Work Plan

Based on the overall strategy for the I-BiDaaS work plan, the work to be performed in the project will be realised in a set of work packages illustrated below.



Work Packages

Lead Beneficiary: UNIMAN
Duration: M1 - M8

WP1 materialises the Baseline Phase of the project and consists of two main activities, namely the Project Set Up activity (M3) and the Positioning of I-BiDaaS (M8). Data value chains (including access control rights and accessibility), the silos that the solution will break and industrial requirements and challenges will be defined by the data providers very early in the project (M3). A knowledge repository will be created, continuously updated and will guide the partners during project’s lifecycle. WP1 main objective is to determine the detailed functionality of the I-BiDaaS platform, according to the user’s needs, the state-of-the-art in distributed data and process mining, predictive analytics and real-time complex event processing over extremely large numbers of high volume streams that are produced in project’s industrial domains. In doing so, this work package will describe in detail the scientific (academic and technical) and the industrial needs and challenges for research and innovation in the Big Data economy. More specifically, the objectives are: a) To define the industrial challenges of the data provider which the proposed solutions will address; b) To synthesise and present the current state of the art from the viewpoint of the project’s highlighted problems; c) To describe the technical framework in which the project will develop with an outline of the three-layer architecture; d) To specify the test cases for the experiments including the verification and validation approach and develop a mapping of the architecture’s mechanics with the streaming data flowing from the data providers.
D1.1. Project set-up (Lead:ENPC; Due:M3; R; CO)
D1.2. Architecture definition (Lead:UNSPMF; Due:M8; R; CO)
D1.3. Positioning of I-BiDaaS (Lead:UNIMAN; Due:M8; R; PU)
Lead Beneficiary: IBM
Duration: M3 – M30

WP2 will built on top of WP1 achievements with the ultimate goal to create complete datasets that can be utilized to validate I-BiDaaS solution in real-life industrial and cross-sectorial experiments. The objectives of WP2 are: a) To define the data nature and format and prepare the respective datasets for simplified processing; b) To deploy an end-to-end solution for data on-boarding; c) To provide a mechanism for transforming and integrating both streaming and historical data produced by heterogeneous sources; d) To fabricate synthetic and realistic big data so as to facilitate the development of the I-BiDaaS technologies and the validation of the I-BiDaaS solution against industrial cross-sectorial experiments; e) To create visualization tools and interfaces for both IT and non-IT experts for the realization of Big Data as a Self-Service.
D2.1. Data assets and formats (Lead:IBM; Due:M8; R; CO)
D2.2. The Data Fabrication Platform (DFP) - interim version (Lead:IBM; Due:M12; R; PU)
D2.3. I-BiDaaS visualization and monitoring framework, and a multi-purpose interface (Lead:AEGIS; Due:M12; R; PU)
D2.4. Universal Messaging Bus - interim version (Lead:SAG; Due:M18; R; PU)
D2.5. The Data Fabrication Platform (DFP) - final version (Lead:IBM; Due:M24; R; PU)
D2.6. Universal Messaging Bus - final version (Lead:SAG; Due:M30; R; PU)
Lead Beneficiary: BSC
Duration: M6 – M30

WP3 activities will focus on the implementation and development of batch processing innovative technologies for the rapidly-increasing historical data. WP3 tools and technologies will be part of project’s knowledge repository. The objectives of WP3 are: a) To introduce innovative, distributed big data analytics architectures based on fully asynchronous Innovative Distributed Solvers (IDS) that will efficiently solve corresponding optimization problems; b) To provide application layer tools (COMPSs, Hecuba and Data Fabrication Platform) to enable both developers and not-IT users to manage batch data by comprising storage of the master dataset and computing arbitrary views using Big Data analysis; d) “automatic ML-based creation” of data fabrication rules; e) To offer a scalable and reliable distributed data management, with an easy-to-use interface and independent of the underlying storage system. The latter will be part of the distributed large-scale layer of the I-BiDaaS solution.
D3.1. Batch Processing Analytics module implementation (Lead:BSC; Due:M12; R; PU)
D3.2. Batch Processing Analytics module implementation as part of I-BiDaaS solution (Lead:BSC; Due:M18; R; PU)
D3.3. Batch Processing Analytics module implementation - final report (Lead:BSC; Due:M30; R; PU)
Lead Beneficiary: SAG
Duration: M6 – M30

The objectives of WP4 are: a) To develop the I-BiDaaS Distributed Big Data analytics algorithms over extremely large numbers of high volume streams; b) To define, customize and integrate its complex event processing engine (Apama by SAG), and to customize the needed visualization tools (MashZone by SAG) in collaboration with advanced visualizations; c) To develop machine-learning techniques deployed on respective edge nodes for handling incomplete data; d) To develop both static and dynamic techniques to partition the incoming queries and execute to the GPU the analytics that will yield higher performance. WP4 tools and technologies will be part of project’s knowledge repository.
D4.1. Real time complex event processing engine – design and approach (Lead:SAG; Due:M12; R; CO)
D4.2. Distributed event-processing engine (Lead:SAG; Due:M24; R; PU)
D4.3. Streaming analytics and predictions (Lead:FORTH; Due:M30; R; PU)
Lead Beneficiary: ATOS
Duration: M6 – M36

