services. The search engine will leverage available information exposed by current technologies and extend this information with semantic annotations to allow for more accurate retrieval. It will use the service information to enable efficient clustering and matchmaking of services, in view of the goal to provide an efficient discovery and clustered search possibility for Web Services.

SHAPE

Modelling is an integrated part of software engineering approaches. Business process models are widely used to describe how work is done within an organization, while various product models describe what is done. Various approaches based on model-driven engineering (MDE) concepts, such as the OMG MDA (Model Driven Architecture) and related efforts around domain-specific languages have gained much popularity. Business models are described in the computation-independent models (CIMs) while for the product models, the model-driven approach separates platform-independent models (PIMs) from the platform-specific ones (PSMs) in order to abstract the implementation technologies.

The objective of SHAPE is to support the development and the realization of enterprise systems based on Semantically-enabled Heterogeneous Architectures(SHA). SHA extends service-oriented architecture (SOA) with semantics and heterogeneous infrastructures (Web services, agents, Semantic Web Services,P2P and grid) under a unified service-oriented approach. SHAPE will develop a model-driven engineering (MDE) tool-supported methodology. SHAPE will take an active role in the standardization of metamodels and languages for SHA. The technical results will be compliant with the proposed standards to ensure high industry acceptance. In current SOA approaches, business requirements and technical details are intertwined constraining the evolution of service-oriented business solutions. SHAPE will provide metamodels and languages, methods and tools to separate the different viewpoints of SOA for the development of semantically-enabled, flexible and adaptive business services on a rich SHA-infrastructure.

SOA4All: A Web of billions of Services (SOA4All)

The emerging generation starts by abstracting from software and sees all resources as services in a service-oriented architecture (SOA). In a world of services, it is the service that counts for a customer and not the software or hardware components which implement the service. Service-oriented architectures are rapidly becoming the dominant computing paradigm. However, current SOA solutions are still restricted in their application context to being in-house solutions of companies. A service Web will have billions of services. While service orientation is widely acknowledged for its potential to revolutionize the world of computing by abstracting from the underlying hardware and software layers, its success depends on resolving a number of fundamental challenges that SOA does not address today. SOA4All will help to realize a world where billions of parties are exposing and consuming services via advanced Web technology.

The outcome of the project will be a comprehensive framework and infrastructure that integrates four complimentary and revolutionary technical advances into a coherent and domain independent service delivery platform:

• Web principles and technology as the underlying infrastructure for the integration of services at a world wide scale.
• Web 2.0 as a means to structure human-machine cooperation in an efficient and cost-effective manner.
• Semantic Web technology as a means to abstract from syntax to semantics as
  required for meaningful service discovery.
• Context management as a way to process in a machine understandable way user needs that facilitates the customization of existing services for the needs of users.

SOA4All will significantly impact the competitiveness of the European Software and IT Services industry and more widely to address the Lisbon goals. For that purpose SOA4All will use the support of the NESSI constituency and will contribute significantly to the NESSI Open Framework, which is one of the main challenges of the European Platform on Software and Services. It has a consortium of 16 partners and led by Atos Origin.

WSMO4LS

Scientific Workflows are very important to support life-science researcher in the discovery of cures for many diseases. Life-science researchers need easy to use and as much as possible automated software frameworks, so as to require for them a minimum knowledge of software technologies to accomplish their daily research task without extra learning efforts and reducing their manual efforts. Research in scientific workflows produced many results in this area, but still a huge manual effort is required to scientists to integrate different available data and compose different available services. Semantic Web is currently one of the most interesting research areas with focus on automation of interoperability composition, and discovery of services that can bring a huge contribute to the research in scientific workflow. The objective of the collaboration among the University of Innsbruck and the University of Malaga, is to bring together their respective expertises in Semantic Web technologies and scientific workflows to produce a prototype of a innovative Semantic based framework for scientific workflows.