Periodic Report Summary - RAISME (Rapid Application Innovation for SMEs) Project context and objectives:RAISME will enable high-tech organisations with niche skills to rapidly build and scale innovative ICT applications. This will be achieved through the collabourative use of advanced mashup technology and cloud computing. The RAISME SMEs are at the vanguard of a new business paradigm where the end-user becomes part of the product development lifecycle, thus accelerating it, and where collabouration allows faster exploitation of knowledge and productivity. Initial RAISME partners who have already developed state-of-the-art visualisation, optimisation and integration tools that will be able boot-strap a series of new applications and then deliver highly innovative knowledge services to the market.Given the limited resources of SMEs, they are likely to be more successful if they collabourate with other organisations. This includes seeking ideas and expertise not just from internal sources, but also from linkages with other firms - often extending to sharing and use of intellectual property (IP). Research suggests, however, that smaller firms often do not collabourate because they face significant barriers to co-operation. They suffer, amongst other things, from the inability to identify suitable partners, to forge co-operative agreements and to acquire tacit knowledge. RAISME aims to go at least some way in helping to overcome these issues.The RAISME consortium consists of three SMEs, DRTS, GAMCO, and VISUP, and five RTD performers, i2CAT, UPC and the University of Sheffield. DRTS brings complexity science experience and the Dacord technology. GAMCO brings neural-network modelling and the GENM technology. And, VISUP brings visualisation, user design experience and the Closer.IT technology. From the RTD's, Sheffield provides multi-criteria optimisation expertise in the form of MOGA. UPC provides experience with the REST web-service APIs and semantic matchmaking technology. With i2CAT providing web infrastructure, integration expertise and network visualisation and manipulation.The collabourative project output is intended to provide a platform for data processing, analysis and visualisation supporting the marketing and exploitation of novel algorithms and visualisation technologies. It will also extend the knowledge and experience of the project partners in the change towards cloud-computing in terms of development, technological requirements, integration on cloud platforms and the identification of new business models.As a prototype, the product will provide two main exploitation paths: to develop into a platform to offer data processing direct to the consumer through web access; and to develop into a platform-as-a-service as a market place for data processing and analysis algorithms.The RAISME mashup platform will incorporate semantic mechanisms for data and service integration to support easy integration of future processing and visualisation service. The platform will be a multi-user account system that can be extended for usage accounting and billing therefore creating the opportunity for new revenue streams for the project partners and to create a market place for external SMEs to register there services in the platform.Project results:At the start, the RAISME project partners reviewed progress in business and technology in the two years since the project conception to establish the platform requirements and architecture (WP2), case studies and business scenarios (WP1). This included a review of the project direction before fully committing resources. In this first period, project management, reporting and control procedures (WP5) have also been put in place.After the initial requirements phase, a first prototype was produced. The focus was to design and implement the desired RAISME platform requirements (D2.1) leading to the platform architecture (D2.2) and initial prototype (D3.1). The prototype was demonstrated to all partners with feedback on how to proceed with further integration of services and how to improve the concept of the integration platform. The initial prototype showed we could integrate SME data processing services with: data importing; automated data identification; integration of hosted and remote web services; and the results can be seen on screen with visualisations of time series graph, network plots and parallel coordinates.The evaluation of the prototype platform architecture showed limitations in: expandable provisioning across clouds; user account management; large data storage and secure access; interactive visualisations for the user to explore data. The project investigated cloud technologies in infrastructure as a service (e.g. OVH, Microsoft, Amazon.com) platform as a service (e.g. WSO2, Google, Salesforce.com) and software as a service (many examples). The salient issue is how to change service provider and avoid vendor lock-in. The investigation was documented by updating platform architecture (D2.2) and in tool integration methodology (D2.3).Developed from the first prototype, the second prototype used open-source packages from Apache projects and wso2.org built on cloud computing to evaluate the ease of deployment. The new architecture now provided identity management, data services, and application execution environment, which were extended to include user accounts and user data storage according to RAISME requirements.The user interface was designed using a wire frame design of pages for: user registration; data importing