D3.8 CLOUD INFRASTRUCTURE INCENTIVES MANAGEMENT AND DATA GOVERNANCE SOFTWARE PROTOTYPE 3

The third and final version of the Cloud Infrastructure, Incentives Management and Data Governance software prototype includes the cloud gateways and APIs, the cloud provisioning mechanisms, the implemented version of the algorithms as well as the data governance tools according to the D3.1 [1], D3.4 [2] and D3.7 [3] specifications and is built upon the first and second versions of the prototype described in D3.2 [4] and D3.5 [5] respectively. The prototype’s cloud infrastructure is supported by RECAS-BARI and is utilized by EGI through cloud gateways. These gateways allow the prototype to gather data from heterogenous data sources, such as Twitter and the global terrorism database and have integrated microservices to serve the needs of the different PolicyCLOUD pilots. The final version of the Incentives Management tool is also provided in this deliverable. This final version has been integrated with the Policy Development Toolkit (PDT) and has been deployed in the EGI Cloud. This third version of the prototype also includes the latest updates of the ABAC based access control mechanism and the Keycloak integration. This is broken down to 8 key components that have been combined to provide fine-tuned and secure access control and authentication. Specifically, Keycloak has been integrated with the Marketplace, the Gateways and the PDT and custom access policies have been developed for the gateways microservices. Finally, both the introduction of a XACML editor to ease access policies creation and the integration of EGI Check-in, an alternative way to authenticate to the prototype with academic and social credential, enhance the user experience in the PolicyCLOUD platformThis deliverable is submitted to the EC, not yet approved

PolicyCLOUD: Analytics as a Service Facilitating Efficient Data-Driven Public Policy Management

Part 2: Clustering/Unsupervised Learning/AnalyticsInternational audienceWhile several application domains are exploiting the added-value of analytics over various datasets to obtain actionable insights and drive decision making, the public policy management domain has not yet taken advantage of the full potential of the aforementioned analytics and data models. Diverse and heterogeneous datasets are being generated from various sources, which could be utilized across the complete policies lifecycle (i.e. modelling, creation, evaluation and optimization) to realize efficient policy management. To this end, in this paper we present an overall architecture of a cloud-based environment that facilitates data retrieval and analytics, as well as policy modelling, creation and optimization. The environment enables data collection from heterogeneous sources, linking and aggregation, complemented with data cleaning and interoperability techniques in order to make the data ready for use. An innovative approach for analytics as a service is introduced and linked with a policy development toolkit, which is an integrated web-based environment to fulfil the requirements of the public policy ecosystem stakeholders

D6.9 INTEGRATION OF RESULTS: POLICYCLOUD COMPLETE ENVIRONMENT M36

This deliverable has been released in December 2022, at M36 of the project, and its main objective is to specify the final integration results between the PolicyCLOUD components. This deliverable will follow the methodology of D6.2 and D6.8 that were respectively submitted in M12 (December 2020) and M24 (December 2021) which have two main pillars: Define common practices for integration and validation of the outcomes of the project Detail the cloud environment the project will make use of to demonstrate the results Regarding the former, GitLab will be the base code repository for the project, where the project already owns an organizational account. Over GitLab [1], the trunk-based development branching policy has been applied, as we considered it the most suitable policy given the project characteristics. Also, GitLab’s issue reporting tool has been adopted, as it is fully integrated with GitLab’s features. The test bed to support the demonstrators has been deployed over EGI’s (EGI) infrastructure where flexibility is one of the critical features. This deliverable abstractly incorporates all the changes and implementations that WP2, WP3, WP4 and WP5 had made during the second year of the project. More details about the components and the actual implementation can be found in the related WP deliverables [7] [8] [9]. In detail, the schemas of the data have been finalized so the standard version that we defined initiated the data import to the repository of PolicyCLOUD. Moreover, the infrastructure (IaaS) and the platform deployment (PaaS/ Serverless) have been restructured and reshaped based on the latest needs of the components. EGI deployed the new flavour of PolicyCLOUD to the Openstack Infrastructure and IBM made the proper changes to the Openwhisk middleware for the serverless and other services. The related WP deliverables highlight detailed information and instructions for each component change that in total orchestrate the PolicyCLOUD engine.This deliverable is submitted to the EC, not yet approved

D2.7 CONCEPTUAL MODEL & REFERENCE ARCHITECTURE

The third and final version of the PolicyCLOUD Conceptual Model & Reference Architecture (originally submitted as Deliverable D2.2 in September 2020 [20] with the second version submitted as D2.6 in June 2021 [21]) is presented in this document. The PolicyCLOUD Conceptual Model presents the overall project concept along 2 main axes. Along the first data axis PolicyCLOUD delivers Cloud Gateways and APIs to access data sources and adapt to their interfaces so as to simplify interaction and data collection from any source. Along the second main axis, the Policies Management Framework of PolicyCLOUD allows the definition of forward-looking policies as well as their dynamic adaptation and refocusing to the population they are applied on. Based on the project’s offerings along the main two axes of the Concept, five main building blocks (in a layered manner) define its Architecture: (1) The Cloud Based Environment and Data Acquisition, (2) Data Analytics, (3) the Policies Management Framework, (4) the Policy Development Toolkit and (5) The Marketplace. The architecture also includes a Data Governance Model, Protection and Privacy Enforcement and the Ethical Framework as depicted in Figure 2. The architecture allows for integrated data acquisition and analytics. It also allows data fusion with processing and initial analytics (see 7.6.5) as well as seamless analytics (see 7.6.6) on hybrid data at rest. Integration in PolicyCLOUD follows three directions: (i) architecture integration, (ii) integration with the cloud infrastructure and (iii) integration with Use Case scenarios through the implementation of end-to- end scenarios. Additional integration activities take place along the two frameworks of PolicyCLOUD, (a) the Data Governance model, protection and privacy enforcement mechanism and (b) the Ethical and Legal Compliance framework. For end-to-end data path analysis we have used two Use Case scenarios: (i) the scenario of Use Case 1: “Radicalization incidents” and the scenario of Use Case 2: “Visualization of negative and positive opinions on social networks for different products”. The new updates in this final document provide the following: Analysis of how External Frameworks can be integrated with PolicyCLOUD (section 7.6.11.4); Presentation of the overall Conceptual View and architecture of the Data Marketplace (section 7.9.1); Outline of the mechanisms developed for initialising the Policy Development Toolkit with Policy Model components and the visualization of results (section 7.8.3); Analysis of the Ethical and Legal Compliance Framework positive interventions to the PolicyCLOUD architecture, including the addition of specific fields/parameters to the registration Application Programming Interfaces to be populated with details regarding each individual analytics tool and dataset/data source (section 7.5); Presentation of the integration of the Data Governance model, protection and privacy enforcement mechanisms with the Policy Development Toolkit, the cloud gateways and the marketplace (section 7.10.2), and within the same context, the integration of EGI-Check-in with Keycloak including the integration of the Data Governance model, protection and privacy enforcement mechanisms with the Kubernetes cluster. The document also addresses the Reviewers’ comments to the previous version of the deliverable (Deliverable D2.6), included in the second review report. In order to address these comments, additional updates of Deliverable D2.7 include: (i) links to specific user/stakeholder requirements (D2.5), (ii) descriptions and implementation details for the two remaining pilot Use Cases (Sofia and London) and (iii) reference to EOSC and to the role of the Conceptual Model & Reference Architecture document for the identification of the relevant services and of their providers, and description of the onboarding process based on Deliverable D3.4 [22].This deliverable is submitted to the EC, not yet approved