Periodic Reporting for period 3 - PolicyCLOUD (Policy Management through technologies across the complete data lifecycle on cloud environments.)
Berichtszeitraum: 2022-01-01 bis 2022-12-31
Governments and policy makers are constantly looking for efficient ways for policy modelling, creation and implementation. In the traditional policy making cycle, which is divided into 5 different stages (a. agenda setting, b. policy formulation, c. decision making, d. policy implementation and e. policy evaluation), data is a valuable tool for allowing policy choices to become more evidence-based and analytical.
Relevant data sets can be obtained from open administrative and government data (statistics about populations, economic indicators, education, etc.), data related to social dynamics (e.g. online platforms, social media, crowd-sourcing, internet of things), cloud environments, big data and other data sources. Innovative data-driven approaches for policy making create opportunities for evidence-based policies, modernization of public sectors and assistance of local governance towards enhanced levels of trust.
Analyzing and linking available datasets and new data technologies and approaches, policy makers will be able to deeply understand how public policy and services interact with citizens and therefore to be more citizen-focused, taking account of citizens’ needs, preferences and actual experience of public services.
PolicyCLOUD overall objective was to deliver an integrated cloud-based environment for data-driven policy management. An environment providing decision making support to public authorities for policy modelling, implementation and simulation, as well as for policy enforcement and adaptation. Stakeholders will have a tool to specify the requirements and parameters to be considered during the collection and analysis of different data sets, thus tailoring policy making in a variety of use cases and scenarios. PolicyCLOUD technologies aim at optimizing policies across sectors by utilizing inter-linked data sets and assessing the impact of policies, considering different criteria for population segmentation (i.e. area, regional, local, national), in order to ensure high impact of the proposed policies on targeted groups.
Relevant data sets can be obtained from open administrative and government data (statistics about populations, economic indicators, education, etc.), data related to social dynamics (e.g. online platforms, social media, crowd-sourcing, internet of things), cloud environments, big data and other data sources. Innovative data-driven approaches for policy making create opportunities for evidence-based policies, modernization of public sectors and assistance of local governance towards enhanced levels of trust.
Analyzing and linking available datasets and new data technologies and approaches, policy makers will be able to deeply understand how public policy and services interact with citizens and therefore to be more citizen-focused, taking account of citizens’ needs, preferences and actual experience of public services.
PolicyCLOUD overall objective was to deliver an integrated cloud-based environment for data-driven policy management. An environment providing decision making support to public authorities for policy modelling, implementation and simulation, as well as for policy enforcement and adaptation. Stakeholders will have a tool to specify the requirements and parameters to be considered during the collection and analysis of different data sets, thus tailoring policy making in a variety of use cases and scenarios. PolicyCLOUD technologies aim at optimizing policies across sectors by utilizing inter-linked data sets and assessing the impact of policies, considering different criteria for population segmentation (i.e. area, regional, local, national), in order to ensure high impact of the proposed policies on targeted groups.
These are the main project results at the end of the project:
Technical results:
• An extensible, highly scalable cloud architecture supporting generic components, made up of five layers: (1) cloud based environment and data management, (2) data acquisition and analytics, (3) policies management framework, (4) policy development toolkit, and (5) data marketplace. The architecture also incorporates a data protection and privacy enforcement mechanism which adds an ethical and legal framework to the whole architecture.
• A set of innovative tools running on top of cloud infrastructures. This includes data modelling, data cleaning, data interoperability, data aggregation, incremental data analytics, opinion mining, sentiment analysis, social dynamics and social dynamics analytics. It is important to highlight that all analytical tools and models developed during the scope of PolicyCLOUD are generic both in terms of needs, datasets, and scenarios. Analytical tools and models have been applied and reused in different use cases that contain different types of data.
• PolicyCLOUD introduces a novel approach for achieving Enhanced Semantic Interoperability in the domain of policy making, the SemAI. The latter introduces a multi-layer and hybrid mechanism for semantic interoperability across diverse policy related datasets, both within a single domain and across different policy making domains, shifting from data-based to content-based storage and retrieval.
• The PolicyCLOUD platform may be deployed over any cloud serverless environment so that the many analytics technologies can be considered as decoupled from the infrastructure.
• A method to onboard providers and resources to the EOSC catalogue and marketplace has been developed
Use case oriented results:
• Methodologies for cloud use by public authorities, encompassing not only the methodology for creating policies in cloud environments, but also an overview of the main characteristics and advantages of the cloud and big data for public administration.
• The Policy Development Toolkit (PDT), which includes the data visualisation framework, and the Policy Modelling Editor (PME). These components support the evidence based policies creation process by facilitating the use of data sources, analytical tools to process the data, and KPIs to evaluate the policies. They enable the interaction of the user with the PolicyCLOUD analytics components and the datastore, allowing policy makers to create, update and evaluate policies.
• Three use cases, comprising several scenarios, designed, prototyped and experimented in close collaboration with end-users, all of them with different requirements in terms of needs and data sets, proving the adaptability of PolicyCLOUD analytical models and tools.
Communication, exploitation and business development results:
• Continuous communication content production for the web and social media, which include news, articles, podcasts, videos and policy briefs, focusing, in the last stage of the project, on highlighting the PolicyCLOUD Pilots.
• Implementation of the outreach and stakeholder engagement strategy via workshops and webinars, e.g. the Major Cities of Europe 2022 conference, the Data for Policy 2022 or the data Week 2022 organised by the BDVA .