and cleaning; processing workflow; and data and results visualisation. New interactive graph plotting technologies were chosen to support PC browser and tablet access. The data services and SME services were advanced with service APIs designed for integration and external access using web standards REST and SOAP. A semantic framework was built to support assisted workflow configuration. This used a matchmaker service from the EU funded ALIVE project (see http://www.alive.eu for details) to automatically identify compatible data and services. The progress in design, implementation and experience has been maintained within the project deliverables and technical notes.The SMEs evaluated the project against the use case scenarios defined in the first period. GAMCO used the experience as a demonstration service to prospective customers. DRTS made similar web-based demonstration of their system analysis tool. Both organisations exposed the capabilities of a product that had so far been only an in-house tool for prediction, enhanced by RAISME time-series visualisations and statistical analysis of input and output data.The project website (see http://www.raiseme.eu online) was maintained with information about the project objectives and project partners. A four-page project brochure available on the website was produced to showcase the development, potential markets and listing the project partners. The project was presented at the SPRERS training event (see http://www.sprers.eu/ for details) on 11 November 2011 at Timisoara, Romania. This was part of improving communication between EU FP7 funded projects and use of cloud computing in project.Potential impact:RAISME has built an innovative mashup platform that will integrate sophisticated software services. The platform allows data extraction from heterogeneous data sources, data mining and classification, complex system modelling and advanced visualisation. The platform allows the end-user to create new composite services by creating a customised workflow of algorithm services and visualisations. The development of this new platform will carry out research beyond the current state-of-the-art, but will provide the participating SMEs with a new tool to access markets that were until now closed for them.In this project, each participant provided its expertise to achieve a major goal in collabouration with others. DRTS is a company that focuses on the modelling of complex systems, providing the ability to holistically view, analyse and interpret system data, to reveal trends, patterns and anomalies that provide early-warning prediction. GAMCO is a company whose applied research focuses on extracting implicit knowledge from large historical data by using advanced machine learning to generate models for forecasting, classification, complex multivariate analysis and simulation for a range of sectors. VISUP is a company whose applied research focuses on the visualisation of complex data and the development of interactive solutions.The final RAISME result is a functional prototype that integrates the services provided by the SMEs into a platform that can offer an extended range of users access to powerful processing algorithms. The RAISME integration provides the link between visualisation and analysis of trends and patterns in large complex systems, with system modelling and prediction, to then explore scenarios through system simulation and optimise system options.All project partners plan to exploit the knowledge and experience from RAISME by adapting existing desktop-based application to web-based applications, or by developing new applications as web-based applications. The development requires knowledge gained in several areas of the project, such as web server deployment, dividing an application into distributed web services and development using web technologies.GAMCO are advancing development of the main product Gamco engine neural models (GENM), thanks of the knowledge gained through RAISME and linked with European project GENMAS, also using cloud computing for the automatic acquisition of implicit knowledge in large databases. And will allow the development of two new technologies: services by GENM (SeGENM) for advanced knowledge data discovery services over the internet and applications by GENM (AGENM) will integrate complex solutions into large enterprises via automatically generated models.DRTS is plans to exploit software-as-a-service following of the end of the project. The commercial offering will include extending the proprietary algorithms and processing services developed by DRTS and integrated into the RAISME environment. The business sectors include business intelligence, systems risk analysis and prediction; and the target sectors financial and risk analysis, energy efficiency, business process analysis.Each organisation has differing interests in the deployment of web-based technologies on the cloud, with a combination of public and private clouds. For example, during the project I2CAT used internal virtualisation of server machines to host the demonstration portal and the use of external cloud providers for the RAISME compute and data server, since this had higher hardware requirements that provided internally. The project demonstrator used a hybrid public and private cloud, gaining useful experience in how to develop systems in-house that can be partially deployed outside of the internal IT infrastructure by easily and economically expanding to third party providers.Project website: http://www.raisme.eu