WP5 main objective is to provide the distributed large scale framework that permits powerful and scalable Data processing on top of heterogeneous and federated infrastructures. In more detail, it aims to enable: a) Management of diverse infrastructure resources for Data Analytics (including cloud and GPU resources); b) Orchestration of infrastructure resource management across diverse resource providers; c) Seamless integration and exploitation of infrastructure elasticity capabilities by COMPSs and Hecuba runtime environments. In addition to these this WP will be in charge of providing an integrated solution that realises the concept of Big-Data-as-a-Self-Service.
D5.1. Federated Resource Management for Data Analytics - first version (Lead:ATOS; Due:M12; R; PU)
D5.2. Big-Data-as-a-Self-Service Test and Integration Report - first version (Lead:ITML; Due:M12; R; PU)
D5.3. Federated Resource Management for Data Analytics - second version (Lead:ATOS; Due:M24; R; PU)
D5.4. Big-Data-as-a-Self-Service Test and Integration Report - second version (Lead:ITML; Due:M24; R; PU)
D5.5. Federated Resource Management for Data Analytics - third version (Lead:ATOS; Due:M36; R; PU)
D5.6. Big-Data-as-a-Self-Service Test and Integration Report - third version (Lead:ITML; Due:M36; R; PU)
Lead Beneficiary: CRF
Duration: M8 – M36

WP6 will a) ensure a smooth and adequate running of the experiments according to the experimental protocol, demonstrate how I-BiDaaS solution can effectively aggregate, pre-process, manage and synthesize extremely cross-sectorial, noisy and large scale data sets in both batch and real time; b) provide structured feedback, both from the data providers and the technology owners, to the development process; c) ensure project’s impact thus fostering platform’s long term sustainability.
D6.1. Evaluation report - interim version (Lead:CAIXA; Due:M14; R; CO)
D6.2. Experiments implementation - initial version (Lead:UNIMAN; Due:M18; R; PU)
D6.3. Evaluation report - final version (Lead:CAIXA; Due:M22; R; CO)
D6.4. Experiments implementation - final version (Lead:CRF; Due:M30; R; PU)
D6.5. Assessment report and impact analysis (Lead:TID; Due:M36; R; PU)
Lead Beneficiary: ENPC
Duration: M1 – M36

The main objective of WP7 is to ensure that the project’s results are shared effectively with the relevant communities and that the project's exploitation strategy, as well as those of each individual partner are defined. More specifically, the objectives are: a) To provide maximum visibility and public awareness of the I-BiDaaS solution by following a sound dissemination strategy; b) To provide business and technical know-how to the participating partners and companies outside the consortium; c) To identify I-BiDaaS products and map them to actual market needs; d) To define a condensed business plan for the potential commercialization of the I-BiDaaS services; e) To define individual exploitation strategies by project’s partners; f) To take under consideration any policy, privacy and legal issues.
D7.1. Project website (Lead:ITML; Due:M2; R+DEM; PU)
D7.2. Market analysis and business modelling (Lead:ENPC; Due:M8; R; CO)
D7.3. First report on Dissemination strategy and activities (Lead:AEGIS; Due:M12; R; PU)
D7.4. First report on Exploitation Strategy and activities (Lead:ENPC; Due:M12; R; CO)
D7.5. Second report on Dissemination strategy and activities (Lead:AEGIS; Due:M24; R; PU)
D7.6. Second report on Exploitation Strategy and activities (Lead:ENPC; Due:M24; R; CO)
D7.7. Third report on Dissemination strategy and activities (Lead:AEGIS; Due:M36; R; PU)
D7.8. Third report on Exploitation Strategy and activities (Lead:ENPC; Due:M36; R; CO)
Lead Beneficiary: FORTH
Duration: M1-M36

The goal of WP8 is to set up and maintain the administrative, financial and management infrastructure of the I-BiDaaS project, and specifically: a) To provide effective project management at all stages throughout the duration of the project; b) To initiate the project phases, accomplish all necessary administrative tasks and provide regular progress reports to the Commission; c) To supervise the technical progress of the project; d) To closely monitor the I-BiDaaS project development and take appropriate actions if needed; e) To establish/maintain effective communication between project partners; f) To ensure a proper project Administration and Coordination.
D8.1. Project handbook (Lead:FORTH; Due:M3; R; CO)
D8.2. Data Management Plan (Lead: FORTH, Due M6; ORDP; CO)