• Publication of a whitepaper, together with StandICT EU project, on the standardisation of data interoperability in data driven policymaking.
• Design of business models, individual and joint exploitation plans towards the sustainability of the PolicyCLOUD results.
Technical results:
• An extensible, highly scalable cloud architecture supporting generic components, made up of five layers: (1) cloud based environment and data management, (2) data acquisition and analytics, (3) policies management framework, (4) policy development toolkit, and (5) data marketplace. The architecture also incorporates a data protection and privacy enforcement mechanism which adds an ethical and legal framework to the whole architecture.
• A set of innovative tools running on top of cloud infrastructures. This includes data modelling, data cleaning, data interoperability, data aggregation, incremental data analytics, opinion mining, sentiment analysis, social dynamics and social dynamics analytics. It is important to highlight that all analytical tools and models developed during the scope of PolicyCLOUD are generic both in terms of needs, datasets, and scenarios. Analytical tools and models have been applied and reused in different use cases that contain different types of data.
• PolicyCLOUD introduces a novel approach for achieving Enhanced Semantic Interoperability in the domain of policy making, the SemAI. The latter introduces a multi-layer and hybrid mechanism for semantic interoperability across diverse policy related datasets, both within a single domain and across different policy making domains, shifting from data-based to content-based storage and retrieval.
• The PolicyCLOUD platform may be deployed over any cloud serverless environment so that the many analytics technologies can be considered as decoupled from the infrastructure.
• A method to onboard providers and resources to the EOSC catalogue and marketplace has been developed
Use case oriented results:
• Methodologies for cloud use by public authorities, encompassing not only the methodology for creating policies in cloud environments, but also an overview of the main characteristics and advantages of the cloud and big data for public administration.
• The Policy Development Toolkit (PDT), which includes the data visualisation framework, and the Policy Modelling Editor (PME). These components support the evidence based policies creation process by facilitating the use of data sources, analytical tools to process the data, and KPIs to evaluate the policies. They enable the interaction of the user with the PolicyCLOUD analytics components and the datastore, allowing policy makers to create, update and evaluate policies.
• Three use cases, comprising several scenarios, designed, prototyped and experimented in close collaboration with end-users, all of them with different requirements in terms of needs and data sets, proving the adaptability of PolicyCLOUD analytical models and tools.
Communication, exploitation and business development results:
• Continuous communication content production for the web and social media, which include news, articles, podcasts, videos and policy briefs, focusing, in the last stage of the project, on highlighting the PolicyCLOUD Pilots.
• Implementation of the outreach and stakeholder engagement strategy via workshops and webinars, e.g. the Major Cities of Europe 2022 conference, the Data for Policy 2022 or the data Week 2022 organised by the BDVA .
• Publication of a whitepaper, together with StandICT EU project, on the standardisation of data interoperability in data driven policymaking.
• Design of business models, individual and joint exploitation plans towards the sustainability of the PolicyCLOUD results.
PolicyCLOUD delivered services that will facilitate a data -driven policy management:
• A policy development toolkit: Automated tools enabling data manipulation, modelling and visualization.
• A data marketplace: Repository of exploitable data and knowledge for policy making scenarios.
• Cloud capabilities: Adaptable cloud gateways and APIs to obtain data from heterogeneous sources.
• Reusable models and analytical tools: Technologies enabling opinion mining, sentiment, social dynamics and behavioral data analysis.
• Policies management framework: Decision tool enabling the integration of data collection, modelling and simulation technologies.
• Ethics framework: Documented approach ensuring the provision of privacy and security for sensitive data.
These services will impact and boost benefits for all the project stakeholders and the entire society in general.
• Enlarging the evidence-base for effective policy making. Extracting meaningful information from aggregated data sources.
• Facilitating interoperability, reusability and scalability for efficient policy making through the application of PolicyCLOUD models and tools to different contexts and sectors.
• Realizing a social-centric approach considering legal and security aspects; taking account of citizens’ needs, preferences and actual experience of public services and analyzing social dynamics to increase citizen participation and engagement in the policy creation process.
• Promoting data-driven innovation; modernization of the public administration and public sector through the use of cloud, big data and data analytics technologies.
• Boosting the data driven economy; the policy development toolkit and the data marketplace are expected to have a direct impact in the increase of productivity.
• A policy development toolkit: Automated tools enabling data manipulation, modelling and visualization.
• A data marketplace: Repository of exploitable data and knowledge for policy making scenarios.
• Cloud capabilities: Adaptable cloud gateways and APIs to obtain data from heterogeneous sources.
• Reusable models and analytical tools: Technologies enabling opinion mining, sentiment, social dynamics and behavioral data analysis.
• Policies management framework: Decision tool enabling the integration of data collection, modelling and simulation technologies.
• Ethics framework: Documented approach ensuring the provision of privacy and security for sensitive data.
These services will impact and boost benefits for all the project stakeholders and the entire society in general.
• Enlarging the evidence-base for effective policy making. Extracting meaningful information from aggregated data sources.
• Facilitating interoperability, reusability and scalability for efficient policy making through the application of PolicyCLOUD models and tools to different contexts and sectors.
• Realizing a social-centric approach considering legal and security aspects; taking account of citizens’ needs, preferences and actual experience of public services and analyzing social dynamics to increase citizen participation and engagement in the policy creation process.
• Promoting data-driven innovation; modernization of the public administration and public sector through the use of cloud, big data and data analytics technologies.
• Boosting the data driven economy; the policy development toolkit and the data marketplace are expected to have a direct impact in the increase of productivity.